R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(321.61
+ ,26.75
+ ,0
+ ,0
+ ,1546.66
+ ,9.26
+ ,0.037987
+ ,345.85
+ ,22.33
+ ,0
+ ,0
+ ,1570.98
+ ,9.19
+ ,0.038863
+ ,338.60
+ ,16.38
+ ,0
+ ,0
+ ,1709.05
+ ,8.7
+ ,0.031132
+ ,345.64
+ ,12.77
+ ,0
+ ,0
+ ,1818.6
+ ,7.78
+ ,0.022556
+ ,340.71
+ ,11.89
+ ,0
+ ,0
+ ,1783.97
+ ,7.3
+ ,0.015903
+ ,342.49
+ ,13.49
+ ,0
+ ,0
+ ,1876.7
+ ,7.71
+ ,0.014911
+ ,342.65
+ ,11.95
+ ,0
+ ,0
+ ,1892.71
+ ,7.8
+ ,0.017658
+ ,348.68
+ ,9.88
+ ,0
+ ,0
+ ,1775.3
+ ,7.3
+ ,0.01577
+ ,377.36
+ ,13.42
+ ,0
+ ,0
+ ,1898.33
+ ,7.17
+ ,0.015741
+ ,418.05
+ ,14.03
+ ,0
+ ,0
+ ,1767.57
+ ,7.45
+ ,0.017544
+ ,423.13
+ ,14.01
+ ,0
+ ,0
+ ,1877.8
+ ,7.43
+ ,0.014719
+ ,397.69
+ ,14.47
+ ,0
+ ,0
+ ,1914.22
+ ,7.25
+ ,0.012844
+ ,390.80
+ ,15.44
+ ,0
+ ,0
+ ,1895.94
+ ,7.11
+ ,0.010979
+ ,408.29
+ ,18.1
+ ,0
+ ,0
+ ,2158.03
+ ,7.08
+ ,0.014599
+ ,401.02
+ ,17.28
+ ,0
+ ,0
+ ,2223.98
+ ,7.25
+ ,0.021043
+ ,409.24
+ ,17.74
+ ,0
+ ,0
+ ,2304.68
+ ,7.25
+ ,0.030331
+ ,439.28
+ ,18.05
+ ,0
+ ,0
+ ,2286.35
+ ,8.02
+ ,0.037753
+ ,459.95
+ ,18.41
+ ,0
+ ,0
+ ,2291.56
+ ,8.61
+ ,0.038567
+ ,449.66
+ ,18.71
+ ,0
+ ,0
+ ,2418.52
+ ,8.4
+ ,0.03653
+ ,451.14
+ ,19.62
+ ,0
+ ,0
+ ,2572.06
+ ,8.45
+ ,0.039269
+ ,460.66
+ ,18.88
+ ,0
+ ,0
+ ,2662.94
+ ,8.76
+ ,0.042844
+ ,460.23
+ ,18.32
+ ,0
+ ,0
+ ,2596.27
+ ,9.42
+ ,0.043557
+ ,465.69
+ ,18.63
+ ,0
+ ,0
+ ,1993.52
+ ,9.52
+ ,0.045331
+ ,468.01
+ ,17.87
+ ,0
+ ,0
+ ,1833.54
+ ,8.86
+ ,0.04529
+ ,486.74
+ ,16.77
+ ,0
+ ,0
+ ,1938.82
+ ,8.99
+ ,0.044344
+ ,475.89
+ ,16.5
+ ,0
+ ,0
+ ,1958.21
+ ,8.67
+ ,0.040468
+ ,441.52
+ ,15.9
+ ,0
+ ,0
+ ,2071.61
+ ,8.21
+ ,0.039427
+ ,443.63
+ ,14.86
+ ,0
+ ,0
+ ,1988.05
+ ,8.37
+ ,0.039251
+ ,451.62
+ ,16.42
+ ,0
+ ,0
+ ,2032.32
+ ,8.72
+ ,0.039042
+ ,451.14
+ ,16.36
+ ,0
+ ,0
+ ,2031.11
+ ,9.09
+ ,0.038904
+ ,450.88
+ ,15.49
+ ,0
+ ,0
+ ,2141.7
+ ,8.92
+ ,0.039648
+ ,437.56
+ ,14.47
+ ,0
+ ,0
+ ,2128.72
+ ,9.06
+ ,0.041301
+ ,431.18
+ ,14.57
+ ,0
+ ,0
+ ,2031.64
+ ,9.26
+ ,0.04021
+ ,412.02
+ ,13.22
+ ,0
+ ,0
+ ,2112.9
+ ,8.98
+ ,0.041739
+ ,407.14
+ ,12.23
+ ,0
+ ,0
+ ,2148.64
+ ,8.8
+ ,0.042498
+ ,420.48
+ ,12.53
+ ,0
+ ,0
+ ,2114.5
+ ,8.96
+ ,0.042461
+ ,418.92
+ ,14.68
+ ,0
+ ,0
+ ,2168.56
+ ,9.11
+ ,0.044194
+ ,403.57
+ ,16.45
+ ,0
+ ,0
+ ,2342.31
+ ,9.09
+ ,0.046672
+ ,387.55
+ ,16.52
+ ,0
+ ,0
+ ,2258.38
+ ,9.17
+ ,0.048276
+ ,390.02
+ ,18.1
+ ,0
+ ,0
+ ,2293.61
+ ,9.36
+ ,0.049785
+ ,384.37
+ ,19.39
+ ,0
+ ,0
+ ,2418.79
+ ,9.18
+ ,0.051238
+ ,370.62
+ ,18.22
+ ,0
+ ,0
+ ,2480.14
+ ,8.86
+ ,0.053617
+ ,367.90
+ ,17.8
+ ,0
+ ,0
+ ,2440.05
+ ,8.28
+ ,0.051695
+ ,374.91
+ ,17.67
+ ,0
+ ,0
+ ,2660.65
+ ,8.02
+ ,0.049789
+ ,365.15
+ ,16.87
+ ,0
+ ,0
+ ,2737.26
+ ,8.11
+ ,0.047059
+ ,361.91
+ ,17.69
+ ,0
+ ,0
+ ,2692.81
+ ,8.19
+ ,0.043406
+ ,367.03
+ ,18.41
+ ,0
+ ,0
+ ,2645.07
+ ,8.01
+ ,0.044925
+ ,395.19
+ ,18.38
+ ,0
+ ,0
+ ,2706.26
+ ,7.87
+ ,0.04655
+ ,409.25
+ ,19.37
+ ,0
+ ,0
+ ,2753.19
+ ,7.84
+ ,0.046473
+ ,410.49
+ ,20.59
+ ,0
+ ,0
+ ,2590.53
+ ,8.21
+ ,0.052023
+ ,416.58
+ ,19.68
+ ,0
+ ,0
+ ,2627.24
+ ,8.47
+ ,0.052632
+ ,392.21
+ ,18.12
+ ,0
+ ,0
+ ,2707.2
+ ,8.59
+ ,0.05233
+ ,374.29
+ ,16.32
+ ,0
+ ,0
+ ,2656.75
+ ,8.79
+ ,0.047116
+ ,369.05
+ ,16.21
+ ,0
+ ,0
+ ,2876.65
+ ,8.76
+ ,0.043619
+ ,352.19
+ ,14.93
+ ,0
+ ,0
+ ,2880.68
+ ,8.48
+ ,0.046737
+ ,362.85
+ ,16.81
+ ,0
+ ,0
+ ,2905.19
+ ,8.47
+ ,0.048232
+ ,395.47
+ ,26.54
+ ,0
+ ,0
+ ,2614.35
+ ,8.75
+ ,0.05618
+ ,388.82
+ ,33.62
+ ,0
+ ,0
+ ,2452.47
+ ,8.89
+ ,0.0616
+ ,380.39
+ ,34.85
+ ,0
+ ,0
+ ,2442.32
+ ,8.72
+ ,0.062898
+ ,381.73
+ ,31.54
+ ,0
+ ,0
+ ,2559.64
+ ,8.39
+ ,0.062748
+ ,377.69
+ ,26.61
+ ,0
+ ,0
+ ,2633.65
+ ,8.08
+ ,0.061063
+ ,383.04
+ ,22.81
+ ,0
+ ,0
+ ,2736.38
+ ,8.09
+ ,0.056515
+ ,363.89
+ ,18.53
+ ,0
+ ,0
+ ,2882.17
+ ,7.85
+ ,0.053125
+ ,363.23
+ ,18.21
+ ,0
+ ,0
+ ,2913.85
+ ,8.11
+ ,0.048951
+ ,358.37
+ ,18.49
+ ,0
+ ,0
+ ,2887.86
+ ,8.04
+ ,0.048875
+ ,356.97
+ ,18.72
+ ,0
+ ,0
+ ,3027.49
+ ,8.07
+ ,0.049536
+ ,366.87
+ ,17.78
+ ,0
+ ,0
+ ,2906.74
+ ,8.28
+ ,0.046959
+ ,367.57
+ ,19.02
+ ,0
+ ,0
+ ,3024.81
+ ,8.27
+ ,0.044479
+ ,355.88
+ ,19.3
+ ,0
+ ,0
+ ,3043.59
+ ,7.9
+ ,0.037994
+ ,348.88
+ ,19.95
+ ,0
+ ,0
+ ,3016.76
+ ,7.65
+ ,0.033911
+ ,358.77
+ ,21.56
+ ,0
+ ,0
+ ,3069.9
+ ,7.53
+ ,0.029213
+ ,360.42
+ ,20.41
+ ,0
+ ,0
+ ,2894.67
+ ,7.42
+ ,0.029895
+ ,361.08
+ ,17.63
+ ,0
+ ,0
+ ,3168.82
+ ,7.09
+ ,0.030643
+ ,354.57
+ ,17.52
+ ,0
+ ,0
+ ,3223.38
+ ,7.03
+ ,0.026003
+ ,353.73
+ ,17.65
+ ,0
+ ,0
+ ,3267.66
+ ,7.34
+ ,0.02819
+ ,344.20
+ ,17.35
+ ,0
+ ,0
+ ,3235.46
+ ,7.54
+ ,0.031852
+ ,338.34
+ ,18.65
+ ,0
+ ,0
+ ,3359.11
+ ,7.48
+ ,0.031805
+ ,337.21
+ ,19.52
+ ,0
+ ,0
+ ,3396.87
+ ,7.39
+ ,0.030236
+ ,340.96
+ ,20.88
+ ,0
+ ,0
+ ,3318.51
+ ,7.26
+ ,0.030882
+ ,353.29
+ ,20.18
+ ,0
+ ,0
+ ,3393.77
+ ,6.84
+ ,0.031571
+ ,342.67
+ ,19.62
+ ,0
+ ,0
+ ,3257.34
+ ,6.59
+ ,0.031479
+ ,345.71
+ ,20.19
+ ,0
+ ,0
+ ,3271.65
+ ,6.42
+ ,0.029883
+ ,344.17
+ ,20.04
+ ,0
+ ,0
+ ,3226.27
+ ,6.59
+ ,0.032023
+ ,334.92
+ ,18.9
+ ,0
+ ,0
+ ,3305.15
+ ,6.87
+ ,0.030479
+ ,334.81
+ ,17.93
+ ,0
+ ,0
+ ,3301.1
+ ,6.77
+ ,0.029007
+ ,329.05
+ ,17.24
+ ,0
+ ,0
+ ,3310.02
+ ,6.6
+ ,0.032585
+ ,329.31
+ ,18.23
+ ,0
+ ,0
+ ,3370.8
+ ,6.26
+ ,0.032468
+ ,330.25
+ ,18.5
+ ,0
+ ,0
+ ,3435.1
+ ,5.98
+ ,0.030869
+ ,341.89
+ ,18.44
+ ,0
+ ,0
+ ,3427.54
+ ,5.97
+ ,0.032258
+ ,367.74
+ ,18.17
+ ,0
+ ,0
+ ,3527.42
+ ,6.04
+ ,0.032212
+ ,371.93
+ ,17.37
+ ,0
+ ,0
+ ,3516.07
+ ,5.96
+ ,0.029957
+ ,392.79
+ ,16.37
+ ,0
+ ,0
+ ,3539.46
+ ,5.81
+ ,0.027758
+ ,377.97
+ ,16.43
+ ,0
+ ,0
+ ,3651.24
+ ,5.68
+ ,0.027679
+ ,354.93
+ ,15.8
+ ,0
+ ,0
+ ,3555.11
+ ,5.36
+ ,0.026893
+ ,364.40
+ ,16.44
+ ,0
+ ,0
+ ,3680.58
+ ,5.33
+ ,0.027504
+ ,374.05
+ ,15.09
+ ,0
+ ,0
+ ,3683.94
+ ,5.72
+ ,0.026761
+ ,383.63
+ ,13.36
+ ,0
+ ,0
+ ,3754.08
+ ,5.77
+ ,0.027484
+ ,386.56
+ ,14.17
+ ,0
+ ,0
+ ,3978.35
+ ,5.75
+ ,0.025245
+ ,381.90
+ ,13.75
+ ,0
+ ,0
+ ,3832.01
+ ,5.97
+ ,0.025157
+ ,384.08
+ ,13.69
+ ,0
+ ,0
+ ,3635.95
+ ,6.48
+ ,0.02507
+ ,377.29
+ ,15.15
+ ,0
+ ,0
+ ,3681.68
+ ,6.97
+ ,0.023611
+ ,381.54
+ ,16.43
+ ,0
+ ,0
+ ,3758.36
+ ,7.18
+ ,0.022885
+ ,385.60
+ ,17.23
+ ,0
+ ,0
+ ,3624.95
+ ,7.1
+ ,0.024931
+ ,385.47
+ ,18.04
+ ,0
+ ,0
+ ,3764.49
+ ,7.3
+ ,0.027701
+ ,380.40
+ ,16.98
+ ,0
+ ,0
+ ,3913.41
+ ,7.24
+ ,0.029006
+ ,391.74
+ ,16.13
+ ,0
+ ,0
+ ,3843.18
+ ,7.46
+ ,0.029635
+ ,389.57
+ ,16.48
+ ,0
+ ,0
+ ,3908.11
+ ,7.74
+ ,0.026081
+ ,384.29
+ ,17.2
+ ,0
+ ,0
+ ,3739.22
+ ,7.96
+ ,0.026749
+ ,379.26
+ ,16.13
+ ,0
+ ,0
+ ,3834.43
+ ,7.81
+ ,0.026749
+ ,378.44
+ ,16.88
+ ,0
+ ,0
+ ,3843.85
+ ,7.78
+ ,0.028044
+ ,376.63
+ ,17.44
+ ,0
+ ,0
+ ,4011.04
+ ,7.47
+ ,0.02863
+ ,382.48
+ ,17.35
+ ,0
+ ,0
+ ,4157.68
+ ,7.2
+ ,0.028533
+ ,390.89
+ ,18.77
+ ,0
+ ,0
+ ,4321.26
+ ,7.06
+ ,0.030529
+ ,385.04
+ ,18.43
+ ,0
+ ,0
+ ,4465.13
+ ,6.63
+ ,0.031864
+ ,387.58
+ ,17.33
+ ,0
+ ,0
+ ,4556.9
+ ,6.17
+ ,0.030405
+ ,386.19
+ ,16.06
+ ,0
+ ,0
+ ,4708.46
+ ,6.28
+ ,0.027628
+ ,383.78
+ ,16.49
+ ,0
+ ,0
+ ,4610.55
+ ,6.49
+ ,0.026174
+ ,383.10
+ ,16.77
+ ,0
+ ,0
+ ,4789.07
+ ,6.2
+ ,0.025435
+ ,383.25
+ ,16.18
+ ,0
+ ,0
+ ,4755.47
+ ,6.04
+ ,0.028094
+ ,385.19
+ ,16.82
+ ,0
+ ,0
+ ,5074.48
+ ,5.93
+ ,0.026052
+ ,387.35
+ ,17.93
+ ,0
+ ,0
+ ,5117.11
+ ,5.71
+ ,0.025384
+ ,400.49
+ ,17.79
+ ,0
+ ,0
+ ,5395.29
+ ,5.65
+ ,0.027279
+ ,404.53
+ ,17.69
+ ,0
+ ,0
+ ,5485.61
+ ,5.81
+ ,0.026508
+ ,396.15
+ ,19.46
+ ,0
+ ,0
+ ,5587.13
+ ,6.27
+ ,0.028402
+ ,392.79
+ ,20.78
+ ,0
+ ,0
+ ,5569.07
+ ,6.51
+ ,0.028966
+ ,391.96
+ ,19.12
+ ,0
+ ,0
+ ,5643.17
+ ,6.74
+ ,0.028909
+ ,385.04
+ ,18.56
+ ,0
+ ,0
+ ,5654.62
+ ,6.91
+ ,0.027541
+ ,383.58
+ ,19.56
+ ,0
+ ,0
+ ,5528.9
+ ,6.87
+ ,0.029508
+ ,387.46
+ ,20.19
+ ,0
+ ,0
+ ,5616.2
+ ,6.64
+ ,0.028777
+ ,382.90
+ ,22.14
+ ,0
+ ,0
+ ,5882.16
+ ,6.83
+ ,0.030026
+ ,381.04
+ ,23.43
+ ,0
+ ,0
+ ,6029.37
+ ,6.53
+ ,0.029928
+ ,377.69
+ ,22.25
+ ,0
+ ,0
+ ,6521.69
+ ,6.2
+ ,0.032552
+ ,368.95
+ ,23.51
+ ,0
+ ,0
+ ,6448.26
+ ,6.3
+ ,0.033225
+ ,353.87
+ ,23.29
+ ,0
+ ,0
+ ,6813.08
+ ,6.58
+ ,0.03044
+ ,347.03
+ ,20.54
+ ,0
+ ,0
+ ,6877.73
+ ,6.42
+ ,0.030342
+ ,351.49
+ ,19.42
+ ,0
+ ,0
+ ,6583.47
+ ,6.69
+ ,0.027617
+ ,344.23
+ ,17.98
+ ,0
+ ,0
+ ,7008.98
+ ,6.89
+ ,0.024952
+ ,344.09
+ ,19.47
+ ,0
+ ,0
+ ,7331.03
+ ,6.71
+ ,0.02235
+ ,340.51
+ ,18.02
+ ,0
+ ,0
+ ,7672.78
+ ,6.49
+ ,0.022974
+ ,323.90
+ ,18.45
+ ,0
+ ,0
+ ,8222.6
+ ,6.22
+ ,0.022293
+ ,324.02
+ ,18.79
+ ,0
+ ,0
+ ,7622.41
+ ,6.3
+ ,0.02225
+ ,323.11
+ ,18.73
+ ,0
+ ,0
+ ,7945.25
+ ,6.21
+ ,0.021546
+ ,324.36
+ ,20.12
+ ,0
+ ,0
+ ,7442.07
+ ,6.03
+ ,0.020846
+ ,305.55
+ ,19.16
+ ,0
+ ,0
+ ,7823.12
+ ,5.88
+ ,0.018285
+ ,288.59
+ ,17.24
+ ,0
+ ,0
+ ,7908.24
+ ,5.81
+ ,0.017024
+ ,289.15
+ ,15.07
+ ,0
+ ,0
+ ,7906.49
+ ,5.54
+ ,0.015713
+ ,297.49
+ ,14.18
+ ,0
+ ,0
+ ,8545.71
+ ,5.57
+ ,0.014411
+ ,295.94
+ ,13.24
+ ,0
+ ,0
+ ,8799.8
+ ,5.65
+ ,0.01375
+ ,308.29
+ ,13.39
+ ,0
+ ,0
+ ,9063.36
+ ,5.64
+ ,0.014357
+ ,299.10
+ ,13.97
+ ,0
+ ,0
+ ,8899.94
+ ,5.65
+ ,0.016864
+ ,292.32
+ ,12.48
+ ,0
+ ,0
+ ,8952.01
+ ,5.5
+ ,0.016843
+ ,292.87
+ ,12.72
+ ,0
+ ,0
+ ,8883.28
+ ,5.46
+ ,0.016822
+ ,284.11
+ ,12.49
+ ,0
+ ,0
+ ,7539.06
+ ,5.34
+ ,0.016169
+ ,288.98
+ ,13.8
+ ,0
+ ,0
+ ,7842.61
+ ,4.81
+ ,0.014888
+ ,295.93
+ ,13.26
+ ,0
+ ,0
+ ,8592.9
+ ,4.53
+ ,0.014851
+ ,294.17
+ ,11.88
+ ,0
+ ,0
+ ,9116.54
+ ,4.83
+ ,0.01548
+ ,291.68
+ ,10.41
+ ,0
+ ,0
+ ,9181.42
+ ,4.65
+ ,0.016119
+ ,287.07
+ ,11.32
+ ,0
