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 <- c(315.42
+ ,316.32
+ ,316.49
+ ,317.56
+ ,318.13
+ ,318.00
+ ,316.39
+ ,314.66
+ ,313.68
+ ,313.18
+ ,314.66
+ ,315.43
+ ,316.27
+ ,316.81
+ ,317.42
+ ,318.87
+ ,319.87
+ ,319.43
+ ,318.01
+ ,315.75
+ ,314.00
+ ,313.68
+ ,314.84
+ ,316.03
+ ,316.73
+ ,317.54
+ ,318.38
+ ,319.31
+ ,320.42
+ ,319.61
+ ,318.42
+ ,316.64
+ ,314.83
+ ,315.15
+ ,315.95
+ ,316.85
+ ,317.78
+ ,318.40
+ ,319.53
+ ,320.41
+ ,320.85
+ ,320.45
+ ,319.44
+ ,317.25
+ ,316.12
+ ,315.27
+ ,316.53
+ ,317.53
+ ,318.58
+ ,318.92
+ ,319.70
+ ,321.22
+ ,322.08
+ ,321.31
+ ,319.58
+ ,317.61
+ ,316.05
+ ,315.83
+ ,316.91
+ ,318.20
+ ,319.41
+ ,320.07
+ ,320.74
+ ,321.40
+ ,322.06
+ ,321.73
+ ,320.27
+ ,318.54
+ ,316.54
+ ,316.71
+ ,317.53
+ ,318.55
+ ,319.27
+ ,320.28
+ ,320.73
+ ,321.97
+ ,322.00
+ ,321.71
+ ,321.05
+ ,318.71
+ ,317.65
+ ,317.14
+ ,318.71
+ ,319.25
+ ,320.46
+ ,321.43
+ ,322.22
+ ,323.54
+ ,323.91
+ ,323.59
+ ,322.26
+ ,320.21
+ ,318.48
+ ,317.94
+ ,319.63
+ ,320.87
+ ,322.17
+ ,322.34
+ ,322.88
+ ,324.25
+ ,324.83
+ ,323.93
+ ,322.39
+ ,320.76
+ ,319.10
+ ,319.23
+ ,320.56
+ ,321.80
+ ,322.40
+ ,322.99
+ ,323.73
+ ,324.86
+ ,325.41
+ ,325.19
+ ,323.97
+ ,321.92
+ ,320.10
+ ,319.96
+ ,320.97
+ ,322.48
+ ,323.52
+ ,323.89
+ ,325.04
+ ,326.01
+ ,326.67
+ ,325.96
+ ,325.13
+ ,322.90
+ ,321.61
+ ,321.01
+ ,322.08
+ ,323.37
+ ,324.34
+ ,325.30
+ ,326.29
+ ,327.54
+ ,327.54
+ ,327.21
+ ,325.98
+ ,324.42
+ ,322.91
+ ,322.90
+ ,323.85
+ ,324.96
+ ,326.01
+ ,326.51
+ ,327.01
+ ,327.62
+ ,328.76
+ ,328.40
+ ,327.20
+ ,325.28
+ ,323.20
+ ,323.40
+ ,324.64
+ ,325.85
+ ,326.60
+ ,327.47
+ ,327.58
+ ,329.56
+ ,329.90
+ ,328.92
+ ,327.89
+ ,326.17
+ ,324.68
+ ,325.04
+ ,326.34
+ ,327.39
+ ,328.37
+ ,329.40
+ ,330.14
+ ,331.33
+ ,332.31
+ ,331.90
+ ,330.70
+ ,329.15
+ ,327.34
+ ,327.02
+ ,327.99
+ ,328.48
+ ,329.18
+ ,330.55
+ ,331.32
+ ,332.48
+ ,332.92
+ ,332.08
+ ,331.02
+ ,329.24
+ ,327.28
+ ,327.21
+ ,328.29
+ ,329.41
+ ,330.23
+ ,331.24
+ ,331.87
+ ,333.14
+ ,333.80
+ ,333.42
+ ,331.73
+ ,329.90
+ ,328.40
+ ,328.17
+ ,329.32
+ ,330.59
+ ,331.58
+ ,332.39
+ ,333.33
+ ,334.41
+ ,334.71
+ ,334.17
+ ,332.88
+ ,330.77
+ ,329.14
+ ,328.77
+ ,330.14
+ ,331.52
+ ,332.75
+ ,333.25
+ ,334.53
+ ,335.90
+ ,336.57
+ ,336.10
+ ,334.76
+ ,332.59
+ ,331.41
+ ,330.98
+ ,332.24
+ ,333.68
+ ,334.80
+ ,335.22
+ ,336.47
+ ,337.59
+ ,337.84
+ ,337.72
+ ,336.37
+ ,334.51
+ ,332.60
+ ,332.37
+ ,333.75
+ ,334.79
+ ,336.05
+ ,336.59
+ ,337.79
+ ,338.71
+ ,339.30
+ ,339.12
+ ,337.56
+ ,335.92
+ ,333.74
+ ,333.70
+ ,335.13
+ ,336.56
+ ,337.84
+ ,338.19
+ ,339.90
+ ,340.60
+ ,341.29
+ ,341.00
+ ,339.39
+ ,337.43
+ ,335.72
+ ,335.84
+ ,336.93
+ ,338.04
+ ,339.06
+ ,340.30
+ ,341.21
+ ,342.33
+ ,342.74
+ ,342.07
+ ,340.32
+ ,338.27
+ ,336.52
+ ,336.68
+ ,338.19
+ ,339.44
+ ,340.57
+ ,341.44
+ ,342.53
+ ,343.39
+ ,343.96
+ ,343.18
+ ,341.88
+ ,339.65
+ ,337.80
+ ,337.69
+ ,339.09
+ ,340.32
+ ,341.20
+ ,342.35
+ ,342.93
+ ,344.77
