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(286602
+ ,326011
+ ,277915
+ ,276687
+ ,283042
+ ,286602
+ ,283042
+ ,328282
+ ,286602
+ ,277915
+ ,276687
+ ,283042
+ ,276687
+ ,317480
+ ,283042
+ ,286602
+ ,277915
+ ,276687
+ ,277915
+ ,317539
+ ,276687
+ ,283042
+ ,286602
+ ,277915
+ ,277128
+ ,313737
+ ,277915
+ ,276687
+ ,283042
+ ,286602
+ ,277103
+ ,312276
+ ,277128
+ ,277915
+ ,276687
+ ,283042
+ ,275037
+ ,309391
+ ,277103
+ ,277128
+ ,277915
+ ,276687
+ ,270150
+ ,302950
+ ,275037
+ ,277103
+ ,277128
+ ,277915
+ ,267140
+ ,300316
+ ,270150
+ ,275037
+ ,277103
+ ,277128
+ ,264993
+ ,304035
+ ,267140
+ ,270150
+ ,275037
+ ,277103
+ ,287259
+ ,333476
+ ,264993
+ ,267140
+ ,270150
+ ,275037
+ ,291186
+ ,337698
+ ,287259
+ ,264993
+ ,267140
+ ,270150
+ ,292300
+ ,335932
+ ,291186
+ ,287259
+ ,264993
+ ,267140
+ ,288186
+ ,323931
+ ,292300
+ ,291186
+ ,287259
+ ,264993
+ ,281477
+ ,313927
+ ,288186
+ ,292300
+ ,291186
+ ,287259
+ ,282656
+ ,314485
+ ,281477
+ ,288186
+ ,292300
+ ,291186
+ ,280190
+ ,313218
+ ,282656
+ ,281477
+ ,288186
+ ,292300
+ ,280408
+ ,309664
+ ,280190
+ ,282656
+ ,281477
+ ,288186
+ ,276836
+ ,302963
+ ,280408
+ ,280190
+ ,282656
+ ,281477
+ ,275216
+ ,298989
+ ,276836
+ ,280408
+ ,280190
+ ,282656
+ ,274352
+ ,298423
+ ,275216
+ ,276836
+ ,280408
+ ,280190
+ ,271311
+ ,301631
+ ,274352
+ ,275216
+ ,276836
+ ,280408
+ ,289802
+ ,329765
+ ,271311
+ ,274352
+ ,275216
+ ,276836
+ ,290726
+ ,335083
+ ,289802
+ ,271311
+ ,274352
+ ,275216
+ ,292300
+ ,327616
+ ,290726
+ ,289802
+ ,271311
+ ,274352
+ ,278506
+ ,309119
+ ,292300
+ ,290726
+ ,289802
+ ,271311
+ ,269826
+ ,295916
+ ,278506
+ ,292300
+ ,290726
+ ,289802
+ ,265861
+ ,291413
+ ,269826
+ ,278506
+ ,292300
+ ,290726
+ ,269034
+ ,291542
+ ,265861
+ ,269826
+ ,278506
+ ,292300
+ ,264176
+ ,284678
+ ,269034
+ ,265861
+ ,269826
+ ,278506
+ ,255198
+ ,276475
+ ,264176
+ ,269034
+ ,265861
+ ,269826
+ ,253353
+ ,272566
+ ,255198
+ ,264176
+ ,269034
+ ,265861
+ ,246057
+ ,264981
+ ,253353
+ ,255198
+ ,264176
+ ,269034
+ ,235372
+ ,263290
+ ,246057
+ ,253353
+ ,255198
+ ,264176
+ ,258556
+ ,296806
+ ,235372
+ ,246057
+ ,253353
+ ,255198
+ ,260993
+ ,303598
+ ,258556
+ ,235372
+ ,246057
+ ,253353
+ ,254663
+ ,286994
+ ,260993
+ ,258556
+ ,235372
+ ,246057
+ ,250643
+ ,276427
+ ,254663
+ ,260993
+ ,258556
+ ,235372
+ ,243422
+ ,266424
+ ,250643
+ ,254663
+ ,260993
+ ,258556
+ ,247105
+ ,267153
+ ,243422
+ ,250643
+ ,254663
+ ,260993
+ ,248541
+ ,268381
+ ,247105
+ ,243422
+ ,250643
+ ,254663
+ ,245039
+ ,262522
+ ,248541
+ ,247105
+ ,243422
+ ,250643
+ ,237080
+ ,255542
+ ,245039
+ ,248541
+ ,247105
+ ,243422
+ ,237085
+ ,253158
+ ,237080
+ ,245039
+ ,248541
+ ,247105
+ ,225554
+ ,243803
+ ,237085
+ ,237080
+ ,245039
+ ,248541
+ ,226839
+ ,250741
+ ,225554
+ ,237085
+ ,237080
+ ,245039
+ ,247934
+ ,280445
+ ,226839
+ ,225554
+ ,237085
+ ,237080
+ ,248333
+ ,285257
+ ,247934
+ ,226839
+ ,225554
+ ,237085
+ ,246969
+ ,270976
+ ,248333
+ ,247934
+ ,226839
+ ,225554
+ ,245098
+ ,261076
+ ,246969
+ ,248333
+ ,247934
+ ,226839
+ ,246263
+ ,255603
+ ,245098
+ ,246969
+ ,248333
+ ,247934
+ ,255765
+ ,260376
+ ,246263
+ ,245098
+ ,246969
+ ,248333
+ ,264319
+ ,263903
+ ,255765
+ ,246263
+ ,245098
+ ,246969
+ ,268347
+ ,264291
+ ,264319
+ ,255765
+ ,246263
+ ,245098
+ ,273046
+ ,263276
+ ,268347
+ ,264319
+ ,255765
+ ,246263
+ ,273963
+ ,262572
+ ,273046
+ ,268347
+ ,264319
+ ,255765
+ ,267430
+ ,256167
+ ,273963
+ ,273046
+ ,268347
+ ,264319
+ ,271993
+ ,264221
+ ,267430
+ ,273963
+ ,273046
+ ,268347
+ ,292710
+ ,293860
+ ,271993
+ ,267430
