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(1687
+ ,0
+ ,1508
+ ,0
+ ,1507
+ ,0
+ ,1385
+ ,0
+ ,1632
+ ,0
+ ,1511
+ ,0
+ ,1559
+ ,0
+ ,1630
+ ,0
+ ,1579
+ ,0
+ ,1653
+ ,0
+ ,2152
+ ,0
+ ,2148
+ ,0
+ ,1752
+ ,0
+ ,1765
+ ,0
+ ,1717
+ ,0
+ ,1558
+ ,0
+ ,1575
+ ,0
+ ,1520
+ ,0
+ ,1805
+ ,0
+ ,1800
+ ,0
+ ,1719
+ ,0
+ ,2008
+ ,0
+ ,2242
+ ,0
+ ,2478
+ ,0
+ ,2030
+ ,0
+ ,1655
+ ,0
+ ,1693
+ ,0
+ ,1623
+ ,0
+ ,1805
+ ,0
+ ,1746
+ ,0
+ ,1795
+ ,0
+ ,1926
+ ,0
+ ,1619
+ ,0
+ ,1992
+ ,0
+ ,2233
+ ,0
+ ,2192
+ ,0
+ ,2080
+ ,0
+ ,1768
+ ,0
+ ,1835
+ ,0
+ ,1569
+ ,0
+ ,1976
+ ,0
+ ,1853
+ ,0
+ ,1965
+ ,0
+ ,1689
+ ,0
+ ,1778
+ ,0
+ ,1976
+ ,0
+ ,2397
+ ,0
+ ,2654
+ ,0
+ ,2097
+ ,0
+ ,1963
+ ,0
+ ,1677
+ ,0
+ ,1941
+ ,0
+ ,2003
+ ,0
+ ,1813
+ ,0
+ ,2012
+ ,0
+ ,1912
+ ,0
+ ,2084
+ ,0
+ ,2080
+ ,0
+ ,2118
+ ,0
+ ,2150
+ ,0
+ ,1608
+ ,0
+ ,1503
+ ,0
+ ,1548
+ ,0
+ ,1382
+ ,0
+ ,1731
+ ,0
+ ,1798
+ ,0
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+ ,0
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+ ,0
+ ,2004
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+ ,0
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+ ,0
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+ ,0
+ ,1905
+ ,0
+ ,2199
+ ,0
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+ ,1403
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+ ,1528
+ ,0
+ ,1643
+ ,0
+ ,1515
+ ,0
+ ,1685
+ ,0
+ ,2000
+ ,0
+ ,2215
+ ,0
+ ,1956
+ ,0
+ ,1462
+ ,0
+ ,1563
+ ,0
+ ,1459
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+ ,0
+ ,1622
+ ,0
+ ,1657
+ ,0
+ ,1638
+ ,0
+ ,1643
+ ,0
+ ,1683
+ ,0
+ ,2050
+ ,0
+ ,2262
+ ,0
+ ,1813
+ ,0
+ ,1445
+ ,0
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+ ,0
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+ ,0
+ ,1431
+ ,0
+ ,1427
+ ,0
+ ,1554
+ ,0
+ ,1645
+ ,0
+ ,1653
+ ,0
+ ,2016
+ ,0
+ ,2207
+ ,0
+ ,1665
+ ,0
+ ,1361
+ ,0
+ ,1506
+ ,0
+ ,1360
+ ,0
+ ,1453
+ ,0
+ ,1522
+ ,0
+ ,1460
+ ,0
+ ,1552
+ ,0
+ ,1548
+ ,0
+ ,1827
+ ,0
+ ,1737
+ ,0
+ ,1941
+ ,0
+ ,1474
+ ,0
+ ,1458
+ ,0
+ ,1542
+ ,0
+ ,1404
+ ,0
+ ,1522
+ ,0
+ ,1385
+ ,0
+ ,1641
+ ,0
+ ,1510
+ ,0
+ ,1681
+ ,0
+ ,1938
+ ,0
+ ,1868
+ ,0
+ ,1726
+ ,0
+ ,1456
+ ,0
+ ,1445
+ ,0
+ ,1456
+ ,0
+ ,1365
+ ,0
+ ,1487
+ ,0
+ ,1558
+ ,0
+ ,1488
+ ,0
+ ,1684
+ ,0
+ ,1594
+ ,0
+ ,1850
+ ,0
+ ,1998
+ ,0
+ ,2079
+ ,0
+ ,1494
+ ,0
+ ,1057
+ ,1
+ ,1218
+ ,1
+ ,1168
+ ,1
+ ,1236
+ ,1
+ ,1076
+ ,1
+ ,1174
+ ,1
+ ,1139
+ ,1
+ ,1427
+ ,1
+ ,1487
+ ,1
+ ,1483
+ ,1
+ ,1513
+ ,1
+ ,1357
+ ,1
+ ,1165
+ ,1
+ ,1282
+ ,1
+ ,1110
+ ,1
+ ,1297
+ ,1
+ ,1185
+ ,1
+ ,1222
+ ,1
+ ,1284
+ ,1
+ ,1444
+ ,1
+ ,1575
+ ,1
+ ,1737
+ ,1
+ ,1763
+ ,1)
+ ,dim=c(2
+ ,192)
+ ,dimnames=list(c('Y'
+ ,'X')
+ ,1:192))
> y <- array(NA,dim=c(2,192),dimnames=list(c('Y','X'),1:192))
> 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
Y X
1 1687 0
2 1508 0
3 1507 0
4 1385 0
5 1632 0
6 1511 0
7 1559 0
8 1630 0
9 1579 0
10 1653 0
11 2152 0
12 2148 0
13 1752 0
14 1765 0
15 1717 0
16 1558 0
17 1575 0
18 1520 0
19 1805 0
20 1800 0
21 1719 0
22 2008 0
23 2242 0
24 2478 0
25 2030 0
26 1655 0
27 1693 0
28 1623 0
29 1805 0
30 1746 0
31 1795 0
32 1926 0
33 1619 0
34 1992 0
35 2233 0
36 2192 0
37 2080 0
38 1768 0
39 1835 0
40 1569 0
41 1976 0
42 1853 0
43 1965 0
44 1689 0
45 1778 0
46 1976 0
47 2397 0
48 2654 0
49 2097 0
50 1963 0
51 1677 0
52 1941 0
53 2003 0
54 1813 0
55 2012 0
56 1912 0
57 2084 0
58 2080 0
59 2118 0
60 2150 0
61 1608 0
62 1503 0
63 1548 0
64 1382 0
65 1731 0
66 1798 0
67 1779 0
68 1887 0
69 2004 0
70 2077 0
71 2092 0
72 2051 0
73 1577 0
74 1356 0
75 1652 0
76 1382 0
77 1519 0
78 1421 0
79 1442 0
80 1543 0
81 1656 0
82 1561 0
83 1905 0
84 2199 0
85 1473 0
86 1655 0
87 1407 0
88 1395 0
89 1530 0
90 1309 0
91 1526 0
92 1327 0
93 1627 0
94 1748 0
95 1958 0
96 2274 0
97 1648 0
98 1401 0
99 1411 0
100 1403 0
101 1394 0
102 1520 0
103 1528 0
104 1643 0
105 1515 0
106 1685 0
107 2000 0
108 2215 0
109 1956 0
110 1462 0
111 1563 0
112 1459 0
113 1446 0
114 1622 0
115 1657 0
116 1638 0
117 1643 0
118 1683 0
119 2050 0
120 2262 0
121 1813 0
122 1445 0
123 1762 0
124 1461 0
125 1556 0
126 1431 0
127 1427 0
128 1554 0
129 1645 0
130 1653 0
131 2016 0
132 2207 0
133 1665 0
134 1361 0
135 1506 0
136 1360 0
137 1453 0
138 1522 0
139 1460 0
140 1552 0
141 1548 0
142 1827 0
143 1737 0
144 1941 0
145 1474 0
146 1458 0
147 1542 0
148 1404 0
149 1522 0
150 1385 0
151 1641 0