+ ,345.58
+ ,345.14
+ ,343.81
+ ,342.22
+ ,339.69
+ ,339.82
+ ,340.98
+ ,342.82
+ ,343.52
+ ,344.33
+ ,345.11
+ ,346.88
+ ,347.25
+ ,346.61
+ ,345.22
+ ,343.11
+ ,340.90
+ ,341.17
+ ,342.80
+ ,344.04
+ ,344.79
+ ,345.82
+ ,347.25
+ ,348.17
+ ,348.75
+ ,348.07
+ ,346.38
+ ,344.52
+ ,342.92
+ ,342.63
+ ,344.06
+ ,345.38
+ ,346.12
+ ,346.79
+ ,347.69
+ ,349.38
+ ,350.04
+ ,349.38
+ ,347.78
+ ,345.75
+ ,344.70
+ ,344.01
+ ,345.50
+ ,346.75
+ ,347.86
+ ,348.32
+ ,349.26
+ ,350.84
+ ,351.70
+ ,351.11
+ ,349.37
+ ,347.97
+ ,346.31
+ ,346.22
+ ,347.68
+ ,348.82
+ ,350.29
+ ,351.58
+ ,352.08
+ ,353.45
+ ,354.08
+ ,353.66
+ ,352.25
+ ,350.30
+ ,348.58
+ ,348.74
+ ,349.93
+ ,351.21
+ ,352.62
+ ,352.93
+ ,353.54
+ ,355.27
+ ,355.52
+ ,354.97
+ ,353.74
+ ,351.51
+ ,349.63
+ ,349.82
+ ,351.12
+ ,352.35
+ ,353.47
+ ,354.51
+ ,355.18
+ ,355.98
+ ,356.94
+ ,355.99
+ ,354.58
+ ,352.68
+ ,350.72
+ ,350.92
+ ,352.55
+ ,353.91)
> par8 = 'FALSE'
> par7 = '1'
> par6 = ''
> par5 = '1'
> par4 = ''
> par3 = '0'
> par2 = 'periodic'
> par1 = '12'
> main = 'Seasonal Decomposition by Loess'
> #'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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par1 <- as.numeric(par1) #seasonal period
> if (par2 != 'periodic') par2 <- as.numeric(par2) #s.window
> par3 <- as.numeric(par3) #s.degree
> if (par4 == '') par4 <- NULL else par4 <- as.numeric(par4)#t.window
> par5 <- as.numeric(par5)#t.degree
> if (par6 != '') par6 <- as.numeric(par6)#l.window
> par7 <- as.numeric(par7)#l.degree
> if (par8 == 'FALSE') par8 <- FALSE else par9 <- TRUE #robust
> nx <- length(x)
> x <- ts(x,frequency=par1)
> if (par6 != '') {
+ m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.window=par6, l.degree=par7, robust=par8)
+ } else {
+ m <- stl(x,s.window=par2, s.degree=par3, t.window=par4, t.degre=par5, l.degree=par7, robust=par8)
+ }
> m$time.series
         seasonal    trend    remainder
Jan  1 -0.0801751 315.2364  0.263821819
Feb  1  0.5630906 315.3365  0.420459004
Mar  1  1.2747939 315.4365 -0.221341442
Apr  1  2.3934412 315.5362 -0.369648749
May  1  2.8908384 315.6359 -0.396705992
Jun  1  2.2901417 315.7309 -0.021042888
Jul  1  0.8516326 315.8259 -0.287567318
Aug  1 -1.1543733 315.9181 -0.103724055
Sep  1 -2.9275669 316.0103  0.597306823
Oct  1 -3.1649278 316.1178  0.227100765
Nov  1 -2.0010387 316.2254  0.435644767
Dec  1 -0.9358567 316.3316  0.034264694
Jan  2 -0.0801751 316.4378 -0.087614973
Feb  2  0.5630906 316.5180 -0.271113605
Mar  2  1.2747939 316.5983 -0.453049868
Apr  2  2.3934412 316.6492 -0.172650051
May  2  2.8908384 316.7002  0.278999829
Jun  2  2.2901417 316.7489  0.390944938
Jul  2  0.8516326 316.7977  0.360702512
Aug  2 -1.1543733 316.8466  0.057755333
Sep  2 -2.9275669 316.8956  0.031995769
Oct  2 -3.1649278 316.9317 -0.086745777
Nov  2 -2.0010387 316.9678 -0.126737262
Dec  2 -0.9358567 317.0018 -0.035975845
Jan  3 -0.0801751 317.0359 -0.225714021
Feb  3  0.5630906 317.0998 -0.122933961