+ ,0
+ ,9358.82
+ ,4.72
+ ,0.016708
+ ,287.33
+ ,10.75
+ ,0
+ ,0
+ ,9306.57
+ ,5
+ ,0.016059
+ ,285.96
+ ,12.86
+ ,0
+ ,0
+ ,9786.15
+ ,5.23
+ ,0.017263
+ ,282.62
+ ,15.73
+ ,0
+ ,0
+ ,10789.03
+ ,5.18
+ ,0.022769
+ ,276.44
+ ,16.12
+ ,0
+ ,0
+ ,10559.73
+ ,5.54
+ ,0.020885
+ ,261.31
+ ,16.24
+ ,0
+ ,0
+ ,10970.79
+ ,5.9
+ ,0.019632
+ ,256.08
+ ,18.75
+ ,0
+ ,0
+ ,10655.14
+ ,5.79
+ ,0.021446
+ ,256.69
+ ,20.21
+ ,0
+ ,0
+ ,10829.27
+ ,5.94
+ ,0.022644
+ ,264.74
+ ,22.37
+ ,0
+ ,0
+ ,10336.94
+ ,5.92
+ ,0.026284
+ ,310.72
+ ,22.19
+ ,0
+ ,0
+ ,10729.85
+ ,6.11
+ ,0.02561
+ ,293.18
+ ,24.22
+ ,0
+ ,0
+ ,10877.8
+ ,6.03
+ ,0.02622
+ ,283.07
+ ,25.01
+ ,0
+ ,0
+ ,11497.11
+ ,6.28
+ ,0.026846
+ ,284.32
+ ,25.21
+ ,0
+ ,0
+ ,10940.52
+ ,6.66
+ ,0.027389
+ ,299.86
+ ,27.15
+ ,0
+ ,0
+ ,10128.3
+ ,6.52
+ ,0.032219
+ ,286.39
+ ,27.49
+ ,0
+ ,0
+ ,10921.91
+ ,6.26
+ ,0.037576
+ ,279.69
+ ,23.45
+ ,0
+ ,0
+ ,10733.9
+ ,5.99
+ ,0.030686
+ ,275.19
+ ,27.23
+ ,0
+ ,0
+ ,10522.32
+ ,6.44
+ ,0.031889
+ ,285.73
+ ,29.62
+ ,0
+ ,0
+ ,10447.88
+ ,6.1
+ ,0.037304
+ ,281.59
+ ,28.16
+ ,0
+ ,0
+ ,10521.97
+ ,6.05
+ ,0.036593
+ ,274.47
+ ,29.41
+ ,0
+ ,0
+ ,11215.9
+ ,5.83
+ ,0.034111
+ ,273.68
+ ,32.08
+ ,0
+ ,0
+ ,10650.91
+ ,5.8
+ ,0.034544
+ ,270.00
+ ,31.4
+ ,0
+ ,0
+ ,10971.13
+ ,5.74
+ ,0.034483
+ ,266.01
+ ,32.33
+ ,0
+ ,0
+ ,10414.48
+ ,5.72
+ ,0.034462
+ ,271.45
+ ,25.28
+ ,0
+ ,0
+ ,10786.84
+ ,5.24
+ ,0.033868
+ ,265.49
+ ,25.95
+ ,0
+ ,0
+ ,10887.35
+ ,5.16
+ ,0.037322
+ ,261.87
+ ,27.24
+ ,0
+ ,0
+ ,10495.27
+ ,5.1
+ ,0.035336
+ ,263.03
+ ,25.02
+ ,0
+ ,0
+ ,9878.77
+ ,4.89
+ ,0.029206
+ ,260.48
+ ,25.66
+ ,0
+ ,0
+ ,10734.96
+ ,5.14
+ ,0.032691
+ ,272.36
+ ,27.55
+ ,0
+ ,0
+ ,10911.93
+ ,5.39
+ ,0.036152
+ ,269.82
+ ,26.97
+ ,0
+ ,0
+ ,10502.39
+ ,5.28
+ ,0.032483
+ ,267.53
+ ,24.8
+ ,0
+ ,0
+ ,10522.8
+ ,5.24
+ ,0.027199
+ ,272.39
+ ,25.81
+ ,0
+ ,0
+ ,9949.74
+ ,4.97
+ ,0.027199
+ ,283.42
+ ,25.03
+ ,0
+ ,0
+ ,8847.55
+ ,4.73
+ ,0.026482
+ ,283.06
+ ,20.73
+ ,0
+ ,0
+ ,9075.13
+ ,4.57
+ ,0.021264
+ ,276.16
+ ,18.69
+ ,0
+ ,0
+ ,9851.55
+ ,4.65
+ ,0.018955
+ ,275.85
+ ,18.52
+ ,0
+ ,0
+ ,10021.49
+ ,5.09
+ ,0.015517
+ ,281.51
+ ,19.15
+ ,0
+ ,0
+ ,9920.01
+ ,5.04
+ ,0.011422
+ ,295.50
+ ,19.98
+ ,0
+ ,0
+ ,10106.12
+ ,4.91
+ ,0.011377
+ ,294.06
+ ,23.64
+ ,0
+ ,0
+ ,10403.94
+ ,5.28
+ ,0.014756
+ ,302.68
+ ,25.43
+ ,0
+ ,0
+ ,9946.22
+ ,5.21
+ ,0.016393
+ ,314.58
+ ,25.69
+ ,0
+ ,0
+ ,9925.25
+ ,5.16
+ ,0.011818
+ ,321.18
+ ,24.49
+ ,0
+ ,0
+ ,9243.26
+ ,4.93
+ ,0.010674
+ ,313.29
+ ,25.75
+ ,0
+ ,0
+ ,8736.59
+ ,4.65
+ ,0.014648
+ ,310.25
+ ,26.78
+ ,0
+ ,0
+ ,8663.5
+ ,4.26
+ ,0.018028
+ ,319.14
+ ,28.28
+ ,0
+ ,0
+ ,7591.93
+ ,3.87
+ ,0.015143
+ ,316.56
+ ,27.53
+ ,0
+ ,0
+ ,8397.03
+ ,3.94
+ ,0.020259
+ ,319.07
+ ,24.79
+ ,0
+ ,0
+ ,8896.09
+ ,4.05
+ ,0.021984
+ ,331.92
+ ,27.89
+ ,0
+ ,0
+ ,8341.63
+ ,4.03
+ ,0.023769
+ ,356.86
+ ,30.77
+ ,0
+ ,0
+ ,8053.81
+ ,4.05
+ ,0.025974
+ ,358.97
+ ,32.88
+ ,0
+ ,0
+ ,7891.08
+ ,3.9
+ ,0.029809
+ ,340.55
+ ,30.36
+ ,1
+ ,0
+ ,7992.13
+ ,3.81
+ ,0.030201
+ ,328.18
+ ,25.49
+ ,1
+ ,0
+ ,8480.09
+ ,3.96
+ ,0.022247
+ ,355.68
+ ,26.06
+ ,1
+ ,0
+ ,8850.26
+ ,3.57
+ ,0.020578
+ ,356.35
+ ,27.91
+ ,1
+ ,0
+ ,8985.44
+ ,3.33
+ ,0.021123
+ ,350.99
+ ,28.59
+ ,1
+ ,0
+ ,9233.8
+ ,3.98
+ ,0.021099
+ ,359.77
+ ,29.68
+ ,1
+ ,0
+ ,9415.82
+ ,4.45
+ ,0.021583
+ ,378.95
+ ,26.88
+ ,1
+ ,0
+ ,9275.06
+ ,4.27
+ ,0.023204
+ ,378.92
+ ,29.01
+ ,1
+ ,0
+ ,9801.12
+ ,4.29
+ ,0.020408
+ ,389.91
+ ,29.12
+ ,1
+ ,0
+ ,9782.46
+ ,4.3
+ ,0.01765
+ ,406.11
+ ,29.95
+ ,1
+ ,0
+ ,10453.92
+ ,4.27
+ ,0.018795
+ ,413.79
+ ,31.4
+ ,1
+ ,0
+ ,10488.07
+ ,4.15
+ ,0.019263
+ ,404.95
+ ,31.32
+ ,1
+ ,0
+ ,10583.92
+ ,4.08
+ ,0.016931
+ ,406.67
+ ,33.67
+ ,1
+ ,0
+ ,10357.7
+ ,3.83
+ ,0.017372
+ ,403.26
+ ,33.71
+ ,1
+ ,0
+ ,10225.57
+ ,4.35
+ ,0.022851
+ ,383.78
+ ,37.63
+ ,1
+ ,0
+ ,10188.45
+ ,4.72
+ ,0.030518
+ ,392.48
+ ,35.54
+ ,1
+ ,0
+ ,10435.48
+ ,4.73
+ ,0.032662
+ ,398.09
+ ,37.93
+ ,1
+ ,0
+ ,10139.71
+ ,4.5
+ ,0.029908
+ ,400.51
+ ,42.08
+ ,1
+ ,0
+ ,10173.92
+ ,4.28
+ ,0.026544
+ ,405.28
+ ,41.65
+ ,1
+ ,0
+ ,10080.27
+ ,4.13
+ ,0.025378
+ ,420.46
+ ,46.87
+ ,1
+ ,0
+ ,10027.47
+ ,4.1
+ ,0.031892
+ ,439.38
+ ,42.23
+ ,1
+ ,0
+ ,10428.02
+ ,4.19
+ ,0.03523
+ ,442.08
+ ,39.09
+ ,1
+ ,0
+ ,10783.01
+ ,4.23
+ ,0.032556
+ ,424.03
+ ,42.89
+ ,1
+ ,0
+ ,10489.94
+ ,4.22
+ ,0.029698
+ ,423.35
+ ,44.56
+ ,1
+ ,0
+ ,10766.23
+ ,4.17
+ ,0.030075
+ ,434.32
+ ,50.93
+ ,1
+ ,0
+ ,10503.76
+ ,4.5
+ ,0.031483
+ ,429.23
+ ,50.64
+ ,1
+ ,0
+ ,10192.51
+ ,4.34
+ ,0.035106
+ ,421.87
+ ,47.81
+ ,1
+ ,0
+ ,10467.48
+ ,4.14
+ ,0.028027
+ ,430.66
+ ,53.89
+ ,1
+ ,0
+ ,10274.97
+ ,4
+ ,0.025303
+ ,424.48
+ ,56.37
+ ,1
+ ,0
+ ,10640.91
+ ,4.18
+ ,0.031679
+ ,437.93
+ ,61.87
+ ,1
+ ,0
+ ,10481.6
+ ,4.26
+ ,0.036412
+ ,456.05
+ ,61.65
+ ,1
+ ,0
+ ,10568.7
+ ,4.2
+ ,0.046867
+ ,469.90
+ ,58.19
+ ,1
+ ,0
+ ,10440.07
+ ,4.46
+ ,0.043478
+ ,476.67
+ ,54.98
+ ,1
+ ,0
+ ,10805.87
+ ,4.54
+ ,0.034555
+ ,510.10
+ ,56.47
+ ,1
+ ,0
+ ,10717.5
+ ,4.47
+ ,0.034157
+ ,549.86
+ ,62.36
+ ,1
+ ,0
+ ,10864.86
+ ,4.42
+ ,0.039853
+ ,555.00
+ ,59.71
+ ,1
+ ,0
+ ,10993.41
+ ,4.57
+ ,0.035975
+ ,557.09
+ ,60.93
+ ,1
+ ,0
+ ,11109.32
+ ,4.72
+ ,0.033626
+ ,610.65
+ ,68
+ ,1
+ ,0
+ ,11367.14
+ ,4.99
+ ,0.035457
+ ,675.39
+ ,68.61
+ ,1
+ ,0
+ ,11168.31
+ ,5.11
+ ,0.041667
+ ,596.15
+ ,68.29
+ ,1
+ ,0
+ ,11150.22
+ ,5.11
+ ,0.043188
+ ,633.71
+ ,72.51
+ ,1
+ ,0
+ ,11185.68
+ ,5.09
+ ,0.041453
+ ,632.33
+ ,71.81
+ ,1
+ ,0
+ ,11381.15
+ ,4.88
+ ,0.038187
+ ,598.06
+ ,61.97
+ ,1
+ ,0
+ ,11679.07
+ ,4.72
+ ,0.020624
+ ,585.78
+ ,57.95
+ ,1
+ ,0
+ ,12080.73
+ ,4.73
+ ,0.013052
+ ,627.83
+ ,58.13
+ ,1
+ ,0
+ ,12221.93
+ ,4.6
+ ,0.019737
+ ,629.42
+ ,61
+ ,1
+ ,0
+ ,12463.15
+ ,4.56
+ ,0.025407
+ ,631.17
+ ,53.4
+ ,1
+ ,0
+ ,12621.69
+ ,4.76
+ ,0.020756
+ ,664.75
+ ,57.58
+ ,1
+ ,0
+ ,12268.63
+ ,4.72
+ ,0.024152
+ ,654.90
+ ,60.6
+ ,1
+ ,0
+ ,12354.35
+ ,4.56
+ ,0.027788
+ ,679.37
+ ,65.1
+ ,1
+ ,0
+ ,13062.92
+ ,4.69
+ ,0.025737
+ ,666.92
+ ,65.1
+ ,1
+ ,0
+ ,13627.64
+ ,4.75
+ ,0.026909
+ ,655.49
+ ,68.19
+ ,1
+ ,0
+ ,13408.62
+ ,5.1
+ ,0.02687
+ ,665.30
+ ,73.67
+ ,1
+ ,0
+ ,13211.99
+ ,5
+ ,0.023582
+ ,665.41
+ ,70.13
+ ,1
+ ,1
+ ,13357.74
+ ,4.67
+ ,0.019701
+ ,712.65
+ ,76.91
+ ,1
+ ,1
+ ,13895.63
+ ,4.52
+ ,0.027551
+ ,754.60
+ ,82.15
+ ,1
+ ,1
+ ,13930.01
+ ,4.53
+ ,0.035362
+ ,806.25
+ ,91.27
+ ,1
+ ,1
+ ,13371.72
+ ,4.15
+ ,0.043062
+ ,803.20
+ ,89.43
+ ,1
+ ,1
+ ,13264.82
+ ,4.1
+ ,0.040813
+ ,889.60
+ ,90.82
+ ,1
+ ,1
+ ,12650.36
+ ,3.74
+ ,0.042803
+ ,922.30
+ ,93.75
+ ,1
+ ,1
+ ,12266.39
+ ,3.74
+ ,0.040266
+ ,968.43
+ ,101.84
+ ,1
+ ,1
+ ,12262.89
+ ,3.51
+ ,0.039815
+ ,909.70
+ ,109.05
+ ,1
+ ,1
+ ,12820.13
+ ,3.68
+ ,0.039369
+ ,890.51
+ ,122.77
+ ,1
+ ,1
+ ,12638.32
+ ,3.88
+ ,0.041755
+ ,889.49
+ ,131.52
+ ,1
+ ,1
+ ,11350.01
+ ,4.1
+ ,0.050218
+ ,939.77
+ ,132.55
+ ,1
+ ,1
+ ,11378.02
+ ,4.01
+ ,0.056001
+ ,838.31
+ ,114.57
+ ,1
+ ,1
+ ,11543.55
+ ,3.89
+ ,0.053719
+ ,829.93
+ ,99.29
+ ,1
+ ,1
+ ,10850.66
+ ,3.69
+ ,0.049369
+ ,806.62
+ ,72.69
+ ,1
+ ,1
+ ,9325.01
+ ,3.81
+ ,0.036552
+ ,760.86
+ ,54.04
+ ,1
+ ,1
+ ,8829.04
+ ,3.53
+ ,0.010696
+ ,822.00
+ ,41.53
+ ,1
+ ,1
+ ,8776.39
+ ,2.42
+ ,0.000914
+ ,859.19
+ ,43.91
+ ,1
+ ,1
+ ,8000.86
+ ,2.52
+ ,0.000298
+ ,943.16
+ ,41.76
+ ,1
+ ,1
+ ,7062.93
+ ,2.87
+ ,0.002362
+ ,924.27
+ ,46.95
+ ,1
+ ,1
+ ,7608.92
+ ,2.82
+ ,-0.003836
+ ,889.50
+ ,50.28
+ ,1
+ ,1
+ ,8168.12
+ ,2.93
+ ,-0.007369
+ ,930.20
+ ,58.1
+ ,1
+ ,1
+ ,8500.33
+ ,3.29
+ ,-0.012814
+ ,945.67
+ ,69.13
+ ,1
+ ,1
+ ,8447
+ ,3.72
+ ,-0.014268
+ ,934.23
+ ,64.65
+ ,1
+ ,1
+ ,9171.61
+ ,3.56
+ ,-0.020972
+ ,949.67
+ ,71.63
+ ,1
+ ,1
+ ,9496.28
+ ,3.59
+ ,-0.014843
+ ,996.59
+ ,68.38
+ ,1
+ ,1
+ ,9712.28
+ ,3.4
+ ,-0.012862
+ ,1043.16
+ ,74.08
+ ,1
+ ,1
+ ,9712.73
+ ,3.39
+ ,-0.001828
+ ,1127.04
+ ,77.56
+ ,1
+ ,1
+ ,10344.84
+ ,3.4
+ ,0.018383
+ ,1126.22
+ ,74.88
+ ,1
+ ,1
+ ,10428.05
+ ,3.59
+ ,0.027213
+ ,1116.51
+ ,77.09
+ ,1
+ ,1
+ ,10067.33
+ ,3.73
+ ,0.026257
+ ,1095.41
+ ,74.7
+ ,1
+ ,1
+ ,10325.26
+ ,3.69
+ ,0.021433
+ ,1113.34
+ ,79.3
+ ,1
+ ,1
+ ,10856.63
+ ,3.73
+ ,0.02314
+ ,1148.69
+ ,84.19
+ ,1
+ ,1
+ ,11008.61
+ ,3.85
+ ,0.022364
+ ,1205.43
+ ,75.56
+ ,1
+ ,1
+ ,10136.63
+ ,3.42
+ ,0.02021
+ ,1232.92
+ ,74.73
+ ,1
+ ,1
+ ,9774.02
+ ,3.2
+ ,0.010533
+ ,1192.97
+ ,74.49
+ ,1
+ ,1
+ ,10465.94
+ ,3.01
+ ,0.012352
+ ,1215.81
+ ,75.93
+ ,1
+ ,1
+ ,10014.72
+ ,2.7
+ ,0.011481
+ ,1270.98
+ ,76.14
+ ,1
+ ,1
+ ,10788.05
+ ,2.65
+ ,0.011437
+ ,1342.02
+ ,81.72
+ ,1
+ ,1
+ ,11118.4
+ ,2.54
+ ,0.011722)
+ ,dim=c(7
+ ,299)
+ ,dimnames=list(c('Gold'
+ ,'Oil'
+ ,'ETF'
+ ,'Crisis'
+ ,'Dow'
+ ,'Bonds'
+ ,'Inflation')
+ ,1:299))
> y <- array(NA,dim=c(7,299),dimnames=list(c('Gold','Oil','ETF','Crisis','Dow','Bonds','Inflation'),1:299))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Gold Oil ETF Crisis Dow Bonds Inflation
1 321.61 26.75 0 0 1546.66 9.26 0.037987
2 345.85 22.33 0 0 1570.98 9.19 0.038863
3 338.60 16.38 0 0 1709.05 8.70 0.031132
4 345.64 12.77 0 0 1818.60 7.78 0.022556
5 340.71 11.89 0 0 1783.97 7.30 0.015903
6 342.49 13.49 0 0 1876.70 7.71 0.014911
7 342.65 11.95 0 0 1892.71 7.80 0.017658
8 348.68 9.88 0 0 1775.30 7.30 0.015770
9 377.36 13.42 0 0 1898.33 7.17 0.015741
10 418.05 14.03 0 0 1767.57 7.45 0.017544
11 423.13 14.01 0 0 1877.80 7.43 0.014719
12 397.69 14.47 0 0 1914.22 7.25 0.012844
13 390.80 15.44 0 0 1895.94 7.11 0.010979
