R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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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(998
+ ,1.2
+ ,613
+ ,-1906
+ ,-2.3
+ ,-0.6
+ ,499
+ ,2.3
+ ,998
+ ,-706
+ ,1.2
+ ,-1.1
+ ,59
+ ,1.3
+ ,499
+ ,326
+ ,2.3
+ ,-0.6
+ ,175
+ ,1.4
+ ,59
+ ,146
+ ,1.3
+ ,-2
+ ,-413
+ ,-1.5
+ ,175
+ ,625
+ ,1.4
+ ,0
+ ,-223
+ ,1.4
+ ,-413
+ ,104
+ ,-1.5
+ ,-1.1
+ ,110
+ ,-0.9
+ ,-223
+ ,65
+ ,1.4
+ ,3.4
+ ,13
+ ,-0.6
+ ,110
+ ,25
+ ,-0.9
+ ,0.8
+ ,74
+ ,1.8
+ ,13
+ ,3
+ ,-0.6
+ ,-3.2
+ ,643
+ ,-3.9
+ ,74
+ ,-393
+ ,1.8
+ ,3.1
+ ,44
+ ,2.4
+ ,643
+ ,-358
+ ,-3.9
+ ,-1.7
+ ,216
+ ,1.1
+ ,44
+ ,613
+ ,2.4
+ ,-2.3
+ ,-1189
+ ,-2.3
+ ,216
+ ,998
+ ,1.1
+ ,1.2
+ ,-47
+ ,-4.3
+ ,-1189
+ ,499
+ ,-2.3
+ ,2.3
+ ,279
+ ,1
+ ,-47
+ ,59
+ ,-4.3
+ ,1.3
+ ,374
+ ,0.8
+ ,279
+ ,175
+ ,1
+ ,1.4
+ ,13
+ ,0.3
+ ,374
+ ,-413
+ ,0.8
+ ,-1.5
+ ,152
+ ,2.2
+ ,13
+ ,-223
+ ,0.3
+ ,1.4
+ ,-27
+ ,1.7
+ ,152
+ ,110
+ ,2.2
+ ,-0.9
+ ,334
+ ,1.8
+ ,-27
+ ,13
+ ,1.7
+ ,-0.6
+ ,411
+ ,0.6
+ ,334
+ ,74
+ ,1.8
+ ,1.8
+ ,33
+ ,-2.6
+ ,411
+ ,643
+ ,0.6
+ ,-3.9
+ ,313
+ ,-0.3
+ ,33
+ ,44
+ ,-2.6
+ ,2.4
+ ,751
+ ,0.1
+ ,313
+ ,216
+ ,-0.3
+ ,1.1
+ ,446
+ ,0.9
+ ,751
+ ,-1189
+ ,0.1
+ ,-2.3
+ ,-329
+ ,2.2
+ ,446
+ ,-47
+ ,0.9
+ ,-4.3
+ ,-560
+ ,-2.2
+ ,-329
+ ,279
+ ,2.2
+ ,1
+ ,-783
+ ,0.4
+ ,-560
+ ,374
+ ,-2.2
+ ,0.8
+ ,-371
+ ,-1.1
+ ,-783
+ ,13
+ ,0.4
+ ,0.3
+ ,-308
+ ,-3
+ ,-371
+ ,152
+ ,-1.1
+ ,2.2
+ ,-264
+ ,-2.1
+ ,-308
+ ,-27
+ ,-3
+ ,1.7
+ ,-787
+ ,-1.5
+ ,-264
+ ,334
+ ,-2.1
+ ,1.8
+ ,-486
+ ,0.5
+ ,-787
+ ,411
+ ,-1.5
+ ,0.6
+ ,-243
+ ,3.8
+ ,-486
+ ,33
+ ,0.5
+ ,-2.6
+ ,-416
+ ,-1.9
+ ,-243
+ ,313
+ ,3.8
+ ,-0.3
+ ,-992
+ ,-1.6
+ ,-416
+ ,751
+ ,-1.9
+ ,0.1
+ ,-316
+ ,1.5
+ ,-992
+ ,446
+ ,-1.6
+ ,0.9
+ ,825
+ ,-2.6
+ ,-316
+ ,-329
+ ,1.5
+ ,2.2
+ ,1513
+ ,0.6
+ ,825
+ ,-560
+ ,-2.6
+ ,-2.2
+ ,138
+ ,-0.4
+ ,1513
+ ,-783
+ ,0.6
+ ,0.4
+ ,363
+ ,0.6
+ ,138
+ ,-371
+ ,-0.4
+ ,-1.1
+ ,180
+ ,2
+ ,363
+ ,-308
+ ,0.6
+ ,-3
+ ,-493
+ ,1
+ ,180
+ ,-264
+ ,2
+ ,-2.1
+ ,-325
+ ,-2.1
+ ,-493
+ ,-787
+ ,1
+ ,-1.5
+ ,-225
+ ,0.8