Mar  3  1.2747939 317.1638 -0.058591531
Apr  3  2.3934412 317.2574 -0.340802283
May  3  2.8908384 317.3509  0.178237029
Jun  3  2.2901417 317.4462 -0.126361840
Jul  3  0.8516326 317.5415  0.026851757
Aug  3 -1.1543733 317.6280  0.166409705
Sep  3 -2.9275669 317.7144  0.043155269
Oct  3 -3.1649278 317.7860  0.528893704
Nov  3 -2.0010387 317.8577  0.093382199
Dec  3 -0.9358567 317.9177 -0.131826846
Jan  4 -0.0801751 317.9777 -0.117535484
Feb  4  0.5630906 318.0379 -0.201001346
Mar  4  1.2747939 318.0981  0.157095162
Apr  4  2.3934412 318.1583 -0.141761312
May  4  2.8908384 318.2185 -0.259367722
Jun  4  2.2901417 318.2777 -0.117860852
Jul  4  0.8516326 318.3369  0.251458483
Aug  4 -1.1543733 318.3879  0.016475980
Sep  4 -2.9275669 318.4389  0.608681091
Oct  4 -3.1649278 318.4917 -0.056743134
Nov  4 -2.0010387 318.5445 -0.013417300
Dec  4 -0.9358567 318.5920 -0.126096058
Jan  5 -0.0801751 318.6394  0.020725589
Feb  5  0.5630906 318.6707 -0.313789905
Mar  5  1.2747939 318.7019 -0.276743029
Apr  5  2.3934412 318.7361  0.090465101
May  5  2.8908384 318.7702  0.418923295
Jun  5  2.2901417 318.8261  0.193727132
Jul  5  0.8516326 318.8820 -0.153656565
Aug  5 -1.1543733 318.9456 -0.181256872
Sep  5 -2.9275669 319.0092 -0.031669564
Oct  5 -3.1649278 319.0554 -0.060497413
Nov  5 -2.0010387 319.1016 -0.190575202
Dec  5 -0.9358567 319.1419 -0.006053056
Jan  6 -0.0801751 319.1822  0.307969496
Feb  6  0.5630906 319.2364  0.270462268
Mar  6  1.2747939 319.2907  0.174517410
Apr  6  2.3934412 319.3411 -0.334525450
May  6  2.8908384 319.3915 -0.222318246
Jun  6  2.2901417 319.4214  0.018429535
Jul  6  0.8516326 319.4514 -0.033010218
Aug  6 -1.1543733 319.4695  0.224868011
Sep  6 -2.9275669 319.4876 -0.020066146
Oct  6 -3.1649278 319.5022  0.372685154
Nov  6 -2.0010387 319.5169  0.014186514
Dec  6 -0.9358567 319.5308 -0.044912942
Jan  7 -0.0801751 319.5447 -0.194511991
Feb  7  0.5630906 319.5779  0.139034011
Mar  7  1.2747939 319.6111 -0.155857617
Apr  7  2.3934412 319.6769 -0.100329681
May  7  2.8908384 319.7427 -0.633551682
Jun  7  2.2901417 319.8317 -0.411855370
Jul  7  0.8516326 319.9207  0.277653408
Aug  7 -1.1543733 320.0342 -0.169791572
Sep  7 -2.9275669 320.1476  0.429951062
Oct  7 -3.1649278 320.2813  0.023628996
Nov  7 -2.0010387 320.4150  0.296056989
Dec  7 -0.9358567 320.5460 -0.360151202
Jan  8 -0.0801751 320.6770 -0.136858986
Feb  8  0.5630906 320.7815  0.085381597
Mar  8  1.2747939 320.8860  0.059184550
Apr  8  2.3934412 320.9779  0.168656798
May  8  2.8908384 321.0698 -0.050620890
Jun  8  2.2901417 321.1696  0.130276732
Jul  8  0.8516326 321.2694  0.138986820
Aug  8 -1.1543733 321.3588  0.005557962
Sep  8 -2.9275669 321.4483 -0.040683281
Oct  8 -3.1649278 321.5146 -0.409720805
Nov  8 -2.0010387 321.5810  0.049991730
Dec  8 -0.9358567 321.6272  0.178688429
Jan  9 -0.0801751 321.6733  0.576885535
Feb  9  0.5630906 321.7169  0.059961311
Mar  9  1.2747939 321.7606 -0.155400543
Apr  9  2.3934412 321.8178  0.038724167
May  9  2.8908384 321.8751  0.064098941