14 408.29 18.10 0 0 2158.03 7.08 0.014599
15 401.02 17.28 0 0 2223.98 7.25 0.021043
16 409.24 17.74 0 0 2304.68 7.25 0.030331
17 439.28 18.05 0 0 2286.35 8.02 0.037753
18 459.95 18.41 0 0 2291.56 8.61 0.038567
19 449.66 18.71 0 0 2418.52 8.40 0.036530
20 451.14 19.62 0 0 2572.06 8.45 0.039269
21 460.66 18.88 0 0 2662.94 8.76 0.042844
22 460.23 18.32 0 0 2596.27 9.42 0.043557
23 465.69 18.63 0 0 1993.52 9.52 0.045331
24 468.01 17.87 0 0 1833.54 8.86 0.045290
25 486.74 16.77 0 0 1938.82 8.99 0.044344
26 475.89 16.50 0 0 1958.21 8.67 0.040468
27 441.52 15.90 0 0 2071.61 8.21 0.039427
28 443.63 14.86 0 0 1988.05 8.37 0.039251
29 451.62 16.42 0 0 2032.32 8.72 0.039042
30 451.14 16.36 0 0 2031.11 9.09 0.038904
31 450.88 15.49 0 0 2141.70 8.92 0.039648
32 437.56 14.47 0 0 2128.72 9.06 0.041301
33 431.18 14.57 0 0 2031.64 9.26 0.040210
34 412.02 13.22 0 0 2112.90 8.98 0.041739
35 407.14 12.23 0 0 2148.64 8.80 0.042498
36 420.48 12.53 0 0 2114.50 8.96 0.042461
37 418.92 14.68 0 0 2168.56 9.11 0.044194
38 403.57 16.45 0 0 2342.31 9.09 0.046672
39 387.55 16.52 0 0 2258.38 9.17 0.048276
40 390.02 18.10 0 0 2293.61 9.36 0.049785
41 384.37 19.39 0 0 2418.79 9.18 0.051238
42 370.62 18.22 0 0 2480.14 8.86 0.053617
43 367.90 17.80 0 0 2440.05 8.28 0.051695
44 374.91 17.67 0 0 2660.65 8.02 0.049789
45 365.15 16.87 0 0 2737.26 8.11 0.047059
46 361.91 17.69 0 0 2692.81 8.19 0.043406
47 367.03 18.41 0 0 2645.07 8.01 0.044925
48 395.19 18.38 0 0 2706.26 7.87 0.046550
49 409.25 19.37 0 0 2753.19 7.84 0.046473
50 410.49 20.59 0 0 2590.53 8.21 0.052023
51 416.58 19.68 0 0 2627.24 8.47 0.052632
52 392.21 18.12 0 0 2707.20 8.59 0.052330
53 374.29 16.32 0 0 2656.75 8.79 0.047116
54 369.05 16.21 0 0 2876.65 8.76 0.043619
55 352.19 14.93 0 0 2880.68 8.48 0.046737
56 362.85 16.81 0 0 2905.19 8.47 0.048232
57 395.47 26.54 0 0 2614.35 8.75 0.056180
58 388.82 33.62 0 0 2452.47 8.89 0.061600
59 380.39 34.85 0 0 2442.32 8.72 0.062898
60 381.73 31.54 0 0 2559.64 8.39 0.062748
61 377.69 26.61 0 0 2633.65 8.08 0.061063
62 383.04 22.81 0 0 2736.38 8.09 0.056515
63 363.89 18.53 0 0 2882.17 7.85 0.053125
64 363.23 18.21 0 0 2913.85 8.11 0.048951
65 358.37 18.49 0 0 2887.86 8.04 0.048875
66 356.97 18.72 0 0 3027.49 8.07 0.049536
67 366.87 17.78 0 0 2906.74 8.28 0.046959
68 367.57 19.02 0 0 3024.81 8.27 0.044479
69 355.88 19.30 0 0 3043.59 7.90 0.037994
70 348.88 19.95 0 0 3016.76 7.65 0.033911
71 358.77 21.56 0 0 3069.90 7.53 0.029213
72 360.42 20.41 0 0 2894.67 7.42 0.029895
73 361.08 17.63 0 0 3168.82 7.09 0.030643
74 354.57 17.52 0 0 3223.38 7.03 0.026003
75 353.73 17.65 0 0 3267.66 7.34 0.028190
76 344.20 17.35 0 0 3235.46 7.54 0.031852
77 338.34 18.65 0 0 3359.11 7.48 0.031805
78 337.21 19.52 0 0 3396.87 7.39 0.030236
79 340.96 20.88 0 0 3318.51 7.26 0.030882
80 353.29 20.18 0 0 3393.77 6.84 0.031571
81 342.67 19.62 0 0 3257.34 6.59 0.031479
82 345.71 20.19 0 0 3271.65 6.42 0.029883
83 344.17 20.04 0 0 3226.27 6.59 0.032023
84 334.92 18.90 0 0 3305.15 6.87 0.030479
85 334.81 17.93 0 0 3301.10 6.77 0.029007
86 329.05 17.24 0 0 3310.02 6.60 0.032585
87 329.31 18.23 0 0 3370.80 6.26 0.032468
88 330.25 18.50 0 0 3435.10 5.98 0.030869
89 341.89 18.44 0 0 3427.54 5.97 0.032258
90 367.74 18.17 0 0 3527.42 6.04 0.032212
91 371.93 17.37 0 0 3516.07 5.96 0.029957
92 392.79 16.37 0 0 3539.46 5.81 0.027758
93 377.97 16.43 0 0 3651.24 5.68 0.027679
94 354.93 15.80 0 0 3555.11 5.36 0.026893
95 364.40 16.44 0 0 3680.58 5.33 0.027504
96 374.05 15.09 0 0 3683.94 5.72 0.026761
97 383.63 13.36 0 0 3754.08 5.77 0.027484
98 386.56 14.17 0 0 3978.35 5.75 0.025245
99 381.90 13.75 0 0 3832.01 5.97 0.025157
100 384.08 13.69 0 0 3635.95 6.48 0.025070
101 377.29 15.15 0 0 3681.68 6.97 0.023611
102 381.54 16.43 0 0 3758.36 7.18 0.022885
103 385.60 17.23 0 0 3624.95 7.10 0.024931
104 385.47 18.04 0 0 3764.49 7.30 0.027701
105 380.40 16.98 0 0 3913.41 7.24 0.029006
106 391.74 16.13 0 0 3843.18 7.46 0.029635
107 389.57 16.48 0 0 3908.11 7.74 0.026081
108 384.29 17.20 0 0 3739.22 7.96 0.026749
109 379.26 16.13 0 0 3834.43 7.81 0.026749
110 378.44 16.88 0 0 3843.85 7.78 0.028044
111 376.63 17.44 0 0 4011.04 7.47 0.028630
112 382.48 17.35 0 0 4157.68 7.20 0.028533
113 390.89 18.77 0 0 4321.26 7.06 0.030529
114 385.04 18.43 0 0 4465.13 6.63 0.031864
115 387.58 17.33 0 0 4556.90 6.17 0.030405
116 386.19 16.06 0 0 4708.46 6.28 0.027628
117 383.78 16.49 0 0 4610.55 6.49 0.026174
118 383.10 16.77 0 0 4789.07 6.20 0.025435
119 383.25 16.18 0 0 4755.47 6.04 0.028094
120 385.19 16.82 0 0 5074.48 5.93 0.026052
121 387.35 17.93 0 0 5117.11 5.71 0.025384
122 400.49 17.79 0 0 5395.29 5.65 0.027279
123 404.53 17.69 0 0 5485.61 5.81 0.026508
124 396.15 19.46 0 0 5587.13 6.27 0.028402
125 392.79 20.78 0 0 5569.07 6.51 0.028966
126 391.96 19.12 0 0 5643.17 6.74 0.028909
127 385.04 18.56 0 0 5654.62 6.91 0.027541
128 383.58 19.56 0 0 5528.90 6.87 0.029508
129 387.46 20.19 0 0 5616.20 6.64 0.028777
130 382.90 22.14 0 0 5882.16 6.83 0.030026
131 381.04 23.43 0 0 6029.37 6.53 0.029928
132 377.69 22.25 0 0 6521.69 6.20 0.032552
133 368.95 23.51 0 0 6448.26 6.30 0.033225
134 353.87 23.29 0 0 6813.08 6.58 0.030440
135 347.03 20.54 0 0 6877.73 6.42 0.030342
136 351.49 19.42 0 0 6583.47 6.69 0.027617
137 344.23 17.98 0 0 7008.98 6.89 0.024952
138 344.09 19.47 0 0 7331.03 6.71 0.022350
139 340.51 18.02 0 0 7672.78 6.49 0.022974
140 323.90 18.45 0 0 8222.60 6.22 0.022293
141 324.02 18.79 0 0 7622.41 6.30 0.022250
142 323.11 18.73 0 0 7945.25 6.21 0.021546
143 324.36 20.12 0 0 7442.07 6.03 0.020846
144 305.55 19.16 0 0 7823.12 5.88 0.018285
145 288.59 17.24 0 0 7908.24 5.81 0.017024
146 289.15 15.07 0 0 7906.49 5.54 0.015713
147 297.49 14.18 0 0 8545.71 5.57 0.014411
148 295.94 13.24 0 0 8799.80 5.65 0.013750
149 308.29 13.39 0 0 9063.36 5.64 0.014357
150 299.10 13.97 0 0 8899.94 5.65 0.016864
151 292.32 12.48 0 0 8952.01 5.50 0.016843
152 292.87 12.72 0 0 8883.28 5.46 0.016822
153 284.11 12.49 0 0 7539.06 5.34 0.016169
154 288.98 13.80 0 0 7842.61 4.81 0.014888
155 295.93 13.26 0 0 8592.90 4.53 0.014851
156 294.17 11.88 0 0 9116.54 4.83 0.015480
157 291.68 10.41 0 0 9181.42 4.65 0.016119
158 287.07 11.32 0 0 9358.82 4.72 0.016708
159 287.33 10.75 0 0 9306.57 5.00 0.016059
160 285.96 12.86 0 0 9786.15 5.23 0.017263
161 282.62 15.73 0 0 10789.03 5.18 0.022769
162 276.44 16.12 0 0 10559.73 5.54 0.020885
163 261.31 16.24 0 0 10970.79 5.90 0.019632
164 256.08 18.75 0 0 10655.14 5.79 0.021446
165 256.69 20.21 0 0 10829.27 5.94 0.022644
166 264.74 22.37 0 0 10336.94 5.92 0.026284
167 310.72 22.19 0 0 10729.85 6.11 0.025610
168 293.18 24.22 0 0 10877.80 6.03 0.026220
169 283.07 25.01 0 0 11497.11 6.28 0.026846
170 284.32 25.21 0 0 10940.52 6.66 0.027389
171 299.86 27.15 0 0 10128.30 6.52 0.032219
172 286.39 27.49 0 0 10921.91 6.26 0.037576
173 279.69 23.45 0 0 10733.90 5.99 0.030686
174 275.19 27.23 0 0 10522.32 6.44 0.031889
175 285.73 29.62 0 0 10447.88 6.10 0.037304
176 281.59 28.16 0 0 10521.97 6.05 0.036593
177 274.47 29.41 0 0 11215.90 5.83 0.034111
178 273.68 32.08 0 0 10650.91 5.80 0.034544
179 270.00 31.40 0 0 10971.13 5.74 0.034483
180 266.01 32.33 0 0 10414.48 5.72 0.034462
181 271.45 25.28 0 0 10786.84 5.24 0.033868
182 265.49 25.95 0 0 10887.35 5.16 0.037322
183 261.87 27.24 0 0 10495.27 5.10 0.035336
184 263.03 25.02 0 0 9878.77 4.89 0.029206
185 260.48 25.66 0 0 10734.96 5.14 0.032691
186 272.36 27.55 0 0 10911.93 5.39 0.036152
187 269.82 26.97 0 0 10502.39 5.28 0.032483
188 267.53 24.80 0 0 10522.80 5.24 0.027199
189 272.39 25.81 0 0 9949.74 4.97 0.027199
190 283.42 25.03 0 0 8847.55 4.73 0.026482
191 283.06 20.73 0 0 9075.13 4.57 0.021264
192 276.16 18.69 0 0 9851.55 4.65 0.018955
193 275.85 18.52 0 0 10021.49 5.09 0.015517
194 281.51 19.15 0 0 9920.01 5.04 0.011422
195 295.50 19.98 0 0 10106.12 4.91 0.011377
196 294.06 23.64 0 0 10403.94 5.28 0.014756
197 302.68 25.43 0 0 9946.22 5.21 0.016393
198 314.58 25.69 0 0 9925.25 5.16 0.011818
199 321.18 24.49 0 0 9243.26 4.93 0.010674
200 313.29 25.75 0 0 8736.59 4.65 0.014648
201 310.25 26.78 0 0 8663.50 4.26 0.018028
202 319.14 28.28 0 0 7591.93 3.87 0.015143
203 316.56 27.53 0 0 8397.03 3.94 0.020259
204 319.07 24.79 0 0 8896.09 4.05 0.021984
205 331.92 27.89 0 0 8341.63 4.03 0.023769
206 356.86 30.77 0 0 8053.81 4.05 0.025974
207 358.97 32.88 0 0 7891.08 3.90 0.029809
208 340.55 30.36 1 0 7992.13 3.81 0.030201
209 328.18 25.49 1 0 8480.09 3.96 0.022247
210 355.68 26.06 1 0 8850.26 3.57 0.020578
211 356.35 27.91 1 0 8985.44 3.33 0.021123
212 350.99 28.59 1 0 9233.80 3.98 0.021099
213 359.77 29.68 1 0 9415.82 4.45 0.021583
214 378.95 26.88 1 0 9275.06 4.27 0.023204
215 378.92 29.01 1 0 9801.12 4.29 0.020408
216 389.91 29.12 1 0 9782.46 4.30 0.017650
217 406.11 29.95 1 0 10453.92 4.27 0.018795
218 413.79 31.40 1 0 10488.07 4.15 0.019263
219 404.95 31.32 1 0 10583.92 4.08 0.016931
220 406.67 33.67 1 0 10357.70 3.83 0.017372
221 403.26 33.71 1 0 10225.57 4.35 0.022851
222 383.78 37.63 1 0 10188.45 4.72 0.030518
223 392.48 35.54 1 0 10435.48 4.73 0.032662
224 398.09 37.93 1 0 10139.71 4.50 0.029908
225 400.51 42.08 1 0 10173.92 4.28 0.026544
226 405.28 41.65 1 0 10080.27 4.13 0.025378
227 420.46 46.87 1 0 10027.47 4.10 0.031892
228 439.38 42.23 1 0 10428.02 4.19 0.035230
229 442.08 39.09 1 0 10783.01 4.23 0.032556
230 424.03 42.89 1 0 10489.94 4.22 0.029698
231 423.35 44.56 1 0 10766.23 4.17 0.030075
232 434.32 50.93 1 0 10503.76 4.50 0.031483
233 429.23 50.64 1 0 10192.51 4.34 0.035106
234 421.87 47.81 1 0 10467.48 4.14 0.028027