+ ,-325
+ ,-486
+ ,-2.1
+ ,0.5
+ ,-115
+ ,2.4
+ ,-225
+ ,-243
+ ,0.8
+ ,3.8
+ ,-145
+ ,-0.3
+ ,-115
+ ,-416
+ ,2.4
+ ,-1.9
+ ,-68
+ ,0.6
+ ,-145
+ ,-992
+ ,-0.3
+ ,-1.6
+ ,-335
+ ,-3
+ ,-68
+ ,-316
+ ,0.6
+ ,1.5
+ ,-832
+ ,-0.1
+ ,-335
+ ,825
+ ,-3
+ ,-2.6
+ ,-931
+ ,-2.7
+ ,-832
+ ,1513
+ ,-0.1
+ ,0.6
+ ,-149
+ ,-1.4
+ ,-931
+ ,138
+ ,-2.7
+ ,-0.4
+ ,-251
+ ,0.8
+ ,-149
+ ,363
+ ,-1.4
+ ,0.6
+ ,-43
+ ,-1
+ ,-251
+ ,180
+ ,0.8
+ ,2
+ ,1484
+ ,4.6
+ ,-43
+ ,-493
+ ,-1
+ ,1
+ ,195
+ ,-0.5
+ ,1484
+ ,-325
+ ,4.6
+ ,-2.1
+ ,170
+ ,1.8
+ ,195
+ ,-225
+ ,-0.5
+ ,0.8
+ ,-277
+ ,0.1
+ ,170
+ ,-115
+ ,1.8
+ ,2.4
+ ,-57
+ ,3
+ ,-277
+ ,-145
+ ,0.1
+ ,-0.3
+ ,-665
+ ,2.4
+ ,-57
+ ,-68
+ ,3
+ ,0.6
+ ,-220
+ ,5.5
+ ,-665
+ ,-335
+ ,2.4
+ ,-3
+ ,534
+ ,4.5
+ ,-220
+ ,-832
+ ,5.5
+ ,-0.1
+ ,-449
+ ,3.5
+ ,534
+ ,-931
+ ,4.5
+ ,-2.7
+ ,158
+ ,5
+ ,-449
+ ,-149
+ ,3.5
+ ,-1.4
+ ,-261
+ ,0.4
+ ,158
+ ,-251
+ ,5
+ ,0.8
+ ,-300
+ ,0.2
+ ,-261
+ ,-43
+ ,0.4
+ ,-1
+ ,-1276
+ ,-5.8
+ ,-300
+ ,1484
+ ,0.2
+ ,4.6
+ ,-108
+ ,0.9
+ ,-1276
+ ,195
+ ,-5.8
+ ,-0.5
+ ,-29
+ ,-4.3
+ ,-108
+ ,170
+ ,0.9
+ ,1.8
+ ,305
+ ,-3.8
+ ,-29
+ ,-277
+ ,-4.3
+ ,0.1
+ ,805
+ ,-2.3
+ ,305
+ ,-57
+ ,-3.8
+ ,3
+ ,-88
+ ,-1.8
+ ,805
+ ,-665
+ ,-2.3
+ ,2.4)
+ ,dim=c(6
+ ,72)
+ ,dimnames=list(c('N12S'
+ ,'N12T'
+ ,'N12S1'
+ ,'N12S12'
+ ,'N12T1'
+ ,'N12T12')
+ ,1:72))
> y <- array(NA,dim=c(6,72),dimnames=list(c('N12S','N12T','N12S1','N12S12','N12T1','N12T12'),1:72))
> 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
> 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
N12S N12T N12S1 N12S12 N12T1 N12T12
1 998 1.2 613 -1906 -2.3 -0.6
2 499 2.3 998 -706 1.2 -1.1
3 59 1.3 499 326 2.3 -0.6
4 175 1.4 59 146 1.3 -2.0
5 -413 -1.5 175 625 1.4 0.0
6 -223 1.4 -413 104 -1.5 -1.1
7 110 -0.9 -223 65 1.4 3.4
8 13 -0.6 110 25 -0.9 0.8
9 74 1.8 13 3 -0.6 -3.2
10 643 -3.9 74 -393 1.8 3.1
11 44 2.4 643 -358 -3.9 -1.7
12 216 1.1 44 613 2.4 -2.3
13 -1189 -2.3 216 998 1.1 1.2
14 -47 -4.3 -1189 499 -2.3 2.3
15 279 1.0 -47 59 -4.3 1.3
16 374 0.8 279 175 1.0 1.4
17 13 0.3 374 -413 0.8 -1.5
18 152 2.2 13 -223 0.3 1.4