Jun  9  2.2901417 321.9373 -0.297479902
Jul  9  0.8516326 321.9996 -0.461246280
Aug  9 -1.1543733 322.0634 -0.149010197
Sep  9 -2.9275669 322.1272 -0.099586500
Oct  9 -3.1649278 322.1994  0.195493240
Nov  9 -2.0010387 322.2717  0.289323040
Dec  9 -0.9358567 322.3581  0.377764068
Jan 10 -0.0801751 322.4445  0.035705502
Feb 10  0.5630906 322.5304 -0.103457845
Mar 10  1.2747939 322.6163 -0.161058823
Apr 10  2.3934412 322.6822 -0.215623579
May 10  2.8908384 322.7481 -0.228938272
Jun 10  2.2901417 322.8169  0.082920105
Jul 10  0.8516326 322.8858  0.232590947
Aug 10 -1.1543733 322.9745  0.099910805
Sep 10 -2.9275669 323.0631 -0.035581721
Oct 10 -3.1649278 323.1556 -0.030662012
Nov 10 -2.0010387 323.2480 -0.276992243
Dec 10 -0.9358567 323.3355  0.080307226
Jan 11 -0.0801751 323.4231  0.177107102
Feb 11  0.5630906 323.5183 -0.191415247
Mar 11  1.2747939 323.6136  0.151624773
Apr 11  2.3934412 323.7108 -0.094243626
May 11  2.8908384 323.8080 -0.028861960
Jun 11  2.2901417 323.8957 -0.225885615
Jul 11  0.8516326 323.9835  0.294903196
Aug 11 -1.1543733 324.0778 -0.023443194
Sep 11 -2.9275669 324.1722  0.365398030
Oct 11 -3.1649278 324.2729 -0.097991329
Nov 11 -2.0010387 324.3737 -0.292630630
Dec 11 -0.9358567 324.4687 -0.162869619
Jan 12 -0.0801751 324.5638 -0.143608203
Feb 12  0.5630906 324.6723  0.064643420
Mar 12  1.2747939 324.7807  0.234457413
Apr 12  2.3934412 324.9164  0.230159424
May 12  2.8908384 325.0521 -0.402888502
Jun 12  2.2901417 325.1893 -0.269453372
Jul 12  0.8516326 325.3266 -0.198205777
Aug 12 -1.1543733 325.4318  0.142581052
Sep 12 -2.9275669 325.5370  0.300555496
Oct 12 -3.1649278 325.6127  0.452246108
Nov 12 -2.0010387 325.6884  0.162686780
Dec 12 -0.9358567 325.7572  0.138674408
Jan 13 -0.0801751 325.8260  0.264162442
Feb 13  0.5630906 325.8802  0.066758785
Mar 13  1.2747939 325.9343 -0.199082502
Apr 13  2.3934412 325.9848 -0.758272436
May 13  2.8908384 326.0354 -0.166212306
Jun 13  2.2901417 326.1039  0.005990943
Jul 13  0.8516326 326.1724  0.176006658
Aug 13 -1.1543733 326.2581  0.176272049
Sep 13 -2.9275669 326.3438 -0.216274945
Oct 13 -3.1649278 326.4356  0.129312516
Nov 13 -2.0010387 326.5274  0.113650037
Dec 13 -0.9358567 326.6012  0.184623949
Jan 14 -0.0801751 326.6751  0.005098266
Feb 14  0.5630906 326.7545  0.152398857
Mar 14  1.2747939 326.8339 -0.528738184
Apr 14  2.3934412 326.9482  0.218403956
May 14  2.8908384 327.0624 -0.053203840
Jun 14  2.2901417 327.2079 -0.578011280
Jul 14  0.8516326 327.3534 -0.315006255
Aug 14 -1.1543733 327.5273 -0.202900584
Sep 14 -2.9275669 327.7012 -0.093607299
Oct 14 -3.1649278 327.8995  0.305454014
Nov 14 -2.0010387 328.0978  0.243265387
Dec 14 -0.9358567 328.3171  0.008770483
Jan 15 -0.0801751 328.5364 -0.086224015
Feb 15  0.5630906 328.7561  0.080842620
Mar 15  1.2747939 328.9757 -0.110528376
Apr 15  2.3934412 329.1577 -0.221146985
May 15  2.8908384 329.3397  0.079484469
Jun 15  2.2901417 329.4645  0.145373784
Jul 15  0.8516326 329.5893  0.259075565