152 1510 0
153 1681 0
154 1938 0
155 1868 0
156 1726 0
157 1456 0
158 1445 0
159 1456 0
160 1365 0
161 1487 0
162 1558 0
163 1488 0
164 1684 0
165 1594 0
166 1850 0
167 1998 0
168 2079 0
169 1494 0
170 1057 1
171 1218 1
172 1168 1
173 1236 1
174 1076 1
175 1174 1
176 1139 1
177 1427 1
178 1487 1
179 1483 1
180 1513 1
181 1357 1
182 1165 1
183 1282 1
184 1110 1
185 1297 1
186 1185 1
187 1222 1
188 1284 1
189 1444 1
190 1575 1
191 1737 1
192 1763 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
1717.8 -396.1
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-408.75 -198.00 -63.75 188.26 936.25
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1717.75 20.00 85.886 < 2e-16 ***
X -396.06 57.79 -6.854 9.76e-11 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 260 on 190 degrees of freedom
Multiple R-squared: 0.1982, Adjusted R-squared: 0.194
F-statistic: 46.97 on 1 and 190 DF, p-value: 9.763e-11
> 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,] 0.155930803 0.311861606 0.844069197
[2,] 0.066493527 0.132987055 0.933506473
[3,] 0.025673833 0.051347666 0.974326167
[4,] 0.012217397 0.024434794 0.987782603
[5,] 0.004379978 0.008759956 0.995620022
[6,] 0.002240160 0.004480320 0.997759840
[7,] 0.223580158 0.447160317 0.776419842
[8,] 0.503981354 0.992037292 0.496018646
[9,] 0.420841205 0.841682411 0.579158795
[10,] 0.345365653 0.690731305 0.654634347
[11,] 0.270018209 0.540036419 0.729981791
[12,] 0.219064424 0.438128849 0.780935576
[13,] 0.171075045 0.342150090 0.828924955
[14,] 0.140711527 0.281423053 0.859288473
[15,] 0.114092243 0.228184485 0.885907757
[16,] 0.090079287 0.180158575 0.909920713
[17,] 0.063884764 0.127769529 0.936115236
[18,] 0.088286043 0.176572086 0.911713957
[19,] 0.254036609 0.508073217 0.745963391
[20,] 0.704134516 0.591730968 0.295865484
[21,] 0.709949406 0.580101187 0.290050594
[22,] 0.661732750 0.676534499 0.338267250
[23,] 0.606522270 0.786955459 0.393477730
[24,] 0.559718944 0.880562112 0.440281056
[25,] 0.503737542 0.992524917 0.496262458
[26,] 0.444960835 0.889921670 0.555039165
[27,] 0.390182856 0.780365712 0.609817144
[28,] 0.362128113 0.724256225 0.637871887
[29,] 0.322724827 0.645449653 0.677275173
[30,] 0.318469940 0.636939879 0.681530060
[31,] 0.447502776 0.895005552 0.552497224
[32,] 0.540190518 0.919618963 0.459809482
[33,] 0.562294510 0.875410980 0.437705490
[34,] 0.510686000 0.978627999 0.489314000
[35,] 0.462277789 0.924555578 0.537722211
[36,] 0.443241447 0.886482894 0.556758553
[37,] 0.425738674 0.851477347 0.574261326
[38,] 0.382073907 0.764147813 0.617926093
[39,] 0.362011567 0.724023135 0.637988433
[40,] 0.321992732 0.643985463 0.678007268
[41,] 0.279428291 0.558856581 0.720571709
[42,] 0.265648617 0.531297234 0.734351383
[43,] 0.493782233 0.987564466 0.506217767
[44,] 0.889937541 0.220124918 0.110062459
[45,] 0.901113662 0.197772675 0.098886338
[46,] 0.891931280 0.216137439 0.108068720
[47,] 0.874958770 0.250082459 0.125041230
[48,] 0.861924269 0.276151462 0.138075731
[49,] 0.857741868 0.284516265 0.142258132
[50,] 0.833787221 0.332425559 0.166212779
[51,] 0.831683517 0.336632966 0.168316483
[52,] 0.813452152 0.373095696 0.186547848
[53,] 0.829990046 0.340019907 0.170009954
[54,] 0.845293938 0.309412125 0.154706062
[55,] 0.869886557 0.260226886 0.130113443
[56,] 0.899973181 0.200053639 0.100026819
[57,] 0.892911538 0.214176924 0.107088462
[58,] 0.899813658 0.200372685 0.100186342
[59,] 0.898719123 0.202561753 0.101280877
[60,] 0.924221577 0.151556846 0.075778423
[61,] 0.910274155 0.179451691 0.089725845
[62,] 0.894792537 0.210414927 0.105207463
[63,] 0.877169795 0.245660411 0.122830205
[64,] 0.864097265 0.271805469 0.135902735
[65,] 0.867873641 0.264252718 0.132126359
[66,] 0.887176441 0.225647117 0.112823559
[67,] 0.908449632 0.183100735 0.091550368
[68,] 0.920869504 0.158260991 0.079130496
[69,] 0.916010299 0.167979401 0.083989701
[70,] 0.940402539 0.119194921 0.059597461
[71,] 0.931292248 0.137415505 0.068707752
[72,] 0.946956056 0.106087888 0.053043944
[73,] 0.945881642 0.108236716 0.054118358
[74,] 0.953436315 0.093127370 0.046563685
[75,] 0.957766908 0.084466183 0.042233092
[76,] 0.954411752 0.091176497 0.045588248
[77,] 0.945791198 0.108417604 0.054208802
[78,] 0.940175036 0.119649928 0.059824964
[79,] 0.936131062 0.127737876 0.063868938
[80,] 0.966338566 0.067322867 0.033661434
[81,] 0.966916075 0.066167850 0.033083925