19 -27 1.7 152 110 2.2 -0.9
20 334 1.8 -27 13 1.7 -0.6
21 411 0.6 334 74 1.8 1.8
22 33 -2.6 411 643 0.6 -3.9
23 313 -0.3 33 44 -2.6 2.4
24 751 0.1 313 216 -0.3 1.1
25 446 0.9 751 -1189 0.1 -2.3
26 -329 2.2 446 -47 0.9 -4.3
27 -560 -2.2 -329 279 2.2 1.0
28 -783 0.4 -560 374 -2.2 0.8
29 -371 -1.1 -783 13 0.4 0.3
30 -308 -3.0 -371 152 -1.1 2.2
31 -264 -2.1 -308 -27 -3.0 1.7
32 -787 -1.5 -264 334 -2.1 1.8
33 -486 0.5 -787 411 -1.5 0.6
34 -243 3.8 -486 33 0.5 -2.6
35 -416 -1.9 -243 313 3.8 -0.3
36 -992 -1.6 -416 751 -1.9 0.1
37 -316 1.5 -992 446 -1.6 0.9
38 825 -2.6 -316 -329 1.5 2.2
39 1513 0.6 825 -560 -2.6 -2.2
40 138 -0.4 1513 -783 0.6 0.4
41 363 0.6 138 -371 -0.4 -1.1
42 180 2.0 363 -308 0.6 -3.0
43 -493 1.0 180 -264 2.0 -2.1
44 -325 -2.1 -493 -787 1.0 -1.5
45 -225 0.8 -325 -486 -2.1 0.5
46 -115 2.4 -225 -243 0.8 3.8
47 -145 -0.3 -115 -416 2.4 -1.9
48 -68 0.6 -145 -992 -0.3 -1.6
49 -335 -3.0 -68 -316 0.6 1.5
50 -832 -0.1 -335 825 -3.0 -2.6
51 -931 -2.7 -832 1513 -0.1 0.6
52 -149 -1.4 -931 138 -2.7 -0.4
53 -251 0.8 -149 363 -1.4 0.6
54 -43 -1.0 -251 180 0.8 2.0
55 1484 4.6 -43 -493 -1.0 1.0
56 195 -0.5 1484 -325 4.6 -2.1
57 170 1.8 195 -225 -0.5 0.8
58 -277 0.1 170 -115 1.8 2.4
59 -57 3.0 -277 -145 0.1 -0.3
60 -665 2.4 -57 -68 3.0 0.6
61 -220 5.5 -665 -335 2.4 -3.0
62 534 4.5 -220 -832 5.5 -0.1
63 -449 3.5 534 -931 4.5 -2.7
64 158 5.0 -449 -149 3.5 -1.4
65 -261 0.4 158 -251 5.0 0.8
66 -300 0.2 -261 -43 0.4 -1.0
67 -1276 -5.8 -300 1484 0.2 4.6
68 -108 0.9 -1276 195 -5.8 -0.5
69 -29 -4.3 -108 170 0.9 1.8
70 305 -3.8 -29 -277 -4.3 0.1
71 805 -2.3 305 -57 -3.8 3.0
72 -88 -1.8 805 -665 -2.3 2.4
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) N12T N12S1 N12S12 N12T1 N12T12
-52.4101 42.7706 0.2566 -0.4187 -41.6357 45.5257
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-762.9 -272.6 -31.2 198.6 1085.5
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -52.4101 49.7702 -1.053 0.296162
N12T 42.7706 26.4564 1.617 0.110725
N12S1 0.2566 0.1092 2.350 0.021761 *
N12S12 -0.4187 0.1084 -3.864 0.000257 ***
N12T1 -41.6357 22.5496 -1.846 0.069318 .