235 430.66 53.89 1 0 10274.97 4.00 0.025303
236 424.48 56.37 1 0 10640.91 4.18 0.031679
237 437.93 61.87 1 0 10481.60 4.26 0.036412
238 456.05 61.65 1 0 10568.70 4.20 0.046867
239 469.90 58.19 1 0 10440.07 4.46 0.043478
240 476.67 54.98 1 0 10805.87 4.54 0.034555
241 510.10 56.47 1 0 10717.50 4.47 0.034157
242 549.86 62.36 1 0 10864.86 4.42 0.039853
243 555.00 59.71 1 0 10993.41 4.57 0.035975
244 557.09 60.93 1 0 11109.32 4.72 0.033626
245 610.65 68.00 1 0 11367.14 4.99 0.035457
246 675.39 68.61 1 0 11168.31 5.11 0.041667
247 596.15 68.29 1 0 11150.22 5.11 0.043188
248 633.71 72.51 1 0 11185.68 5.09 0.041453
249 632.33 71.81 1 0 11381.15 4.88 0.038187
250 598.06 61.97 1 0 11679.07 4.72 0.020624
251 585.78 57.95 1 0 12080.73 4.73 0.013052
252 627.83 58.13 1 0 12221.93 4.60 0.019737
253 629.42 61.00 1 0 12463.15 4.56 0.025407
254 631.17 53.40 1 0 12621.69 4.76 0.020756
255 664.75 57.58 1 0 12268.63 4.72 0.024152
256 654.90 60.60 1 0 12354.35 4.56 0.027788
257 679.37 65.10 1 0 13062.92 4.69 0.025737
258 666.92 65.10 1 0 13627.64 4.75 0.026909
259 655.49 68.19 1 0 13408.62 5.10 0.026870
260 665.30 73.67 1 0 13211.99 5.00 0.023582
261 665.41 70.13 1 1 13357.74 4.67 0.019701
262 712.65 76.91 1 1 13895.63 4.52 0.027551
263 754.60 82.15 1 1 13930.01 4.53 0.035362
264 806.25 91.27 1 1 13371.72 4.15 0.043062
265 803.20 89.43 1 1 13264.82 4.10 0.040813
266 889.60 90.82 1 1 12650.36 3.74 0.042803
267 922.30 93.75 1 1 12266.39 3.74 0.040266
268 968.43 101.84 1 1 12262.89 3.51 0.039815
269 909.70 109.05 1 1 12820.13 3.68 0.039369
270 890.51 122.77 1 1 12638.32 3.88 0.041755
271 889.49 131.52 1 1 11350.01 4.10 0.050218
272 939.77 132.55 1 1 11378.02 4.01 0.056001
273 838.31 114.57 1 1 11543.55 3.89 0.053719
274 829.93 99.29 1 1 10850.66 3.69 0.049369
275 806.62 72.69 1 1 9325.01 3.81 0.036552
276 760.86 54.04 1 1 8829.04 3.53 0.010696
277 822.00 41.53 1 1 8776.39 2.42 0.000914
278 859.19 43.91 1 1 8000.86 2.52 0.000298
279 943.16 41.76 1 1 7062.93 2.87 0.002362
280 924.27 46.95 1 1 7608.92 2.82 -0.003836
281 889.50 50.28 1 1 8168.12 2.93 -0.007369
282 930.20 58.10 1 1 8500.33 3.29 -0.012814
283 945.67 69.13 1 1 8447.00 3.72 -0.014268
284 934.23 64.65 1 1 9171.61 3.56 -0.020972
285 949.67 71.63 1 1 9496.28 3.59 -0.014843
286 996.59 68.38 1 1 9712.28 3.40 -0.012862
287 1043.16 74.08 1 1 9712.73 3.39 -0.001828
288 1127.04 77.56 1 1 10344.84 3.40 0.018383
289 1126.22 74.88 1 1 10428.05 3.59 0.027213
290 1116.51 77.09 1 1 10067.33 3.73 0.026257
291 1095.41 74.70 1 1 10325.26 3.69 0.021433
292 1113.34 79.30 1 1 10856.63 3.73 0.023140
293 1148.69 84.19 1 1 11008.61 3.85 0.022364
294 1205.43 75.56 1 1 10136.63 3.42 0.020210
295 1232.92 74.73 1 1 9774.02 3.20 0.010533
296 1192.97 74.49 1 1 10465.94 3.01 0.012352
297 1215.81 75.93 1 1 10014.72 2.70 0.011481
298 1270.98 76.14 1 1 10788.05 2.65 0.011437
299 1342.02 81.72 1 1 11118.40 2.54 0.011722
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Oil ETF Crisis Dow Bonds
314.1253 4.4558 117.5390 335.6773 -0.0149 18.2334
Inflation
-2932.8413
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-242.771 -33.473 -4.009 28.931 364.269
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.141e+02 4.501e+01 6.979 2.00e-11 ***
Oil 4.456e+00 5.409e-01 8.238 5.95e-15 ***
ETF 1.175e+02 1.890e+01 6.218 1.74e-09 ***
Crisis 3.357e+02 2.517e+01 13.334 < 2e-16 ***
Dow -1.490e-02 2.441e-03 -6.104 3.28e-09 ***
Bonds 1.823e+01 6.086e+00 2.996 0.00297 **
Inflation -2.933e+03 5.100e+02 -5.750 2.24e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 73.52 on 292 degrees of freedom
Multiple R-squared: 0.8935, Adjusted R-squared: 0.8913
F-statistic: 408.3 on 6 and 292 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 1.436119e-01 2.872238e-01 0.8563881
[2,] 1.331767e-01 2.663535e-01 0.8668233
[3,] 6.219235e-02 1.243847e-01 0.9378076
[4,] 2.858247e-02 5.716495e-02 0.9714175
[5,] 1.252329e-02 2.504658e-02 0.9874767
[6,] 4.882970e-03 9.765940e-03 0.9951170
[7,] 1.803887e-03 3.607774e-03 0.9981961
[8,] 2.013049e-03 4.026099e-03 0.9979870
[9,] 2.320791e-03 4.641582e-03 0.9976792
[10,] 9.586077e-04 1.917215e-03 0.9990414
[11,] 4.126617e-04 8.253234e-04 0.9995873
[12,] 1.647178e-04 3.294357e-04 0.9998353
[13,] 6.304722e-05 1.260944e-04 0.9999370
[14,] 2.768351e-04 5.536701e-04 0.9997232
[15,] 5.575363e-04 1.115073e-03 0.9994425
[16,] 7.334819e-04 1.466964e-03 0.9992665
[17,] 5.927030e-04 1.185406e-03 0.9994073
[18,] 2.999110e-04 5.998220e-04 0.9997001
[19,] 1.436596e-04 2.873192e-04 0.9998563
[20,] 7.405349e-05 1.481070e-04 0.9999259
[21,] 4.102067e-05 8.204135e-05 0.9999590
[22,] 1.889092e-05 3.778185e-05 0.9999811
[23,] 9.091041e-06 1.818208e-05 0.9999909
[24,] 3.992201e-06 7.984402e-06 0.9999960
[25,] 3.334015e-06 6.668029e-06 0.9999967
[26,] 3.778262e-06 7.556525e-06 0.9999962
[27,] 2.148828e-06 4.297657e-06 0.9999979
[28,] 1.260495e-06 2.520989e-06 0.9999987
[29,] 1.751151e-06 3.502303e-06 0.9999982
[30,] 3.258433e-06 6.516866e-06 0.9999967
[31,] 4.450049e-06 8.900098e-06 0.9999955
[32,] 9.177990e-06 1.835598e-05 0.9999908
[33,] 3.167968e-05 6.335937e-05 0.9999683
[34,] 4.931680e-05 9.863360e-05 0.9999507
[35,] 5.010459e-05 1.002092e-04 0.9999499
[36,] 5.625187e-05 1.125037e-04 0.9999437
[37,] 5.726057e-05 1.145211e-04 0.9999427
[38,] 4.166163e-05 8.332326e-05 0.9999583
[39,] 2.381478e-05 4.762956e-05 0.9999762
[40,] 1.379831e-05 2.759662e-05 0.9999862
[41,] 8.055587e-06 1.611117e-05 0.9999919
[42,] 4.682534e-06 9.365068e-06 0.9999953
[43,] 3.012515e-06 6.025029e-06 0.9999970
[44,] 2.771845e-06 5.543690e-06 0.9999972
[45,] 2.791154e-06 5.582309e-06 0.9999972
[46,] 2.965504e-06 5.931007e-06 0.9999970
[47,] 2.282536e-06 4.565071e-06 0.9999977
[48,] 1.280496e-06 2.560992e-06 0.9999987
[49,] 7.040896e-07 1.408179e-06 0.9999993
[50,] 3.819407e-07 7.638814e-07 0.9999996
[51,] 2.036807e-07 4.073613e-07 0.9999998
[52,] 1.112161e-07 2.224322e-07 0.9999999
[53,] 6.131518e-08 1.226304e-07 0.9999999
[54,] 3.742917e-08 7.485834e-08 1.0000000
[55,] 2.355887e-08 4.711775e-08 1.0000000
[56,] 1.493380e-08 2.986760e-08 1.0000000
[57,] 9.395637e-09 1.879127e-08 1.0000000
[58,] 5.581741e-09 1.116348e-08 1.0000000
[59,] 3.090751e-09 6.181501e-09 1.0000000
[60,] 1.672811e-09 3.345622e-09 1.0000000
[61,] 8.974934e-10 1.794987e-09 1.0000000
[62,] 4.508601e-10 9.017202e-10 1.0000000
[63,] 2.221356e-10 4.442713e-10 1.0000000
[64,] 1.069329e-10 2.138657e-10 1.0000000
[65,] 5.175500e-11 1.035100e-10 1.0000000
[66,] 2.470487e-11 4.940975e-11 1.0000000
[67,] 1.260083e-11 2.520165e-11 1.0000000
[68,] 6.403517e-12 1.280703e-11 1.0000000
[69,] 3.194124e-12 6.388248e-12 1.0000000
[70,] 1.543746e-12 3.087492e-12 1.0000000
[71,] 7.519884e-13 1.503977e-12 1.0000000
[72,] 3.466436e-13 6.932872e-13 1.0000000
[73,] 1.653446e-13 3.306892e-13 1.0000000
[74,] 7.523438e-14 1.504688e-13 1.0000000
[75,] 3.562694e-14 7.125387e-14 1.0000000
[76,] 1.672517e-14 3.345035e-14 1.0000000
[77,] 7.769727e-15 1.553945e-14 1.0000000
[78,] 3.438283e-15 6.876565e-15 1.0000000
[79,] 1.535383e-15 3.070765e-15 1.0000000
[80,] 7.073642e-16 1.414728e-15 1.0000000
[81,] 4.955113e-16 9.910225e-16 1.0000000
[82,] 3.613064e-16 7.226128e-16 1.0000000
[83,] 4.876085e-16 9.752171e-16 1.0000000
[84,] 3.886152e-16 7.772304e-16 1.0000000
[85,] 1.831067e-16 3.662135e-16 1.0000000
[86,] 1.013432e-16 2.026864e-16 1.0000000
[87,] 5.916373e-17 1.183275e-16 1.0000000
[88,] 3.879153e-17 7.758306e-17 1.0000000
[89,] 3.182688e-17 6.365376e-17 1.0000000
[90,] 1.874304e-17 3.748607e-17 1.0000000
[91,] 9.698363e-18 1.939673e-17 1.0000000
[92,] 4.616787e-18 9.233573e-18 1.0000000
[93,] 2.385582e-18 4.771163e-18 1.0000000
[94,] 1.230485e-18 2.460969e-18 1.0000000
[95,] 6.078193e-19 1.215639e-18 1.0000000
[96,] 2.685241e-19 5.370482e-19 1.0000000
[97,] 1.249843e-19 2.499686e-19 1.0000000
[98,] 5.423703e-20 1.084741e-19 1.0000000
[99,] 2.206542e-20 4.413085e-20 1.0000000
[100,] 8.765305e-21 1.753061e-20 1.0000000
[101,] 3.459938e-21 6.919877e-21 1.0000000
[102,] 1.367837e-21 2.735675e-21 1.0000000
[103,] 5.761401e-22 1.152280e-21 1.0000000
[104,] 2.961948e-22 5.923897e-22 1.0000000
[105,] 1.492694e-22 2.985388e-22 1.0000000
[106,] 8.733113e-23 1.746623e-22 1.0000000
[107,] 4.378234e-23 8.756468e-23 1.0000000
[108,] 1.926278e-23 3.852557e-23 1.0000000
[109,] 8.933753e-24 1.786751e-23 1.0000000
[110,] 4.254147e-24 8.508295e-24 1.0000000
[111,] 2.150372e-24 4.300745e-24 1.0000000
[112,] 1.236510e-24 2.473019e-24 1.0000000
[113,] 1.048462e-24 2.096925e-24 1.0000000
[114,] 8.401580e-25 1.680316e-24 1.0000000
[115,] 4.409230e-25 8.818460e-25 1.0000000
[116,] 2.012733e-25 4.025467e-25 1.0000000
[117,] 8.671784e-26 1.734357e-25 1.0000000
[118,] 3.544033e-26 7.088066e-26 1.0000000
[119,] 1.470743e-26 2.941486e-26 1.0000000
[120,] 6.358041e-27 1.271608e-26 1.0000000
[121,] 2.663111e-27 5.326222e-27 1.0000000
[122,] 1.124769e-27 2.249537e-27 1.0000000
[123,] 5.564363e-28 1.112873e-27 1.0000000
[124,] 2.650815e-28 5.301631e-28 1.0000000
[125,] 1.475410e-28 2.950821e-28 1.0000000
[126,] 1.070634e-28 2.141267e-28 1.0000000
[127,] 7.576110e-29 1.515222e-28 1.0000000
[128,] 7.548046e-29 1.509609e-28 1.0000000
[129,] 5.179591e-29 1.035918e-28 1.0000000
[130,] 3.946309e-29 7.892618e-29 1.0000000
[131,] 3.358641e-29 6.717282e-29 1.0000000
[132,] 2.605768e-29 5.211537e-29 1.0000000
[133,] 1.820783e-29 3.641565e-29 1.0000000
[134,] 1.016474e-29 2.032949e-29 1.0000000
[135,] 7.504659e-30 1.500932e-29 1.0000000
[136,] 9.757481e-30 1.951496e-29 1.0000000