[82,] 0.960164119 0.079671761 0.039835881
[83,] 0.965277069 0.069445861 0.034722931
[84,] 0.970379455 0.059241090 0.029620545
[85,] 0.967464051 0.065071898 0.032535949
[86,] 0.977737303 0.044525394 0.022262697
[87,] 0.975322648 0.049354704 0.024677352
[88,] 0.982127604 0.035744793 0.017872396
[89,] 0.977903932 0.044192137 0.022096068
[90,] 0.972580035 0.054839929 0.027419965
[91,] 0.973652199 0.052695601 0.026347801
[92,] 0.992147867 0.015704267 0.007852133
[93,] 0.989944177 0.020111646 0.010055823
[94,] 0.991080475 0.017839050 0.008919525
[95,] 0.991852053 0.016295894 0.008147947
[96,] 0.992689156 0.014621688 0.007310844
[97,] 0.993587966 0.012824069 0.006412034
[98,] 0.992587471 0.014825059 0.007412529
[99,] 0.991334311 0.017331378 0.008665689
[100,] 0.988786623 0.022426753 0.011213377
[101,] 0.987197427 0.025605146 0.012802573
[102,] 0.983488735 0.033022530 0.016511265
[103,] 0.986210074 0.027579852 0.013789926
[104,] 0.995481226 0.009037549 0.004518774
[105,] 0.996074339 0.007851321 0.003925661
[106,] 0.995808214 0.008383573 0.004191786
[107,] 0.994712555 0.010574889 0.005287445
[108,] 0.994383717 0.011232567 0.005616283
[109,] 0.994202766 0.011594469 0.005797234
[110,] 0.992371889 0.015256222 0.007628111
[111,] 0.989937179 0.020125642 0.010062821
[112,] 0.986889938 0.026220124 0.013110062
[113,] 0.983038754 0.033922493 0.016961246
[114,] 0.978201030 0.043597941 0.021798970
[115,] 0.985499029 0.029001943 0.014500971
[116,] 0.997273738 0.005452524 0.002726262
[117,] 0.996840500 0.006319000 0.003159500
[118,] 0.996604329 0.006791343 0.003395671
[119,] 0.995731903 0.008536193 0.004268097
[120,] 0.995231935 0.009536129 0.004768065
[121,] 0.993835720 0.012328561 0.006164280
[122,] 0.993579113 0.012841775 0.006420887
[123,] 0.993393504 0.013212993 0.006606496
[124,] 0.991524685 0.016950630 0.008475315
[125,] 0.988655488 0.022689023 0.011344512
[126,] 0.984959360 0.030081280 0.015040640
[127,] 0.990221627 0.019556746 0.009778373
[128,] 0.998279991 0.003440018 0.001720009
[129,] 0.997591625 0.004816750 0.002408375
[130,] 0.997892813 0.004214375 0.002107187
[131,] 0.997293899 0.005412202 0.002706101
[132,] 0.997677692 0.004644616 0.002322308
[133,] 0.997354591 0.005290817 0.002645409
[134,] 0.996546554 0.006906892 0.003453446
[135,] 0.996045290 0.007909420 0.003954710
[136,] 0.994686971 0.010626058 0.005313029
[137,] 0.992957425 0.014085150 0.007042575
[138,] 0.992033010 0.015933981 0.007966990
[139,] 0.989583771 0.020832458 0.010416229
[140,] 0.992081659 0.015836682 0.007918341
[141,] 0.990449484 0.019101031 0.009550516
[142,] 0.988949707 0.022100585 0.011050293
[143,] 0.985456061 0.029087878 0.014543939
[144,] 0.985571135 0.028857731 0.014428865
[145,] 0.981780175 0.036439651 0.018219825
[146,] 0.983522710 0.032954581 0.016477290
[147,] 0.977248898 0.045502204 0.022751102
[148,] 0.972640095 0.054719809 0.027359905
[149,] 0.962925549 0.074148902 0.037074451
[150,] 0.967302522 0.065394955 0.032697478
[151,] 0.966685544 0.066628912 0.033314456
[152,] 0.957191721 0.085616558 0.042808279
[153,] 0.951103840 0.097792320 0.048896160
[154,] 0.946573335 0.106853330 0.053426665
[155,] 0.941989760 0.116020480 0.058010240
[156,] 0.953946389 0.092107223 0.046053611
[157,] 0.951782015 0.096435970 0.048217985
[158,] 0.943781676 0.112436649 0.056218324
[159,] 0.948852830 0.102294340 0.051147170
[160,] 0.933869588 0.132260824 0.066130412
[161,] 0.932017992 0.135964017 0.067982008
[162,] 0.908408409 0.183183183 0.091591591
[163,] 0.896695572 0.206608857 0.103304428
[164,] 0.946324945 0.107350109 0.053675055
[165,] 0.925761978 0.148476043 0.074238022
[166,] 0.932074147 0.135851705 0.067925853
[167,] 0.912198628 0.175602743 0.087801372
[168,] 0.897139750 0.205720500 0.102860250
[169,] 0.867972376 0.264055249 0.132027624
[170,] 0.884055444 0.231889112 0.115944556
[171,] 0.871741028 0.256517944 0.128258972
[172,] 0.875980463 0.248039073 0.124019537
[173,] 0.829472349 0.341055301 0.170527651
[174,] 0.781248855 0.437502290 0.218751145
[175,] 0.723085430 0.553829141 0.276914570
[176,] 0.668097907 0.663804186 0.331902093
[177,] 0.573634400 0.852731200 0.426365600
[178,] 0.540064086 0.919871828 0.459935914
[179,] 0.449856184 0.899712367 0.550143816
[180,] 0.491029489 0.982058978 0.508970511
[181,] 0.403462687 0.806925374 0.596537313
[182,] 0.428895543 0.857791087 0.571104457
[183,] 0.488140963 0.976281926 0.511859037