Aug 15 -1.1543733 329.6763  0.628062330
Sep 15 -2.9275669 329.7633  0.504236711
Oct 15 -3.1649278 329.8210  0.363924452
Nov 15 -2.0010387 329.8787  0.112362253
Dec 15 -0.9358567 329.9018 -0.485954839
Jan 16 -0.0801751 329.9249 -0.664771525
Feb 16  0.5630906 329.9357  0.051216995
Mar 16  1.2747939 329.9464  0.098767885
Apr 16  2.3934412 329.9791  0.107459237
May 16  2.8908384 330.0118  0.017400653
Jun 16  2.2901417 330.0691 -0.279247358
Jul 16  0.8516326 330.1265  0.041917096
Aug 16 -1.1543733 330.1865  0.207878330
Sep 16 -2.9275669 330.2465 -0.038972821
Oct 16 -3.1649278 330.3097  0.065242538
Nov 16 -2.0010387 330.3728 -0.081792044
Dec 16 -0.9358567 330.4470 -0.101150107
Jan 17 -0.0801751 330.5212 -0.211007763
Feb 17  0.5630906 330.5987  0.078254409
Mar 17  1.2747939 330.6761 -0.080921048
Apr 17  2.3934412 330.7625 -0.015983334
May 17  2.8908384 330.8490  0.060204445
Jun 17  2.2901417 330.9456  0.184264505
Jul 17  0.8516326 331.0422 -0.163862969
Aug 17 -1.1543733 331.1452 -0.090845961
Sep 17 -2.9275669 331.2482  0.079358661
Oct 17 -3.1649278 331.3471 -0.012163030
Nov 17 -2.0010387 331.4460 -0.124934662
Dec 17 -0.9358567 331.5324 -0.006576687
Jan 18 -0.0801751 331.6189  0.041281693
Feb 18  0.5630906 331.6925  0.134453115
Mar 18  1.2747939 331.7660  0.289186906
Apr 18  2.3934412 331.8277  0.188899776
May 18  2.8908384 331.8893 -0.070137290
Jun 18  2.2901417 331.9546 -0.074774405
Jul 18  0.8516326 332.0200  0.008400945
Aug 18 -1.1543733 332.1048 -0.180380251
Sep 18 -2.9275669 332.1895 -0.121973832
Oct 18 -3.1649278 332.3133 -0.378400423
Nov 18 -2.0010387 332.4371 -0.296076955
Dec 18 -0.9358567 332.5974 -0.141553445
Jan 19 -0.0801751 332.7577  0.072470471
Feb 19  0.5630906 332.9361 -0.249148687
Mar 19  1.2747939 333.1144  0.140794524
Apr 19  2.3934412 333.2958  0.210799955
May 19  2.8908384 333.4771  0.202055449
Jun 19  2.2901417 333.6493  0.160586003
Jul 19  0.8516326 333.8214  0.086929022
Aug 19 -1.1543733 333.9781 -0.233720783
Sep 19 -2.9275669 334.1347  0.202817027
Oct 19 -3.1649278 334.2749 -0.130015834
Nov 19 -2.0010387 334.4151 -0.174098636
Dec 19 -0.9358567 334.5497  0.066107256
Jan 20 -0.0801751 334.6844  0.195813555
Feb 20  0.5630906 334.8168 -0.159871680
Mar 20  1.2747939 334.9492  0.246005454
Apr 20  2.3934412 335.0675  0.129019188
May 20  2.8908384 335.1859 -0.236717014
Jun 20  2.2901417 335.2910  0.138840457
Jul 20  0.8516326 335.3962  0.122210394
Aug 20 -1.1543733 335.4992  0.165199222
Sep 20 -2.9275669 335.6022 -0.074624334
Oct 20 -3.1649278 335.7083 -0.173372471
Nov 20 -2.0010387 335.8144 -0.063370547
Dec 20 -0.9358567 335.9257 -0.199866881
Jan 21 -0.0801751 336.0370  0.093137192
Feb 21  0.5630906 336.1498 -0.122876043
Mar 21  1.2747939 336.2625  0.252673091
Apr 21  2.3934412 336.3789 -0.062342047
May 21  2.8908384 336.4953 -0.086107122
Jun 21  2.2901417 336.6219  0.207990780
Jul 21  0.8516326 336.7485 -0.040098853
Aug 21 -1.1543733 336.8937  0.180626618
Sep 21 -2.9275669 337.0390 -0.371460295
Oct 21 -3.1649278 337.1995 -0.334557458