N12T12 45.5257 29.6872 1.534 0.129929
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 417.3 on 66 degrees of freedom
Multiple R-squared: 0.4084, Adjusted R-squared: 0.3635
F-statistic: 9.111 on 5 and 66 DF, p-value: 1.260e-06
> 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,] 0.03680609 0.07361218 0.9631939
[2,] 0.01662367 0.03324733 0.9833763
[3,] 0.01203873 0.02407746 0.9879613
[4,] 0.01709981 0.03419962 0.9829002
[5,] 0.09251275 0.18502550 0.9074873
[6,] 0.08289730 0.16579460 0.9171027
[7,] 0.14307612 0.28615224 0.8569239
[8,] 0.11751966 0.23503932 0.8824803
[9,] 0.09355604 0.18711207 0.9064440
[10,] 0.09092417 0.18184834 0.9090758
[11,] 0.06423244 0.12846488 0.9357676
[12,] 0.04391291 0.08782582 0.9560871
[13,] 0.03554838 0.07109676 0.9644516
[14,] 0.06293645 0.12587289 0.9370636
[15,] 0.05247517 0.10495033 0.9475248
[16,] 0.16214559 0.32429118 0.8378544
[17,] 0.12899470 0.25798940 0.8710053
[18,] 0.11799210 0.23598421 0.8820079
[19,] 0.14306897 0.28613793 0.8569310
[20,] 0.21815737 0.43631474 0.7818426
[21,] 0.18061513 0.36123026 0.8193849
[22,] 0.14559917 0.29119834 0.8544008
[23,] 0.11875611 0.23751222 0.8812439
[24,] 0.16716341 0.33432682 0.8328366
[25,] 0.12893424 0.25786848 0.8710658
[26,] 0.09486349 0.18972697 0.9051365
[27,] 0.07834045 0.15668090 0.9216596
[28,] 0.08430265 0.16860529 0.9156974
[29,] 0.06042631 0.12085262 0.9395737
[30,] 0.17379842 0.34759684 0.8262016
[31,] 0.58609809 0.82780381 0.4139019
[32,] 0.63341848 0.73316305 0.3665815
[33,] 0.59011558 0.81976883 0.4098844
[34,] 0.52982098 0.94035804 0.4701790
[35,] 0.54509510 0.90980981 0.4549049
[36,] 0.50487738 0.99024525 0.4951226
[37,] 0.51306844 0.97386311 0.4869316
[38,] 0.51990497 0.96019006 0.4800950
[39,] 0.45889937 0.91779874 0.5411006
[40,] 0.42397529 0.84795058 0.5760247
[41,] 0.38459180 0.76918359 0.6154082
[42,] 0.33366982 0.66733964 0.6663302
[43,] 0.27668759 0.55337517 0.7233124
[44,] 0.22114057 0.44228113 0.7788594
[45,] 0.16652625 0.33305250 0.8334738
[46,] 0.12361996 0.24723992 0.8763800
[47,] 0.42848149 0.85696297 0.5715185
[48,] 0.59634382 0.80731236 0.4036562
[49,] 0.53434417 0.93131166 0.4656558
[50,] 0.47582006 0.95164013 0.5241799
[51,] 0.36954957 0.73909913 0.6304504
[52,] 0.38198059 0.76396117 0.6180194
[53,] 0.26781641 0.53563282 0.7321836
[54,] 0.16927408 0.33854815 0.8307259
[55,] 0.14830219 0.29660438 0.8516978
> postscript(file="/var/www/rcomp/tmp/1u5fk1292407417.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2u5fk1292407417.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/rcomp/tmp/35ew51292407417.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/45ew51292407417.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/55ew51292407417.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 = 72
Frequency = 1
1 2 3 4 5 6
-24.7557700 1.3791951 187.3563355 358.7056941 -21.3380879 -93.3253690
7 8 9 10 11 12
188.8426051 -0.5765464 168.0445325 612.4800036 -406.1169282 671.3913981
13 14 15 16 17 18