[137,] 1.068049e-29 2.136097e-29 1.0000000
[138,] 7.316909e-30 1.463382e-29 1.0000000
[139,] 4.810462e-30 9.620923e-30 1.0000000
[140,] 2.221368e-30 4.442736e-30 1.0000000
[141,] 1.216503e-30 2.433007e-30 1.0000000
[142,] 7.281837e-31 1.456367e-30 1.0000000
[143,] 3.991962e-31 7.983925e-31 1.0000000
[144,] 3.329989e-31 6.659978e-31 1.0000000
[145,] 1.672856e-31 3.345712e-31 1.0000000
[146,] 6.346529e-32 1.269306e-31 1.0000000
[147,] 2.449720e-32 4.899439e-32 1.0000000
[148,] 9.444537e-33 1.888907e-32 1.0000000
[149,] 3.697057e-33 7.394114e-33 1.0000000
[150,] 1.506880e-33 3.013759e-33 1.0000000
[151,] 5.896255e-34 1.179251e-33 1.0000000
[152,] 2.122456e-34 4.244912e-34 1.0000000
[153,] 8.593906e-35 1.718781e-34 1.0000000
[154,] 4.473755e-35 8.947509e-35 1.0000000
[155,] 2.581802e-35 5.163605e-35 1.0000000
[156,] 1.329138e-35 2.658276e-35 1.0000000
[157,] 6.001752e-36 1.200350e-35 1.0000000
[158,] 2.836271e-36 5.672543e-36 1.0000000
[159,] 9.974062e-37 1.994812e-36 1.0000000
[160,] 3.380416e-37 6.760831e-37 1.0000000
[161,] 1.322864e-37 2.645729e-37 1.0000000
[162,] 7.099626e-38 1.419925e-37 1.0000000
[163,] 3.799815e-38 7.599629e-38 1.0000000
[164,] 1.672192e-38 3.344384e-38 1.0000000
[165,] 9.337662e-39 1.867532e-38 1.0000000
[166,] 5.500788e-39 1.100158e-38 1.0000000
[167,] 3.587931e-39 7.175861e-39 1.0000000
[168,] 1.421622e-39 2.843245e-39 1.0000000
[169,] 5.668485e-40 1.133697e-39 1.0000000
[170,] 2.149830e-40 4.299660e-40 1.0000000
[171,] 9.003128e-41 1.800626e-40 1.0000000
[172,] 3.400696e-41 6.801392e-41 1.0000000
[173,] 1.352343e-41 2.704687e-41 1.0000000
[174,] 5.135556e-42 1.027111e-41 1.0000000
[175,] 1.874081e-42 3.748162e-42 1.0000000
[176,] 6.789168e-43 1.357834e-42 1.0000000
[177,] 3.080511e-43 6.161022e-43 1.0000000
[178,] 1.229869e-43 2.459739e-43 1.0000000
[179,] 4.372909e-44 8.745819e-44 1.0000000
[180,] 1.409172e-44 2.818344e-44 1.0000000
[181,] 4.686710e-45 9.373419e-45 1.0000000
[182,] 1.418470e-45 2.836939e-45 1.0000000
[183,] 4.187659e-46 8.375317e-46 1.0000000
[184,] 1.320156e-46 2.640312e-46 1.0000000
[185,] 3.762882e-47 7.525764e-47 1.0000000
[186,] 1.170321e-47 2.340643e-47 1.0000000
[187,] 3.869077e-48 7.738154e-48 1.0000000
[188,] 1.473577e-48 2.947154e-48 1.0000000
[189,] 6.881870e-49 1.376374e-48 1.0000000
[190,] 3.130334e-49 6.260668e-49 1.0000000
[191,] 1.054938e-49 2.109877e-49 1.0000000
[192,] 3.486382e-50 6.972764e-50 1.0000000
[193,] 1.494952e-50 2.989904e-50 1.0000000
[194,] 6.157278e-51 1.231456e-50 1.0000000
[195,] 2.513646e-51 5.027293e-51 1.0000000
[196,] 1.212876e-51 2.425751e-51 1.0000000
[197,] 1.233280e-51 2.466559e-51 1.0000000
[198,] 1.076221e-51 2.152441e-51 1.0000000
[199,] 3.150405e-52 6.300811e-52 1.0000000
[200,] 1.082203e-52 2.164406e-52 1.0000000
[201,] 7.556083e-53 1.511217e-52 1.0000000
[202,] 1.161441e-52 2.322882e-52 1.0000000
[203,] 5.798624e-53 1.159725e-52 1.0000000
[204,] 1.815514e-53 3.631029e-53 1.0000000
[205,] 7.234358e-54 1.446872e-53 1.0000000
[206,] 3.372525e-54 6.745050e-54 1.0000000
[207,] 1.952742e-54 3.905484e-54 1.0000000
[208,] 2.434983e-54 4.869966e-54 1.0000000
[209,] 3.840796e-54 7.681591e-54 1.0000000
[210,] 5.201968e-54 1.040394e-53 1.0000000
[211,] 1.444859e-53 2.889717e-53 1.0000000
[212,] 6.932034e-54 1.386407e-53 1.0000000
[213,] 1.791751e-54 3.583502e-54 1.0000000
[214,] 5.555972e-55 1.111194e-54 1.0000000
[215,] 1.694073e-55 3.388145e-55 1.0000000
[216,] 1.014299e-55 2.028597e-55 1.0000000
[217,] 9.516273e-56 1.903255e-55 1.0000000
[218,] 9.259673e-56 1.851935e-55 1.0000000
[219,] 1.057200e-55 2.114400e-55 1.0000000
[220,] 1.505411e-55 3.010821e-55 1.0000000
[221,] 1.225861e-55 2.451722e-55 1.0000000
[222,] 1.599468e-55 3.198936e-55 1.0000000
[223,] 1.046248e-55 2.092495e-55 1.0000000
[224,] 6.799398e-56 1.359880e-55 1.0000000
[225,] 2.152525e-55 4.305050e-55 1.0000000
[226,] 7.156516e-54 1.431303e-53 1.0000000
[227,] 1.372606e-52 2.745213e-52 1.0000000
[228,] 2.191116e-51 4.382231e-51 1.0000000
[229,] 1.866424e-50 3.732848e-50 1.0000000
[230,] 4.739341e-50 9.478682e-50 1.0000000
[231,] 2.140758e-49 4.281515e-49 1.0000000
[232,] 3.149306e-48 6.298613e-48 1.0000000
[233,] 1.777845e-46 3.555690e-46 1.0000000
[234,] 5.015374e-45 1.003075e-44 1.0000000
[235,] 4.701975e-44 9.403949e-44 1.0000000
[236,] 1.022833e-42 2.045667e-42 1.0000000
[237,] 3.724547e-39 7.449093e-39 1.0000000
[238,] 8.536784e-39 1.707357e-38 1.0000000
[239,] 4.586657e-38 9.173314e-38 1.0000000
[240,] 9.917154e-38 1.983431e-37 1.0000000
[241,] 1.272166e-37 2.544332e-37 1.0000000
[242,] 1.963874e-37 3.927748e-37 1.0000000
[243,] 1.579822e-36 3.159645e-36 1.0000000
[244,] 9.833838e-36 1.966768e-35 1.0000000
[245,] 1.197054e-34 2.394109e-34 1.0000000
[246,] 1.841790e-33 3.683581e-33 1.0000000
[247,] 9.422905e-33 1.884581e-32 1.0000000
[248,] 3.211749e-32 6.423497e-32 1.0000000
[249,] 7.178484e-32 1.435697e-31 1.0000000
[250,] 4.431954e-32 8.863908e-32 1.0000000
[251,] 1.508319e-32 3.016637e-32 1.0000000
[252,] 7.906643e-33 1.581329e-32 1.0000000
[253,] 7.161626e-33 1.432325e-32 1.0000000
[254,] 5.635564e-33 1.127113e-32 1.0000000
[255,] 1.193981e-32 2.387962e-32 1.0000000
[256,] 2.384643e-31 4.769287e-31 1.0000000
[257,] 1.067976e-29 2.135953e-29 1.0000000
[258,] 1.648660e-28 3.297319e-28 1.0000000
[259,] 1.606400e-27 3.212800e-27 1.0000000
[260,] 1.083663e-23 2.167326e-23 1.0000000
[261,] 3.880305e-19 7.760610e-19 1.0000000
[262,] 1.643958e-18 3.287916e-18 1.0000000
[263,] 9.102993e-19 1.820599e-18 1.0000000
[264,] 8.553885e-15 1.710777e-14 1.0000000
[265,] 6.906242e-05 1.381248e-04 0.9999309
[266,] 2.826865e-01 5.653730e-01 0.7173135
[267,] 4.727390e-01 9.454781e-01 0.5272610
[268,] 5.549813e-01 8.900373e-01 0.4450187
[269,] 8.268978e-01 3.462044e-01 0.1731022
[270,] 8.632108e-01 2.735784e-01 0.1367892
[271,] 8.244176e-01 3.511649e-01 0.1755824
[272,] 8.479483e-01 3.041034e-01 0.1520517
[273,] 8.007075e-01 3.985850e-01 0.1992925
[274,] 7.220920e-01 5.558161e-01 0.2779080
[275,] 6.595835e-01 6.808329e-01 0.3404165
[276,] 5.684790e-01 8.630420e-01 0.4315210
[277,] 4.625408e-01 9.250817e-01 0.5374592
[278,] 5.352100e-01 9.295799e-01 0.4647900
[279,] 5.703438e-01 8.593124e-01 0.4296562
[280,] 4.635688e-01 9.271376e-01 0.5364312
> postscript(file="/var/www/html/rcomp/tmp/1x1yq1291318281.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2x1yq1291318281.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/38sfa1291318281.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/48sfa1291318281.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/58sfa1291318281.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 299
Frequency = 1
1 2 3 4 5 6
-146.0954619 -97.9529833 -90.3733320 -73.9930737 -86.2780998 -100.6308578
7 8 9 10 11 12
-86.9548827 -69.8711851 -52.8464146 -16.6400642 -17.7492489 -46.9133699
13 14 15 16 17 18
-61.3149259 -40.6086056 -27.4427083 7.1701973 43.2836619 54.0568472
19 20 21 22 23 24
42.1764834 49.0106716 68.0145430 59.1435764 57.6214746 72.8581237
25 26 27 28 29 30
92.9132570 78.0221958 53.3494722 55.4150311 50.1189195 42.7371639
31 32 33 34 35 36
53.2830869 46.6099301 31.4915602 29.1472314 34.7189919 43.1877498
37 38 39 40 41 42
35.2008273 22.1849992 7.8482348 4.7642801 2.7747703 7.9640096
43 44 45 46 47 48
11.4565760 21.4832117 6.7815987 -12.9467521 -4.0092113 32.5146657
49 50 51 52 53 54
43.1838032 46.0951941 53.8323373 34.5309808 4.9412617 -6.2414714
55 56 57 58 59 60
-3.0880654 4.1271361 7.2638873 -20.0016801 -27.1570378 -3.7433173
61 62 63 64 65 66
15.9969468 26.2886548 22.8152647 7.0707650 1.6293575 2.6764681
67 68 69 70 71 72
3.5789360 -6.5782514 -31.5092053 -49.2216636 -57.3042563 -49.1349587
73 74 75 76 77 78
-23.7925215 -41.5138800 -41.5116276 -43.0912408 -51.9453692 -59.3499565
79 80 81 82 83 84
-58.5623709 -32.3132787 -38.1821728 -39.0499179 -37.4210525 -50.0498622
85 86 87 88 89 90
-48.3918838 -37.3511064 -34.7405903 -33.6299271 -17.5791649 9.5507597
91 92 93 94 95 96
11.9814081 33.9313794 22.6480761 4.5124581 15.3390819 21.7643592
97 98 99 100 101 102
41.3066787 37.7668994 28.5285965 18.5006892 -7.3268122 -13.5960341
103 104 105 106 107 108
-7.6290772 -4.8119802 1.9812748 13.8957701 -4.3950315 -17.4516882
109 110 111 112 113 114
-13.5604520 -13.2369232 -7.6802321 5.3940905 18.3206440 27.8848129
115 116 117 118 119 120
40.8017974 37.1785738 23.3004690 27.1529069 40.1469872 40.0049904
121 122 123 124 125 126
39.9063961 64.4665275 65.1192200 47.5324496 35.2998358 38.6096279
127 128 129 130 131 132
27.2436698 25.9530108 30.3762998 21.2887901 21.0566702 44.0123379
133 134 135 136 137 138
28.7144687 6.7768670 15.7834498 7.9347865 1.9680855 -4.3621038
139 140 141 142 143 144
9.4519459 2.0434231 -9.8785168 -6.1349170 -17.3463038 -30.9775027
145 146 147 148 149 150
-40.5361491 -29.2550853 -11.7912920 -8.7644494 8.8065102 1.7676635
151 152 153 154 155 156
5.0760060 4.2003557 -23.2893883 -13.8272040 11.7042697 20.2696955
157 158 159 160 161 162
30.4524534 24.8818540 19.8944354 15.6053944 31.4789789 8.0554101
163 164 165 166 167 168
-11.7237930 -25.5148515 -28.0374285 -25.9069341 21.2879735 0.1546996
169 170 171 172 173 174
-6.9707089 -20.2406072 -8.7277703 8.5631003 1.7791129 -27.3929276
175 176 177 178 179 180
-6.5306854 -4.2349391 -9.8538481 -29.1416557 -24.1056794 -40.2299829
181 182 183 184 185 186
9.1810717 13.3218801 -6.6182933 -18.9009188 -5.8837064 5.8037196
187 188 189 190 191 192
-9.0085484 -16.0931759 -19.3485047 -18.9912703 -9.1868639 -3.6598080
193 194 195 196 197 198