Nov 21 -2.0010387 337.3599 -0.228904561
Dec 21 -0.9358567 337.5252 -0.029342236
Jan 22 -0.0801751 337.6905  0.229720495
Feb 22  0.5630906 337.8525 -0.225588084
Mar 22  1.2747939 338.0145  0.610665707
Apr 22  2.3934412 338.1674  0.039186394
May 22  2.8908384 338.3202  0.078957146
Jun 22  2.2901417 338.4494  0.260433474
Jul 22  0.8516326 338.5786 -0.040277732
Aug 22 -1.1543733 338.7023 -0.117917970
Sep 22 -2.9275669 338.8259 -0.178370593
Oct 22 -3.1649278 338.9517  0.053189117
Nov 22 -2.0010387 339.0775 -0.146501113
Dec 22 -0.9358567 339.1891 -0.213237304
Jan 23 -0.0801751 339.3006 -0.160473089
Feb 23  0.5630906 339.3854  0.351477900
Mar 23  1.2747939 339.4702  0.464991259
Apr 23  2.3934412 339.5470  0.389561584
May 23  2.8908384 339.6238  0.225381974
Jun 23  2.2901417 339.7096  0.070210321
Jul 23  0.8516326 339.7955 -0.327148866
Aug 23 -1.1543733 339.8930 -0.468600479
Sep 23 -2.9275669 339.9904 -0.542864477
Oct 23 -3.1649278 340.1024 -0.257512595
Nov 23 -2.0010387 340.2144 -0.023410652
Dec 23 -0.9358567 340.3422  0.033661657
Jan 24 -0.0801751 340.4699  0.180234373
Feb 24  0.5630906 340.5867  0.290194673
Mar 24  1.2747939 340.7035  0.551717344
Apr 24  2.3934412 340.7854  0.211127238
May 24  2.8908384 340.8674  0.201787196
Jun 24  2.2901417 340.9207 -0.030807092
Jul 24  0.8516326 340.9740  0.054411085
Aug 24 -1.1543733 341.0294 -0.225012450
Sep 24 -2.9275669 341.0848 -0.357248370
Oct 24 -3.1649278 341.1827 -0.327723522
Nov 24 -2.0010387 341.2805 -0.189448613
Dec 24 -0.9358567 341.4393 -0.183453781
Jan 25 -0.0801751 341.5981 -0.317958542
Feb 25  0.5630906 341.7891 -0.002143896
Mar 25  1.2747939 341.9800 -0.324766880
Apr 25  2.3934412 342.1688  0.207747169
May 25  2.8908384 342.3577  0.331511281
Jun 25  2.2901417 342.5387  0.311121179
Jul 25  0.8516326 342.7198  0.238543542
Aug 25 -1.1543733 342.8893  0.485062055
Sep 25 -2.9275669 343.0588 -0.441231816
Oct 25 -3.1649278 343.2109 -0.225959992
Nov 25 -2.0010387 343.3630 -0.381938108
Dec 25 -0.9358567 343.4967  0.259110725
Jan 26 -0.0801751 343.6305 -0.030340036
Feb 26  0.5630906 343.7482  0.018683242
Mar 26  1.2747939 343.8659 -0.030731109
Apr 26  2.3934412 343.9766  0.509944675
May 26  2.8908384 344.0873  0.271870522
Jun 26  2.2901417 344.1929  0.126941033
Jul 26  0.8516326 344.2985  0.069824010
Aug 26 -1.1543733 344.4150 -0.150674025
Sep 26 -2.9275669 344.5316 -0.703984446
Oct 26 -3.1649278 344.6622 -0.327236300
Nov 26 -2.0010387 344.7928  0.008261907
Dec 26 -0.9358567 344.9304  0.045455306
Jan 27 -0.0801751 345.0680 -0.197850888
Feb 27  0.5630906 345.2043  0.052606029
Mar 27  1.2747939 345.3406  0.634625315
Apr 27  2.3934412 345.4620  0.314552011
May 27  2.8908384 345.5834  0.275728770
Jun 27  2.2901417 345.6784  0.101441098
Jul 27  0.8516326 345.7734 -0.245034110
Aug 27 -1.1543733 345.8496 -0.175217246
Sep 27 -2.9275669 345.9258 -0.078212767
Oct 27 -3.1649278 346.0122 -0.217233461
Nov 27 -2.0010387 346.0985 -0.037504094
Dec 27 -0.9358567 346.2120  0.103813561