-684.5755703 502.8820603 87.1872510 371.7839713 -114.7244530 -37.6438408
19 20 21 22 23 24
92.3313582 419.8905645 376.0319782 562.9341237 170.6834723 746.6987999
25 26 27 28 29 30
-121.7818929 -271.5705610 -166.1780145 -575.4223182 -62.1947418 -114.3928906
31 32 33 34 35 36
-256.3497473 -632.2194229 -170.7108667 -75.4139695 82.9619305 -533.6082433
37 38 39 40 41 42
5.9532256 894.2285102 1085.4764133 -501.7949811 232.4125041 86.3165362
43 44 45 46 47 48
-461.2163648 -275.8936139 -437.1182538 -348.9489136 -38.0199042 -359.0807039
49 50 51 52 53 54
-312.4573673 -350.4411248 52.4361231 165.7502838 -128.1800641 134.2130982
55 56 57 58 59 60
1057.1013316 39.0604668 -56.0650003 -354.9586408 -104.7222746 -631.4960801
61 62 63 64 65 66
-135.9708071 335.5540180 -762.8652621 258.8343348 -199.5830585 -145.0004283
67 68 69 70 71 72
-478.2347881 96.2500318 261.7455061 227.8038303 558.8626011 -648.6372233
> postscript(file="/var/www/rcomp/tmp/6ynv81292407417.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 = 72
Frequency = 1
lag(myerror, k = 1) myerror
0 -24.7557700 NA
1 1.3791951 -24.7557700
2 187.3563355 1.3791951
3 358.7056941 187.3563355
4 -21.3380879 358.7056941
5 -93.3253690 -21.3380879
6 188.8426051 -93.3253690
7 -0.5765464 188.8426051
8 168.0445325 -0.5765464
9 612.4800036 168.0445325
10 -406.1169282 612.4800036
11 671.3913981 -406.1169282
12 -684.5755703 671.3913981
13 502.8820603 -684.5755703
14 87.1872510 502.8820603
15 371.7839713 87.1872510
16 -114.7244530 371.7839713
17 -37.6438408 -114.7244530
18 92.3313582 -37.6438408
19 419.8905645 92.3313582
20 376.0319782 419.8905645
21 562.9341237 376.0319782
22 170.6834723 562.9341237
23 746.6987999 170.6834723
24 -121.7818929 746.6987999
25 -271.5705610 -121.7818929
26 -166.1780145 -271.5705610
27 -575.4223182 -166.1780145
28 -62.1947418 -575.4223182
29 -114.3928906 -62.1947418
30 -256.3497473 -114.3928906
31 -632.2194229 -256.3497473
32 -170.7108667 -632.2194229
33 -75.4139695 -170.7108667
34 82.9619305 -75.4139695
35 -533.6082433 82.9619305
36 5.9532256 -533.6082433
37 894.2285102 5.9532256
38 1085.4764133 894.2285102
39 -501.7949811 1085.4764133
40 232.4125041 -501.7949811
41 86.3165362 232.4125041
42 -461.2163648 86.3165362
43 -275.8936139 -461.2163648
44 -437.1182538 -275.8936139
45 -348.9489136 -437.1182538
46 -38.0199042 -348.9489136
47 -359.0807039 -38.0199042
48 -312.4573673 -359.0807039
49 -350.4411248 -312.4573673
50 52.4361231 -350.4411248
51 165.7502838 52.4361231
52 -128.1800641 165.7502838
53 134.2130982 -128.1800641
54 1057.1013316 134.2130982
55 39.0604668 1057.1013316
56 -56.0650003 39.0604668
57 -354.9586408 -56.0650003
58 -104.7222746 -354.9586408
59 -631.4960801 -104.7222746
60 -135.9708071 -631.4960801
61 335.5540180 -135.9708071
62 -762.8652621 335.5540180
63 258.8343348 -762.8652621
64 -199.5830585 258.8343348
65 -145.0004283 -199.5830585
66 -478.2347881 -145.0004283
67 96.2500318 -478.2347881
68 261.7455061 96.2500318
69 227.8038303 261.7455061
70 558.8626011 227.8038303
71 -648.6372233 558.8626011