> postscript(file="/var/www/html/rcomp/tmp/1g2oy1258722864.ps",horizontal=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/21s5w1258722864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3bksp1258722864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/40yy41258722864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/58azj1258722864.ps",horizontal=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 = 192
Frequency = 1
1 2 3 4 5 6
-30.7514793 -209.7514793 -210.7514793 -332.7514793 -85.7514793 -206.7514793
7 8 9 10 11 12
-158.7514793 -87.7514793 -138.7514793 -64.7514793 434.2485207 430.2485207
13 14 15 16 17 18
34.2485207 47.2485207 -0.7514793 -159.7514793 -142.7514793 -197.7514793
19 20 21 22 23 24
87.2485207 82.2485207 1.2485207 290.2485207 524.2485207 760.2485207
25 26 27 28 29 30
312.2485207 -62.7514793 -24.7514793 -94.7514793 87.2485207 28.2485207
31 32 33 34 35 36
77.2485207 208.2485207 -98.7514793 274.2485207 515.2485207 474.2485207
37 38 39 40 41 42
362.2485207 50.2485207 117.2485207 -148.7514793 258.2485207 135.2485207
43 44 45 46 47 48
247.2485207 -28.7514793 60.2485207 258.2485207 679.2485207 936.2485207
49 50 51 52 53 54
379.2485207 245.2485207 -40.7514793 223.2485207 285.2485207 95.2485207
55 56 57 58 59 60
294.2485207 194.2485207 366.2485207 362.2485207 400.2485207 432.2485207
61 62 63 64 65 66
-109.7514793 -214.7514793 -169.7514793 -335.7514793 13.2485207 80.2485207
67 68 69 70 71 72
61.2485207 169.2485207 286.2485207 359.2485207 374.2485207 333.2485207
73 74 75 76 77 78
-140.7514793 -361.7514793 -65.7514793 -335.7514793 -198.7514793 -296.7514793
79 80 81 82 83 84
-275.7514793 -174.7514793 -61.7514793 -156.7514793 187.2485207 481.2485207
85 86 87 88 89 90
-244.7514793 -62.7514793 -310.7514793 -322.7514793 -187.7514793 -408.7514793
91 92 93 94 95 96
-191.7514793 -390.7514793 -90.7514793 30.2485207 240.2485207 556.2485207
97 98 99 100 101 102
-69.7514793 -316.7514793 -306.7514793 -314.7514793 -323.7514793 -197.7514793
103 104 105 106 107 108
-189.7514793 -74.7514793 -202.7514793 -32.7514793 282.2485207 497.2485207
109 110 111 112 113 114
238.2485207 -255.7514793 -154.7514793 -258.7514793 -271.7514793 -95.7514793
115 116 117 118 119 120
-60.7514793 -79.7514793 -74.7514793 -34.7514793 332.2485207 544.2485207
121 122 123 124 125 126
95.2485207 -272.7514793 44.2485207 -256.7514793 -161.7514793 -286.7514793
127 128 129 130 131 132
-290.7514793 -163.7514793 -72.7514793 -64.7514793 298.2485207 489.2485207
133 134 135 136 137 138
-52.7514793 -356.7514793 -211.7514793 -357.7514793 -264.7514793 -195.7514793
139 140 141 142 143 144
-257.7514793 -165.7514793 -169.7514793 109.2485207 19.2485207 223.2485207
145 146 147 148 149 150
-243.7514793 -259.7514793 -175.7514793 -313.7514793 -195.7514793 -332.7514793
151 152 153 154 155 156
-76.7514793 -207.7514793 -36.7514793 220.2485207 150.2485207 8.2485207
157 158 159 160 161 162
-261.7514793 -272.7514793 -261.7514793 -352.7514793 -230.7514793 -159.7514793
163 164 165 166 167 168
-229.7514793 -33.7514793 -123.7514793 132.2485207 280.2485207 361.2485207
169 170 171 172 173 174
-223.7514793 -264.6956522 -103.6956522 -153.6956522 -85.6956522 -245.6956522
175 176 177 178 179 180
-147.6956522 -182.6956522 105.3043478 165.3043478 161.3043478 191.3043478
181 182 183 184 185 186
35.3043478 -156.6956522 -39.6956522 -211.6956522 -24.6956522 -136.6956522
187 188 189 190 191 192
-99.6956522 -37.6956522 122.3043478 253.3043478 415.3043478 441.3043478
> postscript(file="/var/www/html/rcomp/tmp/6k8u81258722864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 192
Frequency = 1
lag(myerror, k = 1) myerror
0 -30.7514793 NA
1 -209.7514793 -30.7514793
2 -210.7514793 -209.7514793
3 -332.7514793 -210.7514793
4 -85.7514793 -332.7514793
5 -206.7514793 -85.7514793
6 -158.7514793 -206.7514793
7 -87.7514793 -158.7514793
8 -138.7514793 -87.7514793
9 -64.7514793 -138.7514793
10 434.2485207 -64.7514793
11 430.2485207 434.2485207
12 34.2485207 430.2485207
13 47.2485207 34.2485207
14 -0.7514793 47.2485207
15 -159.7514793 -0.7514793
16 -142.7514793 -159.7514793
17 -197.7514793 -142.7514793
18 87.2485207 -197.7514793
19 82.2485207 87.2485207
20 1.2485207 82.2485207
21 290.2485207 1.2485207
22 524.2485207 290.2485207
23 760.2485207 524.2485207
24 312.2485207 760.2485207
25 -62.7514793 312.2485207
26 -24.7514793 -62.7514793
27 -94.7514793 -24.7514793