-18.7861858 -28.5435994 -13.2407143 -23.3880139 -23.4860349 -25.5630540
199 200 201 202 203 204
-22.9385116 -27.2312055 -18.9256268 -34.0348051 -7.5497487 17.6580811
205 206 207 208 209 210
14.0340334 27.9553703 32.2215821 -88.2125715 -97.6755727 -64.9841435
211 212 213 214 215 216
-64.5689298 -81.1806488 -81.6957519 -44.1005464 -54.3485605 -52.3978223
217 218 219 220 221 222
-25.9869979 -20.6985352 -33.3170597 -39.5868997 -38.5560375 -60.3160682
223 224 225 226 227 228
-32.5172878 -45.8466753 -67.2632882 -62.6572678 -51.8716740 1.8398212
229 230 231 232 233 234
15.2482488 -32.2999435 -34.2873543 -57.4988853 -52.3909728 -60.1592143
235 236 237 238 239 240
-86.7650549 -83.1255325 -84.1335073 -31.9786776 -19.3081345 -20.4134032
241 242 243 244 245 246
5.1699023 38.4978830 43.2524452 32.0090564 58.3548223 133.4393721
247 248 249 250 251 252
59.8165579 74.3775888 73.2792878 38.7008867 27.9276947 93.2557603
253 254 255 256 257 258
103.0100804 123.6989131 144.0827207 135.6344919 142.2247339 140.5317443
259 260 261 262 263 264
105.5741045 80.2169029 -242.7707013 -191.9692276 -150.1293007 -117.9225561
265 266 267 268 269 270
-120.0508729 -36.5988642 -30.1157153 -17.2143153 -104.1760679 -183.8573198
271 272 273 274 275 276
-222.2507033 -157.5412339 -180.9244854 -140.6543787 -107.9488985 -148.7238675
277 278 279 280 281 282
-41.0762703 -29.6756037 49.5719217 -1.5750931 -55.2188223 -66.9469303
283 284 285 286 287 288
-113.5236519 -110.9501900 -104.3460503 -30.4522374 23.2697161 160.1546173
289 290 291 292 293 294
194.9485487 164.6604246 144.6339730 154.2611653 165.6227580 249.3477438
295 296 297 298 299
250.7637916 230.9912261 243.7900186 310.3287112 364.2687418
> postscript(file="/var/www/html/rcomp/tmp/6jjwd1291318281.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 299
Frequency = 1
lag(myerror, k = 1) myerror
0 -146.0954619 NA
1 -97.9529833 -146.0954619
2 -90.3733320 -97.9529833
3 -73.9930737 -90.3733320
4 -86.2780998 -73.9930737
5 -100.6308578 -86.2780998
6 -86.9548827 -100.6308578
7 -69.8711851 -86.9548827
8 -52.8464146 -69.8711851
9 -16.6400642 -52.8464146
10 -17.7492489 -16.6400642
11 -46.9133699 -17.7492489
12 -61.3149259 -46.9133699
13 -40.6086056 -61.3149259
14 -27.4427083 -40.6086056
15 7.1701973 -27.4427083
16 43.2836619 7.1701973
17 54.0568472 43.2836619
18 42.1764834 54.0568472
19 49.0106716 42.1764834
20 68.0145430 49.0106716
21 59.1435764 68.0145430
22 57.6214746 59.1435764
23 72.8581237 57.6214746
24 92.9132570 72.8581237
25 78.0221958 92.9132570
26 53.3494722 78.0221958
27 55.4150311 53.3494722
28 50.1189195 55.4150311
29 42.7371639 50.1189195
30 53.2830869 42.7371639
31 46.6099301 53.2830869
32 31.4915602 46.6099301
33 29.1472314 31.4915602
34 34.7189919 29.1472314
35 43.1877498 34.7189919
36 35.2008273 43.1877498
37 22.1849992 35.2008273
38 7.8482348 22.1849992
39 4.7642801 7.8482348
40 2.7747703 4.7642801
41 7.9640096 2.7747703
42 11.4565760 7.9640096
43 21.4832117 11.4565760
44 6.7815987 21.4832117
45 -12.9467521 6.7815987
46 -4.0092113 -12.9467521
47 32.5146657 -4.0092113
48 43.1838032 32.5146657
49 46.0951941 43.1838032
50 53.8323373 46.0951941
51 34.5309808 53.8323373
52 4.9412617 34.5309808
53 -6.2414714 4.9412617
54 -3.0880654 -6.2414714
55 4.1271361 -3.0880654
56 7.2638873 4.1271361
57 -20.0016801 7.2638873
58 -27.1570378 -20.0016801
59 -3.7433173 -27.1570378
60 15.9969468 -3.7433173
61 26.2886548 15.9969468
62 22.8152647 26.2886548
63 7.0707650 22.8152647
64 1.6293575 7.0707650
65 2.6764681 1.6293575
66 3.5789360 2.6764681
67 -6.5782514 3.5789360
68 -31.5092053 -6.5782514
69 -49.2216636 -31.5092053
70 -57.3042563 -49.2216636
71 -49.1349587 -57.3042563
72 -23.7925215 -49.1349587
73 -41.5138800 -23.7925215
74 -41.5116276 -41.5138800
75 -43.0912408 -41.5116276
76 -51.9453692 -43.0912408
77 -59.3499565 -51.9453692
78 -58.5623709 -59.3499565
79 -32.3132787 -58.5623709
80 -38.1821728 -32.3132787
81 -39.0499179 -38.1821728
82 -37.4210525 -39.0499179
83 -50.0498622 -37.4210525
84 -48.3918838 -50.0498622
85 -37.3511064 -48.3918838
86 -34.7405903 -37.3511064
87 -33.6299271 -34.7405903
88 -17.5791649 -33.6299271
89 9.5507597 -17.5791649
90 11.9814081 9.5507597
91 33.9313794 11.9814081
92 22.6480761 33.9313794
93 4.5124581 22.6480761
94 15.3390819 4.5124581
95 21.7643592 15.3390819
96 41.3066787 21.7643592
97 37.7668994 41.3066787
98 28.5285965 37.7668994
99 18.5006892 28.5285965
100 -7.3268122 18.5006892
101 -13.5960341 -7.3268122
102 -7.6290772 -13.5960341
103 -4.8119802 -7.6290772
104 1.9812748 -4.8119802
105 13.8957701 1.9812748
106 -4.3950315 13.8957701
107 -17.4516882 -4.3950315
108 -13.5604520 -17.4516882
109 -13.2369232 -13.5604520
110 -7.6802321 -13.2369232
111 5.3940905 -7.6802321
112 18.3206440 5.3940905
113 27.8848129 18.3206440
114 40.8017974 27.8848129
115 37.1785738 40.8017974
116 23.3004690 37.1785738
117 27.1529069 23.3004690
118 40.1469872 27.1529069
119 40.0049904 40.1469872
120 39.9063961 40.0049904
121 64.4665275 39.9063961
122 65.1192200 64.4665275
123 47.5324496 65.1192200
124 35.2998358 47.5324496
125 38.6096279 35.2998358
126 27.2436698 38.6096279
127 25.9530108 27.2436698
128 30.3762998 25.9530108
129 21.2887901 30.3762998
130 21.0566702 21.2887901
131 44.0123379 21.0566702
132 28.7144687 44.0123379
133 6.7768670 28.7144687
134 15.7834498 6.7768670
135 7.9347865 15.7834498
136 1.9680855 7.9347865
137 -4.3621038 1.9680855
138 9.4519459 -4.3621038
139 2.0434231 9.4519459
140 -9.8785168 2.0434231
141 -6.1349170 -9.8785168
142 -17.3463038 -6.1349170
143 -30.9775027 -17.3463038
144 -40.5361491 -30.9775027
145 -29.2550853 -40.5361491
146 -11.7912920 -29.2550853
147 -8.7644494 -11.7912920
148 8.8065102 -8.7644494
149 1.7676635 8.8065102
150 5.0760060 1.7676635
151 4.2003557 5.0760060
152 -23.2893883 4.2003557
153 -13.8272040 -23.2893883
154 11.7042697 -13.8272040
155 20.2696955 11.7042697
156 30.4524534 20.2696955
157 24.8818540 30.4524534
158 19.8944354 24.8818540
159 15.6053944 19.8944354
160 31.4789789 15.6053944
161 8.0554101 31.4789789
162 -11.7237930 8.0554101
163 -25.5148515 -11.7237930
164 -28.0374285 -25.5148515
165 -25.9069341 -28.0374285
166 21.2879735 -25.9069341
167 0.1546996 21.2879735
168 -6.9707089 0.1546996
169 -20.2406072 -6.9707089
170 -8.7277703 -20.2406072
171 8.5631003 -8.7277703
172 1.7791129 8.5631003
173 -27.3929276 1.7791129
174 -6.5306854 -27.3929276
175 -4.2349391 -6.5306854
176 -9.8538481 -4.2349391
177 -29.1416557 -9.8538481
178 -24.1056794 -29.1416557
179 -40.2299829 -24.1056794
180 9.1810717 -40.2299829
181 13.3218801 9.1810717
182 -6.6182933 13.3218801
183 -18.9009188 -6.6182933
184 -5.8837064 -18.9009188
185 5.8037196 -5.8837064
186 -9.0085484 5.8037196
187 -16.0931759 -9.0085484
188 -19.3485047 -16.0931759
189 -18.9912703 -19.3485047
190 -9.1868639 -18.9912703
191 -3.6598080 -9.1868639
192 -18.7861858 -3.6598080
193 -28.5435994 -18.7861858
194 -13.2407143 -28.5435994
195 -23.3880139 -13.2407143
196 -23.4860349 -23.3880139
197 -25.5630540 -23.4860349
198 -22.9385116 -25.5630540
199 -27.2312055 -22.9385116
200 -18.9256268 -27.2312055
201 -34.0348051 -18.9256268
202 -7.5497487 -34.0348051
203 17.6580811 -7.5497487
204 14.0340334 17.6580811
205 27.9553703 14.0340334
206 32.2215821 27.9553703
207 -88.2125715 32.2215821
208 -97.6755727 -88.2125715
209 -64.9841435 -97.6755727
210 -64.5689298 -64.9841435
211 -81.1806488 -64.5689298
212 -81.6957519 -81.1806488
213 -44.1005464 -81.6957519
214 -54.3485605 -44.1005464
215 -52.3978223 -54.3485605
216 -25.9869979 -52.3978223
217 -20.6985352 -25.9869979
218 -33.3170597 -20.6985352
219 -39.5868997 -33.3170597
220 -38.5560375 -39.5868997
221 -60.3160682 -38.5560375
222 -32.5172878 -60.3160682
223 -45.8466753 -32.5172878
224 -67.2632882 -45.8466753
225 -62.6572678 -67.2632882
226 -51.8716740 -62.6572678
227 1.8398212 -51.8716740
228 15.2482488 1.8398212
229 -32.2999435 15.2482488
230 -34.2873543 -32.2999435
231 -57.4988853 -34.2873543
232 -52.3909728 -57.4988853
233 -60.1592143 -52.3909728
234 -86.7650549 -60.1592143
235 -83.1255325 -86.7650549
236 -84.1335073 -83.1255325
237 -31.9786776 -84.1335073
238 -19.3081345 -31.9786776
239 -20.4134032 -19.3081345
240 5.1699023 -20.4134032
241 38.4978830 5.1699023
242 43.2524452 38.4978830
243 32.0090564 43.2524452
244 58.3548223 32.0090564
245 133.4393721 58.3548223
246 59.8165579 133.4393721
247 74.3775888 59.8165579
248 73.2792878 74.3775888
249 38.7008867 73.2792878
250 27.9276947 38.7008867
251 93.2557603 27.9276947
252 103.0100804 93.2557603
253 123.6989131 103.0100804
254 144.0827207 123.6989131
255 135.6344919 144.0827207
256 142.2247339 135.6344919
257 140.5317443 142.2247339
258 105.5741045 140.5317443
259 80.2169029 105.5741045
260 -242.7707013 80.2169029
261 -191.9692276 -242.7707013
262 -150.1293007 -191.9692276
263 -117.9225561 -150.1293007
264 -120.0508729 -117.9225561
265 -36.5988642 -120.0508729
266 -30.1157153 -36.5988642
267 -17.2143153 -30.1157153
268 -104.1760679 -17.2143153
269 -183.8573198 -104.1760679
270 -222.2507033 -183.8573198
271 -157.5412339 -222.2507033
272 -180.9244854 -157.5412339
273 -140.6543787 -180.9244854
274 -107.9488985 -140.6543787
275 -148.7238675 -107.9488985
276 -41.0762703 -148.7238675
277 -29.6756037 -41.0762703
278 49.5719217 -29.6756037
279 -1.5750931 49.5719217
280 -55.2188223 -1.5750931
281 -66.9469303 -55.2188223
282 -113.5236519 -66.9469303
283 -110.9501900 -113.5236519
284 -104.3460503 -110.9501900
285 -30.4522374 -104.3460503
286 23.2697161 -30.4522374