72 NA -648.6372233
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.3791951 -24.7557700
[2,] 187.3563355 1.3791951
[3,] 358.7056941 187.3563355
[4,] -21.3380879 358.7056941
[5,] -93.3253690 -21.3380879
[6,] 188.8426051 -93.3253690
[7,] -0.5765464 188.8426051
[8,] 168.0445325 -0.5765464
[9,] 612.4800036 168.0445325
[10,] -406.1169282 612.4800036
[11,] 671.3913981 -406.1169282
[12,] -684.5755703 671.3913981
[13,] 502.8820603 -684.5755703
[14,] 87.1872510 502.8820603
[15,] 371.7839713 87.1872510
[16,] -114.7244530 371.7839713
[17,] -37.6438408 -114.7244530
[18,] 92.3313582 -37.6438408
[19,] 419.8905645 92.3313582
[20,] 376.0319782 419.8905645
[21,] 562.9341237 376.0319782
[22,] 170.6834723 562.9341237
[23,] 746.6987999 170.6834723
[24,] -121.7818929 746.6987999
[25,] -271.5705610 -121.7818929
[26,] -166.1780145 -271.5705610
[27,] -575.4223182 -166.1780145
[28,] -62.1947418 -575.4223182
[29,] -114.3928906 -62.1947418
[30,] -256.3497473 -114.3928906
[31,] -632.2194229 -256.3497473
[32,] -170.7108667 -632.2194229
[33,] -75.4139695 -170.7108667
[34,] 82.9619305 -75.4139695
[35,] -533.6082433 82.9619305
[36,] 5.9532256 -533.6082433
[37,] 894.2285102 5.9532256
[38,] 1085.4764133 894.2285102
[39,] -501.7949811 1085.4764133
[40,] 232.4125041 -501.7949811
[41,] 86.3165362 232.4125041
[42,] -461.2163648 86.3165362
[43,] -275.8936139 -461.2163648
[44,] -437.1182538 -275.8936139
[45,] -348.9489136 -437.1182538
[46,] -38.0199042 -348.9489136
[47,] -359.0807039 -38.0199042
[48,] -312.4573673 -359.0807039
[49,] -350.4411248 -312.4573673
[50,] 52.4361231 -350.4411248
[51,] 165.7502838 52.4361231
[52,] -128.1800641 165.7502838
[53,] 134.2130982 -128.1800641
[54,] 1057.1013316 134.2130982
[55,] 39.0604668 1057.1013316
[56,] -56.0650003 39.0604668
[57,] -354.9586408 -56.0650003
[58,] -104.7222746 -354.9586408
[59,] -631.4960801 -104.7222746
[60,] -135.9708071 -631.4960801
[61,] 335.5540180 -135.9708071
[62,] -762.8652621 335.5540180
[63,] 258.8343348 -762.8652621
[64,] -199.5830585 258.8343348
[65,] -145.0004283 -199.5830585
[66,] -478.2347881 -145.0004283
[67,] 96.2500318 -478.2347881
[68,] 261.7455061 96.2500318
[69,] 227.8038303 261.7455061
[70,] 558.8626011 227.8038303
[71,] -648.6372233 558.8626011
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.3791951 -24.7557700
2 187.3563355 1.3791951
3 358.7056941 187.3563355
4 -21.3380879 358.7056941
5 -93.3253690 -21.3380879
6 188.8426051 -93.3253690
7 -0.5765464 188.8426051
8 168.0445325 -0.5765464
9 612.4800036 168.0445325
10 -406.1169282 612.4800036
11 671.3913981 -406.1169282
12 -684.5755703 671.3913981
13 502.8820603 -684.5755703
14 87.1872510 502.8820603
15 371.7839713 87.1872510
16 -114.7244530 371.7839713
17 -37.6438408 -114.7244530
18 92.3313582 -37.6438408
19 419.8905645 92.3313582
20 376.0319782 419.8905645
21 562.9341237 376.0319782
22 170.6834723 562.9341237
23 746.6987999 170.6834723
24 -121.7818929 746.6987999
25 -271.5705610 -121.7818929
26 -166.1780145 -271.5705610
27 -575.4223182 -166.1780145