28 87.2485207 -94.7514793
29 28.2485207 87.2485207
30 77.2485207 28.2485207
31 208.2485207 77.2485207
32 -98.7514793 208.2485207
33 274.2485207 -98.7514793
34 515.2485207 274.2485207
35 474.2485207 515.2485207
36 362.2485207 474.2485207
37 50.2485207 362.2485207
38 117.2485207 50.2485207
39 -148.7514793 117.2485207
40 258.2485207 -148.7514793
41 135.2485207 258.2485207
42 247.2485207 135.2485207
43 -28.7514793 247.2485207
44 60.2485207 -28.7514793
45 258.2485207 60.2485207
46 679.2485207 258.2485207
47 936.2485207 679.2485207
48 379.2485207 936.2485207
49 245.2485207 379.2485207
50 -40.7514793 245.2485207
51 223.2485207 -40.7514793
52 285.2485207 223.2485207
53 95.2485207 285.2485207
54 294.2485207 95.2485207
55 194.2485207 294.2485207
56 366.2485207 194.2485207
57 362.2485207 366.2485207
58 400.2485207 362.2485207
59 432.2485207 400.2485207
60 -109.7514793 432.2485207
61 -214.7514793 -109.7514793
62 -169.7514793 -214.7514793
63 -335.7514793 -169.7514793
64 13.2485207 -335.7514793
65 80.2485207 13.2485207
66 61.2485207 80.2485207
67 169.2485207 61.2485207
68 286.2485207 169.2485207
69 359.2485207 286.2485207
70 374.2485207 359.2485207
71 333.2485207 374.2485207
72 -140.7514793 333.2485207
73 -361.7514793 -140.7514793
74 -65.7514793 -361.7514793
75 -335.7514793 -65.7514793
76 -198.7514793 -335.7514793
77 -296.7514793 -198.7514793
78 -275.7514793 -296.7514793
79 -174.7514793 -275.7514793
80 -61.7514793 -174.7514793
81 -156.7514793 -61.7514793
82 187.2485207 -156.7514793
83 481.2485207 187.2485207
84 -244.7514793 481.2485207
85 -62.7514793 -244.7514793
86 -310.7514793 -62.7514793
87 -322.7514793 -310.7514793
88 -187.7514793 -322.7514793
89 -408.7514793 -187.7514793
90 -191.7514793 -408.7514793
91 -390.7514793 -191.7514793
92 -90.7514793 -390.7514793
93 30.2485207 -90.7514793
94 240.2485207 30.2485207
95 556.2485207 240.2485207
96 -69.7514793 556.2485207
97 -316.7514793 -69.7514793
98 -306.7514793 -316.7514793
99 -314.7514793 -306.7514793
100 -323.7514793 -314.7514793
101 -197.7514793 -323.7514793
102 -189.7514793 -197.7514793
103 -74.7514793 -189.7514793
104 -202.7514793 -74.7514793
105 -32.7514793 -202.7514793
106 282.2485207 -32.7514793
107 497.2485207 282.2485207
108 238.2485207 497.2485207
109 -255.7514793 238.2485207
110 -154.7514793 -255.7514793
111 -258.7514793 -154.7514793
112 -271.7514793 -258.7514793
113 -95.7514793 -271.7514793
114 -60.7514793 -95.7514793
115 -79.7514793 -60.7514793
116 -74.7514793 -79.7514793
117 -34.7514793 -74.7514793
118 332.2485207 -34.7514793
119 544.2485207 332.2485207
120 95.2485207 544.2485207
121 -272.7514793 95.2485207
122 44.2485207 -272.7514793
123 -256.7514793 44.2485207
124 -161.7514793 -256.7514793
125 -286.7514793 -161.7514793
126 -290.7514793 -286.7514793
127 -163.7514793 -290.7514793
128 -72.7514793 -163.7514793
129 -64.7514793 -72.7514793
130 298.2485207 -64.7514793
131 489.2485207 298.2485207
132 -52.7514793 489.2485207
133 -356.7514793 -52.7514793
134 -211.7514793 -356.7514793
135 -357.7514793 -211.7514793
136 -264.7514793 -357.7514793
137 -195.7514793 -264.7514793
138 -257.7514793 -195.7514793
139 -165.7514793 -257.7514793
140 -169.7514793 -165.7514793
141 109.2485207 -169.7514793
142 19.2485207 109.2485207
143 223.2485207 19.2485207
144 -243.7514793 223.2485207
145 -259.7514793 -243.7514793
146 -175.7514793 -259.7514793
147 -313.7514793 -175.7514793
148 -195.7514793 -313.7514793
149 -332.7514793 -195.7514793
150 -76.7514793 -332.7514793
151 -207.7514793 -76.7514793
152 -36.7514793 -207.7514793
153 220.2485207 -36.7514793
154 150.2485207 220.2485207
155 8.2485207 150.2485207
156 -261.7514793 8.2485207
157 -272.7514793 -261.7514793
158 -261.7514793 -272.7514793
159 -352.7514793 -261.7514793
160 -230.7514793 -352.7514793
161 -159.7514793 -230.7514793
162 -229.7514793 -159.7514793
163 -33.7514793 -229.7514793
164 -123.7514793 -33.7514793
165 132.2485207 -123.7514793
166 280.2485207 132.2485207
167 361.2485207 280.2485207
168 -223.7514793 361.2485207
169 -264.6956522 -223.7514793
170 -103.6956522 -264.6956522
171 -153.6956522 -103.6956522
172 -85.6956522 -153.6956522
173 -245.6956522 -85.6956522
174 -147.6956522 -245.6956522
175 -182.6956522 -147.6956522
176 105.3043478 -182.6956522
177 165.3043478 105.3043478
178 161.3043478 165.3043478
179 191.3043478 161.3043478
180 35.3043478 191.3043478
181 -156.6956522 35.3043478
182 -39.6956522 -156.6956522