287 160.1546173 23.2697161
288 194.9485487 160.1546173
289 164.6604246 194.9485487
290 144.6339730 164.6604246
291 154.2611653 144.6339730
292 165.6227580 154.2611653
293 249.3477438 165.6227580
294 250.7637916 249.3477438
295 230.9912261 250.7637916
296 243.7900186 230.9912261
297 310.3287112 243.7900186
298 364.2687418 310.3287112
299 NA 364.2687418
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -97.9529833 -146.0954619
[2,] -90.3733320 -97.9529833
[3,] -73.9930737 -90.3733320
[4,] -86.2780998 -73.9930737
[5,] -100.6308578 -86.2780998
[6,] -86.9548827 -100.6308578
[7,] -69.8711851 -86.9548827
[8,] -52.8464146 -69.8711851
[9,] -16.6400642 -52.8464146
[10,] -17.7492489 -16.6400642
[11,] -46.9133699 -17.7492489
[12,] -61.3149259 -46.9133699
[13,] -40.6086056 -61.3149259
[14,] -27.4427083 -40.6086056
[15,] 7.1701973 -27.4427083
[16,] 43.2836619 7.1701973
[17,] 54.0568472 43.2836619
[18,] 42.1764834 54.0568472
[19,] 49.0106716 42.1764834
[20,] 68.0145430 49.0106716
[21,] 59.1435764 68.0145430
[22,] 57.6214746 59.1435764
[23,] 72.8581237 57.6214746
[24,] 92.9132570 72.8581237
[25,] 78.0221958 92.9132570
[26,] 53.3494722 78.0221958
[27,] 55.4150311 53.3494722
[28,] 50.1189195 55.4150311
[29,] 42.7371639 50.1189195
[30,] 53.2830869 42.7371639
[31,] 46.6099301 53.2830869
[32,] 31.4915602 46.6099301
[33,] 29.1472314 31.4915602
[34,] 34.7189919 29.1472314
[35,] 43.1877498 34.7189919
[36,] 35.2008273 43.1877498
[37,] 22.1849992 35.2008273
[38,] 7.8482348 22.1849992
[39,] 4.7642801 7.8482348
[40,] 2.7747703 4.7642801
[41,] 7.9640096 2.7747703
[42,] 11.4565760 7.9640096
[43,] 21.4832117 11.4565760
[44,] 6.7815987 21.4832117
[45,] -12.9467521 6.7815987
[46,] -4.0092113 -12.9467521
[47,] 32.5146657 -4.0092113
[48,] 43.1838032 32.5146657
[49,] 46.0951941 43.1838032
[50,] 53.8323373 46.0951941
[51,] 34.5309808 53.8323373
[52,] 4.9412617 34.5309808
[53,] -6.2414714 4.9412617
[54,] -3.0880654 -6.2414714
[55,] 4.1271361 -3.0880654
[56,] 7.2638873 4.1271361
[57,] -20.0016801 7.2638873
[58,] -27.1570378 -20.0016801
[59,] -3.7433173 -27.1570378
[60,] 15.9969468 -3.7433173
[61,] 26.2886548 15.9969468
[62,] 22.8152647 26.2886548
[63,] 7.0707650 22.8152647
[64,] 1.6293575 7.0707650
[65,] 2.6764681 1.6293575
[66,] 3.5789360 2.6764681
[67,] -6.5782514 3.5789360
[68,] -31.5092053 -6.5782514
[69,] -49.2216636 -31.5092053
[70,] -57.3042563 -49.2216636
[71,] -49.1349587 -57.3042563
[72,] -23.7925215 -49.1349587
[73,] -41.5138800 -23.7925215
[74,] -41.5116276 -41.5138800
[75,] -43.0912408 -41.5116276
[76,] -51.9453692 -43.0912408
[77,] -59.3499565 -51.9453692
[78,] -58.5623709 -59.3499565
[79,] -32.3132787 -58.5623709
[80,] -38.1821728 -32.3132787
[81,] -39.0499179 -38.1821728
[82,] -37.4210525 -39.0499179
[83,] -50.0498622 -37.4210525
[84,] -48.3918838 -50.0498622
[85,] -37.3511064 -48.3918838
[86,] -34.7405903 -37.3511064
[87,] -33.6299271 -34.7405903
[88,] -17.5791649 -33.6299271
[89,] 9.5507597 -17.5791649
[90,] 11.9814081 9.5507597
[91,] 33.9313794 11.9814081
[92,] 22.6480761 33.9313794
[93,] 4.5124581 22.6480761
[94,] 15.3390819 4.5124581
[95,] 21.7643592 15.3390819
[96,] 41.3066787 21.7643592
[97,] 37.7668994 41.3066787
[98,] 28.5285965 37.7668994
[99,] 18.5006892 28.5285965
[100,] -7.3268122 18.5006892
[101,] -13.5960341 -7.3268122
[102,] -7.6290772 -13.5960341
[103,] -4.8119802 -7.6290772
[104,] 1.9812748 -4.8119802
[105,] 13.8957701 1.9812748
[106,] -4.3950315 13.8957701
[107,] -17.4516882 -4.3950315
[108,] -13.5604520 -17.4516882
[109,] -13.2369232 -13.5604520
[110,] -7.6802321 -13.2369232
[111,] 5.3940905 -7.6802321
[112,] 18.3206440 5.3940905
[113,] 27.8848129 18.3206440
[114,] 40.8017974 27.8848129
[115,] 37.1785738 40.8017974
[116,] 23.3004690 37.1785738
[117,] 27.1529069 23.3004690
[118,] 40.1469872 27.1529069
[119,] 40.0049904 40.1469872
[120,] 39.9063961 40.0049904
[121,] 64.4665275 39.9063961
[122,] 65.1192200 64.4665275
[123,] 47.5324496 65.1192200
[124,] 35.2998358 47.5324496
[125,] 38.6096279 35.2998358
[126,] 27.2436698 38.6096279
[127,] 25.9530108 27.2436698
[128,] 30.3762998 25.9530108
[129,] 21.2887901 30.3762998
[130,] 21.0566702 21.2887901
[131,] 44.0123379 21.0566702
[132,] 28.7144687 44.0123379
[133,] 6.7768670 28.7144687
[134,] 15.7834498 6.7768670
[135,] 7.9347865 15.7834498
[136,] 1.9680855 7.9347865
[137,] -4.3621038 1.9680855
[138,] 9.4519459 -4.3621038
[139,] 2.0434231 9.4519459
[140,] -9.8785168 2.0434231
[141,] -6.1349170 -9.8785168
[142,] -17.3463038 -6.1349170
[143,] -30.9775027 -17.3463038
[144,] -40.5361491 -30.9775027
[145,] -29.2550853 -40.5361491
[146,] -11.7912920 -29.2550853
[147,] -8.7644494 -11.7912920
[148,] 8.8065102 -8.7644494
[149,] 1.7676635 8.8065102
[150,] 5.0760060 1.7676635
[151,] 4.2003557 5.0760060
[152,] -23.2893883 4.2003557
[153,] -13.8272040 -23.2893883
[154,] 11.7042697 -13.8272040
[155,] 20.2696955 11.7042697
[156,] 30.4524534 20.2696955
[157,] 24.8818540 30.4524534
[158,] 19.8944354 24.8818540
[159,] 15.6053944 19.8944354
[160,] 31.4789789 15.6053944
[161,] 8.0554101 31.4789789
[162,] -11.7237930 8.0554101
[163,] -25.5148515 -11.7237930
[164,] -28.0374285 -25.5148515
[165,] -25.9069341 -28.0374285
[166,] 21.2879735 -25.9069341
[167,] 0.1546996 21.2879735
[168,] -6.9707089 0.1546996
[169,] -20.2406072 -6.9707089
[170,] -8.7277703 -20.2406072
[171,] 8.5631003 -8.7277703
[172,] 1.7791129 8.5631003
[173,] -27.3929276 1.7791129
[174,] -6.5306854 -27.3929276
[175,] -4.2349391 -6.5306854
[176,] -9.8538481 -4.2349391
[177,] -29.1416557 -9.8538481
[178,] -24.1056794 -29.1416557
[179,] -40.2299829 -24.1056794
[180,] 9.1810717 -40.2299829
[181,] 13.3218801 9.1810717
[182,] -6.6182933 13.3218801
[183,] -18.9009188 -6.6182933
[184,] -5.8837064 -18.9009188
[185,] 5.8037196 -5.8837064
[186,] -9.0085484 5.8037196
[187,] -16.0931759 -9.0085484
[188,] -19.3485047 -16.0931759
[189,] -18.9912703 -19.3485047
[190,] -9.1868639 -18.9912703
[191,] -3.6598080 -9.1868639
[192,] -18.7861858 -3.6598080
[193,] -28.5435994 -18.7861858
[194,] -13.2407143 -28.5435994
[195,] -23.3880139 -13.2407143
[196,] -23.4860349 -23.3880139
[197,] -25.5630540 -23.4860349
[198,] -22.9385116 -25.5630540
[199,] -27.2312055 -22.9385116
[200,] -18.9256268 -27.2312055
[201,] -34.0348051 -18.9256268
[202,] -7.5497487 -34.0348051
[203,] 17.6580811 -7.5497487
[204,] 14.0340334 17.6580811
[205,] 27.9553703 14.0340334
[206,] 32.2215821 27.9553703
[207,] -88.2125715 32.2215821
[208,] -97.6755727 -88.2125715
[209,] -64.9841435 -97.6755727
[210,] -64.5689298 -64.9841435
[211,] -81.1806488 -64.5689298
[212,] -81.6957519 -81.1806488
[213,] -44.1005464 -81.6957519
[214,] -54.3485605 -44.1005464
[215,] -52.3978223 -54.3485605
[216,] -25.9869979 -52.3978223
[217,] -20.6985352 -25.9869979
[218,] -33.3170597 -20.6985352
[219,] -39.5868997 -33.3170597
[220,] -38.5560375 -39.5868997
[221,] -60.3160682 -38.5560375
[222,] -32.5172878 -60.3160682
[223,] -45.8466753 -32.5172878
[224,] -67.2632882 -45.8466753
[225,] -62.6572678 -67.2632882
[226,] -51.8716740 -62.6572678
[227,] 1.8398212 -51.8716740
[228,] 15.2482488 1.8398212
[229,] -32.2999435 15.2482488
[230,] -34.2873543 -32.2999435
[231,] -57.4988853 -34.2873543
[232,] -52.3909728 -57.4988853
[233,] -60.1592143 -52.3909728
[234,] -86.7650549 -60.1592143
[235,] -83.1255325 -86.7650549
[236,] -84.1335073 -83.1255325
[237,] -31.9786776 -84.1335073
[238,] -19.3081345 -31.9786776
[239,] -20.4134032 -19.3081345
[240,] 5.1699023 -20.4134032
[241,] 38.4978830 5.1699023
[242,] 43.2524452 38.4978830
[243,] 32.0090564 43.2524452
[244,] 58.3548223 32.0090564
[245,] 133.4393721 58.3548223
[246,] 59.8165579 133.4393721
[247,] 74.3775888 59.8165579
[248,] 73.2792878 74.3775888
[249,] 38.7008867 73.2792878
[250,] 27.9276947 38.7008867
[251,] 93.2557603 27.9276947
[252,] 103.0100804 93.2557603
[253,] 123.6989131 103.0100804
[254,] 144.0827207 123.6989131
[255,] 135.6344919 144.0827207
[256,] 142.2247339 135.6344919
[257,] 140.5317443 142.2247339
[258,] 105.5741045 140.5317443
[259,] 80.2169029 105.5741045
[260,] -242.7707013 80.2169029
[261,] -191.9692276 -242.7707013
[262,] -150.1293007 -191.9692276
[263,] -117.9225561 -150.1293007
[264,] -120.0508729 -117.9225561
[265,] -36.5988642 -120.0508729
[266,] -30.1157153 -36.5988642
[267,] -17.2143153 -30.1157153
[268,] -104.1760679 -17.2143153
[269,] -183.8573198 -104.1760679
[270,] -222.2507033 -183.8573198
[271,] -157.5412339 -222.2507033
[272,] -180.9244854 -157.5412339
[273,] -140.6543787 -180.9244854
[274,] -107.9488985 -140.6543787
[275,] -148.7238675 -107.9488985
[276,] -41.0762703 -148.7238675
[277,] -29.6756037 -41.0762703
[278,] 49.5719217 -29.6756037
[279,] -1.5750931 49.5719217
[280,] -55.2188223 -1.5750931
[281,] -66.9469303 -55.2188223
[282,] -113.5236519 -66.9469303
[283,] -110.9501900 -113.5236519
[284,] -104.3460503 -110.9501900
[285,] -30.4522374 -104.3460503
[286,] 23.2697161 -30.4522374
[287,] 160.1546173 23.2697161
[288,] 194.9485487 160.1546173
[289,] 164.6604246 194.9485487
[290,] 144.6339730 164.6604246
[291,] 154.2611653 144.6339730
[292,] 165.6227580 154.2611653
[293,] 249.3477438 165.6227580
[294,] 250.7637916 249.3477438
[295,] 230.9912261 250.7637916
[296,] 243.7900186 230.9912261
[297,] 310.3287112 243.7900186
[298,] 364.2687418 310.3287112
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -97.9529833 -146.0954619
2 -90.3733320 -97.9529833
3 -73.9930737 -90.3733320
4 -86.2780998 -73.9930737
5 -100.6308578 -86.2780998
6 -86.9548827 -100.6308578
7 -69.8711851 -86.9548827