28 -62.1947418 -575.4223182
29 -114.3928906 -62.1947418
30 -256.3497473 -114.3928906
31 -632.2194229 -256.3497473
32 -170.7108667 -632.2194229
33 -75.4139695 -170.7108667
34 82.9619305 -75.4139695
35 -533.6082433 82.9619305
36 5.9532256 -533.6082433
37 894.2285102 5.9532256
38 1085.4764133 894.2285102
39 -501.7949811 1085.4764133
40 232.4125041 -501.7949811
41 86.3165362 232.4125041
42 -461.2163648 86.3165362
43 -275.8936139 -461.2163648
44 -437.1182538 -275.8936139
45 -348.9489136 -437.1182538
46 -38.0199042 -348.9489136
47 -359.0807039 -38.0199042
48 -312.4573673 -359.0807039
49 -350.4411248 -312.4573673
50 52.4361231 -350.4411248
51 165.7502838 52.4361231
52 -128.1800641 165.7502838
53 134.2130982 -128.1800641
54 1057.1013316 134.2130982
55 39.0604668 1057.1013316
56 -56.0650003 39.0604668
57 -354.9586408 -56.0650003
58 -104.7222746 -354.9586408
59 -631.4960801 -104.7222746
60 -135.9708071 -631.4960801
61 335.5540180 -135.9708071
62 -762.8652621 335.5540180
63 258.8343348 -762.8652621
64 -199.5830585 258.8343348
65 -145.0004283 -199.5830585
66 -478.2347881 -145.0004283
67 96.2500318 -478.2347881
68 261.7455061 96.2500318
69 227.8038303 261.7455061
70 558.8626011 227.8038303
71 -648.6372233 558.8626011
> 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/rcomp/tmp/7qxdt1292407417.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8qxdt1292407417.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9qxdt1292407417.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10j6uw1292407417.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/1157tk1292407417.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/rcomp/tmp/12q7981292407417.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/rcomp/tmp/134z7h1292407417.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/rcomp/tmp/14ph551292407417.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/rcomp/tmp/15t04a1292407417.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/rcomp/tmp/16jl9n1292407417.tab")
+ }
>
> try(system("convert tmp/1u5fk1292407417.ps tmp/1u5fk1292407417.png",intern=TRUE))
character(0)
> try(system("convert tmp/2u5fk1292407417.ps tmp/2u5fk1292407417.png",intern=TRUE))
character(0)
> try(system("convert tmp/35ew51292407417.ps tmp/35ew51292407417.png",intern=TRUE))
character(0)
> try(system("convert tmp/45ew51292407417.ps tmp/45ew51292407417.png",intern=TRUE))
character(0)
> try(system("convert tmp/55ew51292407417.ps tmp/55ew51292407417.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ynv81292407417.ps tmp/6ynv81292407417.png",intern=TRUE))
character(0)
> try(system("convert tmp/7qxdt1292407417.ps tmp/7qxdt1292407417.png",intern=TRUE))
character(0)
> try(system("convert tmp/8qxdt1292407417.ps tmp/8qxdt1292407417.png",intern=TRUE))
character(0)
> try(system("convert tmp/9qxdt1292407417.ps tmp/9qxdt1292407417.png",intern=TRUE))
character(0)
> try(system("convert tmp/10j6uw1292407417.ps tmp/10j6uw1292407417.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.200 1.730 4.905