183 -211.6956522 -39.6956522
184 -24.6956522 -211.6956522
185 -136.6956522 -24.6956522
186 -99.6956522 -136.6956522
187 -37.6956522 -99.6956522
188 122.3043478 -37.6956522
189 253.3043478 122.3043478
190 415.3043478 253.3043478
191 441.3043478 415.3043478
192 NA 441.3043478
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -209.7514793 -30.7514793
[2,] -210.7514793 -209.7514793
[3,] -332.7514793 -210.7514793
[4,] -85.7514793 -332.7514793
[5,] -206.7514793 -85.7514793
[6,] -158.7514793 -206.7514793
[7,] -87.7514793 -158.7514793
[8,] -138.7514793 -87.7514793
[9,] -64.7514793 -138.7514793
[10,] 434.2485207 -64.7514793
[11,] 430.2485207 434.2485207
[12,] 34.2485207 430.2485207
[13,] 47.2485207 34.2485207
[14,] -0.7514793 47.2485207
[15,] -159.7514793 -0.7514793
[16,] -142.7514793 -159.7514793
[17,] -197.7514793 -142.7514793
[18,] 87.2485207 -197.7514793
[19,] 82.2485207 87.2485207
[20,] 1.2485207 82.2485207
[21,] 290.2485207 1.2485207
[22,] 524.2485207 290.2485207
[23,] 760.2485207 524.2485207
[24,] 312.2485207 760.2485207
[25,] -62.7514793 312.2485207
[26,] -24.7514793 -62.7514793
[27,] -94.7514793 -24.7514793
[28,] 87.2485207 -94.7514793
[29,] 28.2485207 87.2485207
[30,] 77.2485207 28.2485207
[31,] 208.2485207 77.2485207
[32,] -98.7514793 208.2485207
[33,] 274.2485207 -98.7514793
[34,] 515.2485207 274.2485207
[35,] 474.2485207 515.2485207
[36,] 362.2485207 474.2485207
[37,] 50.2485207 362.2485207
[38,] 117.2485207 50.2485207
[39,] -148.7514793 117.2485207
[40,] 258.2485207 -148.7514793
[41,] 135.2485207 258.2485207
[42,] 247.2485207 135.2485207
[43,] -28.7514793 247.2485207
[44,] 60.2485207 -28.7514793
[45,] 258.2485207 60.2485207
[46,] 679.2485207 258.2485207
[47,] 936.2485207 679.2485207
[48,] 379.2485207 936.2485207
[49,] 245.2485207 379.2485207
[50,] -40.7514793 245.2485207
[51,] 223.2485207 -40.7514793
[52,] 285.2485207 223.2485207
[53,] 95.2485207 285.2485207
[54,] 294.2485207 95.2485207
[55,] 194.2485207 294.2485207
[56,] 366.2485207 194.2485207
[57,] 362.2485207 366.2485207
[58,] 400.2485207 362.2485207
[59,] 432.2485207 400.2485207
[60,] -109.7514793 432.2485207
[61,] -214.7514793 -109.7514793
[62,] -169.7514793 -214.7514793
[63,] -335.7514793 -169.7514793
[64,] 13.2485207 -335.7514793
[65,] 80.2485207 13.2485207
[66,] 61.2485207 80.2485207
[67,] 169.2485207 61.2485207
[68,] 286.2485207 169.2485207
[69,] 359.2485207 286.2485207
[70,] 374.2485207 359.2485207
[71,] 333.2485207 374.2485207
[72,] -140.7514793 333.2485207
[73,] -361.7514793 -140.7514793
[74,] -65.7514793 -361.7514793
[75,] -335.7514793 -65.7514793
[76,] -198.7514793 -335.7514793
[77,] -296.7514793 -198.7514793
[78,] -275.7514793 -296.7514793
[79,] -174.7514793 -275.7514793
[80,] -61.7514793 -174.7514793
[81,] -156.7514793 -61.7514793
[82,] 187.2485207 -156.7514793
[83,] 481.2485207 187.2485207
[84,] -244.7514793 481.2485207
[85,] -62.7514793 -244.7514793
[86,] -310.7514793 -62.7514793
[87,] -322.7514793 -310.7514793
[88,] -187.7514793 -322.7514793
[89,] -408.7514793 -187.7514793
[90,] -191.7514793 -408.7514793
[91,] -390.7514793 -191.7514793
[92,] -90.7514793 -390.7514793
[93,] 30.2485207 -90.7514793
[94,] 240.2485207 30.2485207
[95,] 556.2485207 240.2485207
[96,] -69.7514793 556.2485207
[97,] -316.7514793 -69.7514793
[98,] -306.7514793 -316.7514793
[99,] -314.7514793 -306.7514793
[100,] -323.7514793 -314.7514793
[101,] -197.7514793 -323.7514793
[102,] -189.7514793 -197.7514793
[103,] -74.7514793 -189.7514793
[104,] -202.7514793 -74.7514793
[105,] -32.7514793 -202.7514793
[106,] 282.2485207 -32.7514793
[107,] 497.2485207 282.2485207
[108,] 238.2485207 497.2485207
[109,] -255.7514793 238.2485207
[110,] -154.7514793 -255.7514793
[111,] -258.7514793 -154.7514793
[112,] -271.7514793 -258.7514793
[113,] -95.7514793 -271.7514793
[114,] -60.7514793 -95.7514793
[115,] -79.7514793 -60.7514793
[116,] -74.7514793 -79.7514793
[117,] -34.7514793 -74.7514793
[118,] 332.2485207 -34.7514793
[119,] 544.2485207 332.2485207
[120,] 95.2485207 544.2485207
[121,] -272.7514793 95.2485207
[122,] 44.2485207 -272.7514793
[123,] -256.7514793 44.2485207
[124,] -161.7514793 -256.7514793
[125,] -286.7514793 -161.7514793
[126,] -290.7514793 -286.7514793
[127,] -163.7514793 -290.7514793
[128,] -72.7514793 -163.7514793
[129,] -64.7514793 -72.7514793
[130,] 298.2485207 -64.7514793
[131,] 489.2485207 298.2485207
[132,] -52.7514793 489.2485207