8 -52.8464146 -69.8711851
9 -16.6400642 -52.8464146
10 -17.7492489 -16.6400642
11 -46.9133699 -17.7492489
12 -61.3149259 -46.9133699
13 -40.6086056 -61.3149259
14 -27.4427083 -40.6086056
15 7.1701973 -27.4427083
16 43.2836619 7.1701973
17 54.0568472 43.2836619
18 42.1764834 54.0568472
19 49.0106716 42.1764834
20 68.0145430 49.0106716
21 59.1435764 68.0145430
22 57.6214746 59.1435764
23 72.8581237 57.6214746
24 92.9132570 72.8581237
25 78.0221958 92.9132570
26 53.3494722 78.0221958
27 55.4150311 53.3494722
28 50.1189195 55.4150311
29 42.7371639 50.1189195
30 53.2830869 42.7371639
31 46.6099301 53.2830869
32 31.4915602 46.6099301
33 29.1472314 31.4915602
34 34.7189919 29.1472314
35 43.1877498 34.7189919
36 35.2008273 43.1877498
37 22.1849992 35.2008273
38 7.8482348 22.1849992
39 4.7642801 7.8482348
40 2.7747703 4.7642801
41 7.9640096 2.7747703
42 11.4565760 7.9640096
43 21.4832117 11.4565760
44 6.7815987 21.4832117
45 -12.9467521 6.7815987
46 -4.0092113 -12.9467521
47 32.5146657 -4.0092113
48 43.1838032 32.5146657
49 46.0951941 43.1838032
50 53.8323373 46.0951941
51 34.5309808 53.8323373
52 4.9412617 34.5309808
53 -6.2414714 4.9412617
54 -3.0880654 -6.2414714
55 4.1271361 -3.0880654
56 7.2638873 4.1271361
57 -20.0016801 7.2638873
58 -27.1570378 -20.0016801
59 -3.7433173 -27.1570378
60 15.9969468 -3.7433173
61 26.2886548 15.9969468
62 22.8152647 26.2886548
63 7.0707650 22.8152647
64 1.6293575 7.0707650
65 2.6764681 1.6293575
66 3.5789360 2.6764681
67 -6.5782514 3.5789360
68 -31.5092053 -6.5782514
69 -49.2216636 -31.5092053
70 -57.3042563 -49.2216636
71 -49.1349587 -57.3042563
72 -23.7925215 -49.1349587
73 -41.5138800 -23.7925215
74 -41.5116276 -41.5138800
75 -43.0912408 -41.5116276
76 -51.9453692 -43.0912408
77 -59.3499565 -51.9453692
78 -58.5623709 -59.3499565
79 -32.3132787 -58.5623709
80 -38.1821728 -32.3132787
81 -39.0499179 -38.1821728
82 -37.4210525 -39.0499179
83 -50.0498622 -37.4210525
84 -48.3918838 -50.0498622
85 -37.3511064 -48.3918838
86 -34.7405903 -37.3511064
87 -33.6299271 -34.7405903
88 -17.5791649 -33.6299271
89 9.5507597 -17.5791649
90 11.9814081 9.5507597
91 33.9313794 11.9814081
92 22.6480761 33.9313794
93 4.5124581 22.6480761
94 15.3390819 4.5124581
95 21.7643592 15.3390819
96 41.3066787 21.7643592
97 37.7668994 41.3066787
98 28.5285965 37.7668994
99 18.5006892 28.5285965
100 -7.3268122 18.5006892
101 -13.5960341 -7.3268122
102 -7.6290772 -13.5960341
103 -4.8119802 -7.6290772
104 1.9812748 -4.8119802
105 13.8957701 1.9812748
106 -4.3950315 13.8957701
107 -17.4516882 -4.3950315
108 -13.5604520 -17.4516882
109 -13.2369232 -13.5604520
110 -7.6802321 -13.2369232
111 5.3940905 -7.6802321
112 18.3206440 5.3940905
113 27.8848129 18.3206440
114 40.8017974 27.8848129
115 37.1785738 40.8017974
116 23.3004690 37.1785738
117 27.1529069 23.3004690
118 40.1469872 27.1529069
119 40.0049904 40.1469872
120 39.9063961 40.0049904
121 64.4665275 39.9063961
122 65.1192200 64.4665275
123 47.5324496 65.1192200
124 35.2998358 47.5324496
125 38.6096279 35.2998358
126 27.2436698 38.6096279
127 25.9530108 27.2436698
128 30.3762998 25.9530108
129 21.2887901 30.3762998
130 21.0566702 21.2887901
131 44.0123379 21.0566702
132 28.7144687 44.0123379
133 6.7768670 28.7144687
134 15.7834498 6.7768670
135 7.9347865 15.7834498
136 1.9680855 7.9347865
137 -4.3621038 1.9680855
138 9.4519459 -4.3621038
139 2.0434231 9.4519459
140 -9.8785168 2.0434231
141 -6.1349170 -9.8785168
142 -17.3463038 -6.1349170
143 -30.9775027 -17.3463038
144 -40.5361491 -30.9775027
145 -29.2550853 -40.5361491
146 -11.7912920 -29.2550853
147 -8.7644494 -11.7912920
148 8.8065102 -8.7644494
149 1.7676635 8.8065102
150 5.0760060 1.7676635
151 4.2003557 5.0760060
152 -23.2893883 4.2003557
153 -13.8272040 -23.2893883
154 11.7042697 -13.8272040
155 20.2696955 11.7042697
156 30.4524534 20.2696955
157 24.8818540 30.4524534
158 19.8944354 24.8818540
159 15.6053944 19.8944354
160 31.4789789 15.6053944
161 8.0554101 31.4789789
162 -11.7237930 8.0554101
163 -25.5148515 -11.7237930
164 -28.0374285 -25.5148515
165 -25.9069341 -28.0374285
166 21.2879735 -25.9069341
167 0.1546996 21.2879735
168 -6.9707089 0.1546996
169 -20.2406072 -6.9707089
170 -8.7277703 -20.2406072
171 8.5631003 -8.7277703
172 1.7791129 8.5631003
173 -27.3929276 1.7791129
174 -6.5306854 -27.3929276
175 -4.2349391 -6.5306854
176 -9.8538481 -4.2349391
177 -29.1416557 -9.8538481
178 -24.1056794 -29.1416557
179 -40.2299829 -24.1056794
180 9.1810717 -40.2299829
181 13.3218801 9.1810717
182 -6.6182933 13.3218801
183 -18.9009188 -6.6182933
184 -5.8837064 -18.9009188
185 5.8037196 -5.8837064
186 -9.0085484 5.8037196
187 -16.0931759 -9.0085484
188 -19.3485047 -16.0931759
189 -18.9912703 -19.3485047
190 -9.1868639 -18.9912703
191 -3.6598080 -9.1868639
192 -18.7861858 -3.6598080
193 -28.5435994 -18.7861858
194 -13.2407143 -28.5435994
195 -23.3880139 -13.2407143
196 -23.4860349 -23.3880139
197 -25.5630540 -23.4860349
198 -22.9385116 -25.5630540
199 -27.2312055 -22.9385116
200 -18.9256268 -27.2312055
201 -34.0348051 -18.9256268
202 -7.5497487 -34.0348051
203 17.6580811 -7.5497487
204 14.0340334 17.6580811
205 27.9553703 14.0340334
206 32.2215821 27.9553703
207 -88.2125715 32.2215821
208 -97.6755727 -88.2125715
209 -64.9841435 -97.6755727
210 -64.5689298 -64.9841435
211 -81.1806488 -64.5689298
212 -81.6957519 -81.1806488
213 -44.1005464 -81.6957519
214 -54.3485605 -44.1005464
215 -52.3978223 -54.3485605
216 -25.9869979 -52.3978223
217 -20.6985352 -25.9869979
218 -33.3170597 -20.6985352
219 -39.5868997 -33.3170597
220 -38.5560375 -39.5868997
221 -60.3160682 -38.5560375
222 -32.5172878 -60.3160682
223 -45.8466753 -32.5172878
224 -67.2632882 -45.8466753
225 -62.6572678 -67.2632882
226 -51.8716740 -62.6572678
227 1.8398212 -51.8716740
228 15.2482488 1.8398212
229 -32.2999435 15.2482488
230 -34.2873543 -32.2999435
231 -57.4988853 -34.2873543
232 -52.3909728 -57.4988853
233 -60.1592143 -52.3909728
234 -86.7650549 -60.1592143
235 -83.1255325 -86.7650549
236 -84.1335073 -83.1255325
237 -31.9786776 -84.1335073
238 -19.3081345 -31.9786776
239 -20.4134032 -19.3081345
240 5.1699023 -20.4134032
241 38.4978830 5.1699023
242 43.2524452 38.4978830
243 32.0090564 43.2524452
244 58.3548223 32.0090564
245 133.4393721 58.3548223
246 59.8165579 133.4393721
247 74.3775888 59.8165579
248 73.2792878 74.3775888
249 38.7008867 73.2792878
250 27.9276947 38.7008867
251 93.2557603 27.9276947
252 103.0100804 93.2557603
253 123.6989131 103.0100804
254 144.0827207 123.6989131
255 135.6344919 144.0827207
256 142.2247339 135.6344919
257 140.5317443 142.2247339
258 105.5741045 140.5317443
259 80.2169029 105.5741045
260 -242.7707013 80.2169029
261 -191.9692276 -242.7707013
262 -150.1293007 -191.9692276
263 -117.9225561 -150.1293007
264 -120.0508729 -117.9225561
265 -36.5988642 -120.0508729
266 -30.1157153 -36.5988642
267 -17.2143153 -30.1157153
268 -104.1760679 -17.2143153
269 -183.8573198 -104.1760679
270 -222.2507033 -183.8573198
271 -157.5412339 -222.2507033
272 -180.9244854 -157.5412339
273 -140.6543787 -180.9244854
274 -107.9488985 -140.6543787
275 -148.7238675 -107.9488985
276 -41.0762703 -148.7238675
277 -29.6756037 -41.0762703
278 49.5719217 -29.6756037
279 -1.5750931 49.5719217
280 -55.2188223 -1.5750931
281 -66.9469303 -55.2188223
282 -113.5236519 -66.9469303
283 -110.9501900 -113.5236519
284 -104.3460503 -110.9501900
285 -30.4522374 -104.3460503
286 23.2697161 -30.4522374
287 160.1546173 23.2697161
288 194.9485487 160.1546173
289 164.6604246 194.9485487
290 144.6339730 164.6604246
291 154.2611653 144.6339730
292 165.6227580 154.2611653
293 249.3477438 165.6227580
294 250.7637916 249.3477438
295 230.9912261 250.7637916
296 243.7900186 230.9912261
297 310.3287112 243.7900186
298 364.2687418 310.3287112
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/7jjwd1291318281.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8tswy1291318281.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9tswy1291318281.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10mkd11291318281.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/117kt71291318281.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/12tlav1291318281.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13pc7m1291318281.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/14ad6s1291318281.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/15wwny1291318281.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/16zel31291318281.tab")
+ }
>
> try(system("convert tmp/1x1yq1291318281.ps tmp/1x1yq1291318281.png",intern=TRUE))
character(0)
> try(system("convert tmp/2x1yq1291318281.ps tmp/2x1yq1291318281.png",intern=TRUE))
character(0)
> try(system("convert tmp/38sfa1291318281.ps tmp/38sfa1291318281.png",intern=TRUE))
character(0)
> try(system("convert tmp/48sfa1291318281.ps tmp/48sfa1291318281.png",intern=TRUE))
character(0)
> try(system("convert tmp/58sfa1291318281.ps tmp/58sfa1291318281.png",intern=TRUE))
character(0)
> try(system("convert tmp/6jjwd1291318281.ps tmp/6jjwd1291318281.png",intern=TRUE))
character(0)
> try(system("convert tmp/7jjwd1291318281.ps tmp/7jjwd1291318281.png",intern=TRUE))
character(0)
> try(system("convert tmp/8tswy1291318281.ps tmp/8tswy1291318281.png",intern=TRUE))
character(0)
> try(system("convert tmp/9tswy1291318281.ps tmp/9tswy1291318281.png",intern=TRUE))
character(0)
> try(system("convert tmp/10mkd11291318281.ps tmp/10mkd11291318281.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
8.033 2.066 20.943