Jan 28 -0.0801751 346.3255 -0.125368378
Feb 28  0.5630906 346.4508 -0.223930766
Mar 28  1.2747939 346.5761 -0.160930786
Apr 28  2.3934412 346.6997  0.286882127
May 28  2.8908384 346.8232  0.325945104
Jun 28  2.2901417 346.9484  0.141475582
Jul 28  0.8516326 347.0735 -0.145181475
Aug 28 -1.1543733 347.1967 -0.292294033
Sep 28 -2.9275669 347.3198  0.307781023
Oct 28 -3.1649278 347.4483 -0.273400331
Nov 28 -2.0010387 347.5769 -0.075831625
Dec 28 -0.9358567 347.7200 -0.034121999
Jan 29 -0.0801751 347.8631  0.077088032
Feb 29  0.5630906 348.0232 -0.266321311
Mar 29  1.2747939 348.1834 -0.198168285
Apr 29  2.3934412 348.3533  0.093211282
May 29  2.8908384 348.5233  0.285840913
Jun 29  2.2901417 348.7159  0.103918860
Jul 29  0.8516326 348.9086 -0.390190728
Aug 29 -1.1543733 349.1274 -0.002991728
Sep 29 -2.9275669 349.3462 -0.108605113
Oct 29 -3.1649278 349.5744 -0.189461752
Nov 29 -2.0010387 349.8026 -0.121568332
Dec 29 -0.9358567 350.0275 -0.271683634
Jan 30 -0.0801751 350.2525  0.117701470
Feb 30  0.5630906 350.4673  0.549574858
Mar 30  1.2747939 350.6822  0.123010616
Apr 30  2.3934412 350.8766  0.179963943
May 30  2.8908384 351.0710  0.118167334
Jun 30  2.2901417 351.2449  0.124957280
Jul 30  0.8516326 351.4188 -0.020440310
Aug 30 -1.1543733 351.5659 -0.111496910
Sep 30 -2.9275669 351.7129 -0.205365895
Oct 30 -3.1649278 351.8467  0.058194331
Nov 30 -2.0010387 351.9805 -0.049495383
Dec 30 -0.9358567 352.1044  0.041474746
Jan 31 -0.0801751 352.2282  0.471945282
Feb 31  0.5630906 352.3337  0.033187586
Mar 31  1.2747939 352.4392 -0.174007739
Apr 31  2.3934412 352.5262  0.350406485
May 31  2.8908384 352.6131  0.016070773
Jun 31  2.2901417 352.6989 -0.019058509
Jul 31  0.8516326 352.7847  0.103624675
Aug 31 -1.1543733 352.8858 -0.221445785
Sep 31 -2.9275669 352.9869 -0.429328629
Oct 31 -3.1649278 353.0951 -0.110128754
Nov 31 -2.0010387 353.2032 -0.082178818
Dec 31 -0.9358567 353.3055 -0.019657452
Jan 32 -0.0801751 353.4078  0.142364320
Feb 32  0.5630906 353.5011  0.445771098
Mar 32  1.2747939 353.5945  0.310740245
Apr 32  2.3934412 353.6806 -0.094010033
May 32  2.8908384 353.7667  0.282489752
Jun 32  2.2901417 353.8624 -0.162542318
Jul 32  0.8516326 353.9581 -0.229761924
Aug 32 -1.1543733 354.0498 -0.215416653
Sep 32 -2.9275669 354.1415 -0.493883767
Oct 32 -3.1649278 354.2310 -0.146049384
Nov 32 -2.0010387 354.3205  0.230535058
Dec 32 -0.9358567 354.4114  0.434411556
> m$win
   s    t    l 
3841   19   13 
> m$deg
s t l 
0 1 1 
> m$jump
  s   t   l 
385   2   2 
> m$inner
[1] 2
> m$outer
[1] 0
> postscript(file="/var/www/html/rcomp/tmp/177v61293635751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m,main=main)
> dev.off()
null device 
          1 
> mylagmax <- nx/2
> postscript(file="/var/www/html/rcomp/tmp/2igcr1293635751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> acf(as.numeric(x),lag.max = mylagmax,main='Observed')
> acf(as.numeric(m$time.series[,'trend']),na.action=na.pass,lag.max = mylagmax,main='Trend')