[133,] -356.7514793 -52.7514793
[134,] -211.7514793 -356.7514793
[135,] -357.7514793 -211.7514793
[136,] -264.7514793 -357.7514793
[137,] -195.7514793 -264.7514793
[138,] -257.7514793 -195.7514793
[139,] -165.7514793 -257.7514793
[140,] -169.7514793 -165.7514793
[141,] 109.2485207 -169.7514793
[142,] 19.2485207 109.2485207
[143,] 223.2485207 19.2485207
[144,] -243.7514793 223.2485207
[145,] -259.7514793 -243.7514793
[146,] -175.7514793 -259.7514793
[147,] -313.7514793 -175.7514793
[148,] -195.7514793 -313.7514793
[149,] -332.7514793 -195.7514793
[150,] -76.7514793 -332.7514793
[151,] -207.7514793 -76.7514793
[152,] -36.7514793 -207.7514793
[153,] 220.2485207 -36.7514793
[154,] 150.2485207 220.2485207
[155,] 8.2485207 150.2485207
[156,] -261.7514793 8.2485207
[157,] -272.7514793 -261.7514793
[158,] -261.7514793 -272.7514793
[159,] -352.7514793 -261.7514793
[160,] -230.7514793 -352.7514793
[161,] -159.7514793 -230.7514793
[162,] -229.7514793 -159.7514793
[163,] -33.7514793 -229.7514793
[164,] -123.7514793 -33.7514793
[165,] 132.2485207 -123.7514793
[166,] 280.2485207 132.2485207
[167,] 361.2485207 280.2485207
[168,] -223.7514793 361.2485207
[169,] -264.6956522 -223.7514793
[170,] -103.6956522 -264.6956522
[171,] -153.6956522 -103.6956522
[172,] -85.6956522 -153.6956522
[173,] -245.6956522 -85.6956522
[174,] -147.6956522 -245.6956522
[175,] -182.6956522 -147.6956522
[176,] 105.3043478 -182.6956522
[177,] 165.3043478 105.3043478
[178,] 161.3043478 165.3043478
[179,] 191.3043478 161.3043478
[180,] 35.3043478 191.3043478
[181,] -156.6956522 35.3043478
[182,] -39.6956522 -156.6956522
[183,] -211.6956522 -39.6956522
[184,] -24.6956522 -211.6956522
[185,] -136.6956522 -24.6956522
[186,] -99.6956522 -136.6956522
[187,] -37.6956522 -99.6956522
[188,] 122.3043478 -37.6956522
[189,] 253.3043478 122.3043478
[190,] 415.3043478 253.3043478
[191,] 441.3043478 415.3043478
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -209.7514793 -30.7514793
2 -210.7514793 -209.7514793
3 -332.7514793 -210.7514793
4 -85.7514793 -332.7514793
5 -206.7514793 -85.7514793
6 -158.7514793 -206.7514793
7 -87.7514793 -158.7514793
8 -138.7514793 -87.7514793
9 -64.7514793 -138.7514793
10 434.2485207 -64.7514793
11 430.2485207 434.2485207
12 34.2485207 430.2485207
13 47.2485207 34.2485207
14 -0.7514793 47.2485207
15 -159.7514793 -0.7514793
16 -142.7514793 -159.7514793
17 -197.7514793 -142.7514793
18 87.2485207 -197.7514793
19 82.2485207 87.2485207
20 1.2485207 82.2485207
21 290.2485207 1.2485207
22 524.2485207 290.2485207
23 760.2485207 524.2485207
24 312.2485207 760.2485207
25 -62.7514793 312.2485207
26 -24.7514793 -62.7514793
27 -94.7514793 -24.7514793
28 87.2485207 -94.7514793
29 28.2485207 87.2485207
30 77.2485207 28.2485207
31 208.2485207 77.2485207
32 -98.7514793 208.2485207
33 274.2485207 -98.7514793
34 515.2485207 274.2485207
35 474.2485207 515.2485207
36 362.2485207 474.2485207
37 50.2485207 362.2485207
38 117.2485207 50.2485207
39 -148.7514793 117.2485207
40 258.2485207 -148.7514793
41 135.2485207 258.2485207
42 247.2485207 135.2485207
43 -28.7514793 247.2485207
44 60.2485207 -28.7514793
45 258.2485207 60.2485207
46 679.2485207 258.2485207
47 936.2485207 679.2485207
48 379.2485207 936.2485207
49 245.2485207 379.2485207
50 -40.7514793 245.2485207
51 223.2485207 -40.7514793
52 285.2485207 223.2485207
53 95.2485207 285.2485207
54 294.2485207 95.2485207
55 194.2485207 294.2485207
56 366.2485207 194.2485207
57 362.2485207 366.2485207
58 400.2485207 362.2485207
59 432.2485207 400.2485207
60 -109.7514793 432.2485207
61 -214.7514793 -109.7514793
62 -169.7514793 -214.7514793
63 -335.7514793 -169.7514793
64 13.2485207 -335.7514793
65 80.2485207 13.2485207
66 61.2485207 80.2485207
67 169.2485207 61.2485207
68 286.2485207 169.2485207
69 359.2485207 286.2485207
70 374.2485207 359.2485207
71 333.2485207 374.2485207
72 -140.7514793 333.2485207
73 -361.7514793 -140.7514793
74 -65.7514793 -361.7514793
75 -335.7514793 -65.7514793
76 -198.7514793 -335.7514793
77 -296.7514793 -198.7514793
78 -275.7514793 -296.7514793
79 -174.7514793 -275.7514793
80 -61.7514793 -174.7514793
81 -156.7514793 -61.7514793
82 187.2485207 -156.7514793
83 481.2485207 187.2485207
84 -244.7514793 481.2485207
85 -62.7514793 -244.7514793
86 -310.7514793 -62.7514793
87 -322.7514793 -310.7514793
88 -187.7514793 -322.7514793
89 -408.7514793 -187.7514793