> acf(as.numeric(m$time.series[,'seasonal']),na.action=na.pass,lag.max = mylagmax,main='Seasonal')
> acf(as.numeric(m$time.series[,'remainder']),na.action=na.pass,lag.max = mylagmax,main='Remainder')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/3igcr1293635751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> spectrum(as.numeric(x),main='Observed')
> spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend')
> spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal')
> spectrum(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/4b7bc1293635751.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow = c(2,2))
> cpgram(as.numeric(x),main='Observed')
> cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'trend']),'trend']),main='Trend')
> cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'seasonal']),'seasonal']),main='Seasonal')
> cpgram(as.numeric(m$time.series[!is.na(m$time.series[,'remainder']),'remainder']),main='Remainder')
> par(op)
> 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,'Seasonal Decomposition by Loess - Parameters',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Component',header=TRUE)
> a<-table.element(a,'Window',header=TRUE)
> a<-table.element(a,'Degree',header=TRUE)
> a<-table.element(a,'Jump',header=TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,m$win['s'])
> a<-table.element(a,m$deg['s'])
> a<-table.element(a,m$jump['s'])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,m$win['t'])
> a<-table.element(a,m$deg['t'])
> a<-table.element(a,m$jump['t'])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Low-pass',header=TRUE)
> a<-table.element(a,m$win['l'])
> a<-table.element(a,m$deg['l'])
> a<-table.element(a,m$jump['l'])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/57hsl1293635751.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Seasonal Decomposition by Loess - Time Series Components',6,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'t',header=TRUE)
> a<-table.element(a,'Observed',header=TRUE)
> a<-table.element(a,'Fitted',header=TRUE)
> a<-table.element(a,'Seasonal',header=TRUE)
> a<-table.element(a,'Trend',header=TRUE)
> a<-table.element(a,'Remainder',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:nx) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]+m$time.series[i,'remainder'])
+ a<-table.element(a,m$time.series[i,'seasonal'])
+ a<-table.element(a,m$time.series[i,'trend'])
+ a<-table.element(a,m$time.series[i,'remainder'])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/6ai891293635751.tab") 
> 
> try(system("convert tmp/177v61293635751.ps tmp/177v61293635751.png",intern=TRUE))
character(0)
> try(system("convert tmp/2igcr1293635751.ps tmp/2igcr1293635751.png",intern=TRUE))
character(0)
> try(system("convert tmp/3igcr1293635751.ps tmp/3igcr1293635751.png",intern=TRUE))
character(0)
> try(system("convert tmp/4b7bc1293635751.ps tmp/4b7bc1293635751.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  4.879   0.828  10.195