90 -191.7514793 -408.7514793
91 -390.7514793 -191.7514793
92 -90.7514793 -390.7514793
93 30.2485207 -90.7514793
94 240.2485207 30.2485207
95 556.2485207 240.2485207
96 -69.7514793 556.2485207
97 -316.7514793 -69.7514793
98 -306.7514793 -316.7514793
99 -314.7514793 -306.7514793
100 -323.7514793 -314.7514793
101 -197.7514793 -323.7514793
102 -189.7514793 -197.7514793
103 -74.7514793 -189.7514793
104 -202.7514793 -74.7514793
105 -32.7514793 -202.7514793
106 282.2485207 -32.7514793
107 497.2485207 282.2485207
108 238.2485207 497.2485207
109 -255.7514793 238.2485207
110 -154.7514793 -255.7514793
111 -258.7514793 -154.7514793
112 -271.7514793 -258.7514793
113 -95.7514793 -271.7514793
114 -60.7514793 -95.7514793
115 -79.7514793 -60.7514793
116 -74.7514793 -79.7514793
117 -34.7514793 -74.7514793
118 332.2485207 -34.7514793
119 544.2485207 332.2485207
120 95.2485207 544.2485207
121 -272.7514793 95.2485207
122 44.2485207 -272.7514793
123 -256.7514793 44.2485207
124 -161.7514793 -256.7514793
125 -286.7514793 -161.7514793
126 -290.7514793 -286.7514793
127 -163.7514793 -290.7514793
128 -72.7514793 -163.7514793
129 -64.7514793 -72.7514793
130 298.2485207 -64.7514793
131 489.2485207 298.2485207
132 -52.7514793 489.2485207
133 -356.7514793 -52.7514793
134 -211.7514793 -356.7514793
135 -357.7514793 -211.7514793
136 -264.7514793 -357.7514793
137 -195.7514793 -264.7514793
138 -257.7514793 -195.7514793
139 -165.7514793 -257.7514793
140 -169.7514793 -165.7514793
141 109.2485207 -169.7514793
142 19.2485207 109.2485207
143 223.2485207 19.2485207
144 -243.7514793 223.2485207
145 -259.7514793 -243.7514793
146 -175.7514793 -259.7514793
147 -313.7514793 -175.7514793
148 -195.7514793 -313.7514793
149 -332.7514793 -195.7514793
150 -76.7514793 -332.7514793
151 -207.7514793 -76.7514793
152 -36.7514793 -207.7514793
153 220.2485207 -36.7514793
154 150.2485207 220.2485207
155 8.2485207 150.2485207
156 -261.7514793 8.2485207
157 -272.7514793 -261.7514793
158 -261.7514793 -272.7514793
159 -352.7514793 -261.7514793
160 -230.7514793 -352.7514793
161 -159.7514793 -230.7514793
162 -229.7514793 -159.7514793
163 -33.7514793 -229.7514793
164 -123.7514793 -33.7514793
165 132.2485207 -123.7514793
166 280.2485207 132.2485207
167 361.2485207 280.2485207
168 -223.7514793 361.2485207
169 -264.6956522 -223.7514793
170 -103.6956522 -264.6956522
171 -153.6956522 -103.6956522
172 -85.6956522 -153.6956522
173 -245.6956522 -85.6956522
174 -147.6956522 -245.6956522
175 -182.6956522 -147.6956522
176 105.3043478 -182.6956522
177 165.3043478 105.3043478
178 161.3043478 165.3043478
179 191.3043478 161.3043478
180 35.3043478 191.3043478
181 -156.6956522 35.3043478
182 -39.6956522 -156.6956522
183 -211.6956522 -39.6956522
184 -24.6956522 -211.6956522
185 -136.6956522 -24.6956522
186 -99.6956522 -136.6956522
187 -37.6956522 -99.6956522
188 122.3043478 -37.6956522
189 253.3043478 122.3043478
190 415.3043478 253.3043478
191 441.3043478 415.3043478
> 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/7g0sb1258722864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8b1gd1258722864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/98oyk1258722864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10q83o1258722864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/1195vo1258722864.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/1263du1258722864.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/13kxc31258722864.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/14txau1258722864.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/15u4l11258722864.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/16lft61258722864.tab")
+ }
>
> system("convert tmp/1g2oy1258722864.ps tmp/1g2oy1258722864.png")
> system("convert tmp/21s5w1258722864.ps tmp/21s5w1258722864.png")
> system("convert tmp/3bksp1258722864.ps tmp/3bksp1258722864.png")
> system("convert tmp/40yy41258722864.ps tmp/40yy41258722864.png")
> system("convert tmp/58azj1258722864.ps tmp/58azj1258722864.png")
> system("convert tmp/6k8u81258722864.ps tmp/6k8u81258722864.png")
> system("convert tmp/7g0sb1258722864.ps tmp/7g0sb1258722864.png")
> system("convert tmp/8b1gd1258722864.ps tmp/8b1gd1258722864.png")
> system("convert tmp/98oyk1258722864.ps tmp/98oyk1258722864.png")
> system("convert tmp/10q83o1258722864.ps tmp/10q83o1258722864.png")
>
>
> proc.time()
user system elapsed
4.375 1.702 4.787