+ ,273963
+ ,273046
+ ,295881
+ ,300713
+ ,292710
+ ,271993
+ ,267430
+ ,273963
+ ,293299
+ ,287224
+ ,295881
+ ,292710
+ ,271993
+ ,267430)
+ ,dim=c(6
+ ,61)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:61))
> y <- array(NA,dim=c(6,61),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:61))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Include Monthly 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 Y1 Y2 Y3 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 286602 326011 277915 276687 283042 286602 1 0 0 0 0 0 0 0 0 0 0
2 283042 328282 286602 277915 276687 283042 0 1 0 0 0 0 0 0 0 0 0
3 276687 317480 283042 286602 277915 276687 0 0 1 0 0 0 0 0 0 0 0
4 277915 317539 276687 283042 286602 277915 0 0 0 1 0 0 0 0 0 0 0
5 277128 313737 277915 276687 283042 286602 0 0 0 0 1 0 0 0 0 0 0
6 277103 312276 277128 277915 276687 283042 0 0 0 0 0 1 0 0 0 0 0
7 275037 309391 277103 277128 277915 276687 0 0 0 0 0 0 1 0 0 0 0
8 270150 302950 275037 277103 277128 277915 0 0 0 0 0 0 0 1 0 0 0
9 267140 300316 270150 275037 277103 277128 0 0 0 0 0 0 0 0 1 0 0
10 264993 304035 267140 270150 275037 277103 0 0 0 0 0 0 0 0 0 1 0
11 287259 333476 264993 267140 270150 275037 0 0 0 0 0 0 0 0 0 0 1
12 291186 337698 287259 264993 267140 270150 0 0 0 0 0 0 0 0 0 0 0
13 292300 335932 291186 287259 264993 267140 1 0 0 0 0 0 0 0 0 0 0
14 288186 323931 292300 291186 287259 264993 0 1 0 0 0 0 0 0 0 0 0
15 281477 313927 288186 292300 291186 287259 0 0 1 0 0 0 0 0 0 0 0
16 282656 314485 281477 288186 292300 291186 0 0 0 1 0 0 0 0 0 0 0
17 280190 313218 282656 281477 288186 292300 0 0 0 0 1 0 0 0 0 0 0
18 280408 309664 280190 282656 281477 288186 0 0 0 0 0 1 0 0 0 0 0
19 276836 302963 280408 280190 282656 281477 0 0 0 0 0 0 1 0 0 0 0
20 275216 298989 276836 280408 280190 282656 0 0 0 0 0 0 0 1 0 0 0
21 274352 298423 275216 276836 280408 280190 0 0 0 0 0 0 0 0 1 0 0
22 271311 301631 274352 275216 276836 280408 0 0 0 0 0 0 0 0 0 1 0
23 289802 329765 271311 274352 275216 276836 0 0 0 0 0 0 0 0 0 0 1
24 290726 335083 289802 271311 274352 275216 0 0 0 0 0 0 0 0 0 0 0
25 292300 327616 290726 289802 271311 274352 1 0 0 0 0 0 0 0 0 0 0
26 278506 309119 292300 290726 289802 271311 0 1 0 0 0 0 0 0 0 0 0
27 269826 295916 278506 292300 290726 289802 0 0 1 0 0 0 0 0 0 0 0
28 265861 291413 269826 278506 292300 290726 0 0 0 1 0 0 0 0 0 0 0
29 269034 291542 265861 269826 278506 292300 0 0 0 0 1 0 0 0 0 0 0
30 264176 284678 269034 265861 269826 278506 0 0 0 0 0 1 0 0 0 0 0
31 255198 276475 264176 269034 265861 269826 0 0 0 0 0 0 1 0 0 0 0
32 253353 272566 255198 264176 269034 265861 0 0 0 0 0 0 0 1 0 0 0
33 246057 264981 253353 255198 264176 269034 0 0 0 0 0 0 0 0 1 0 0
34 235372 263290 246057 253353 255198 264176 0 0 0 0 0 0 0 0 0 1 0
35 258556 296806 235372 246057 253353 255198 0 0 0 0 0 0 0 0 0 0 1
36 260993 303598 258556 235372 246057 253353 0 0 0 0 0 0 0 0 0 0 0
37 254663 286994 260993 258556 235372 246057 1 0 0 0 0 0 0 0 0 0 0
38 250643 276427 254663 260993 258556 235372 0 1 0 0 0 0 0 0 0 0 0
39 243422 266424 250643 254663 260993 258556 0 0 1 0 0 0 0 0 0 0 0
40 247105 267153 243422 250643 254663 260993 0 0 0 1 0 0 0 0 0 0 0
41 248541 268381 247105 243422 250643 254663 0 0 0 0 1 0 0 0 0 0 0
42 245039 262522 248541 247105 243422 250643 0 0 0 0 0 1 0 0 0 0 0
43 237080 255542 245039 248541 247105 243422 0 0 0 0 0 0 1 0 0 0 0
44 237085 253158 237080 245039 248541 247105 0 0 0 0 0 0 0 1 0 0 0
45 225554 243803 237085 237080 245039 248541 0 0 0 0 0 0 0 0 1 0 0
46 226839 250741 225554 237085 237080 245039 0 0 0 0 0 0 0 0 0 1 0
47 247934 280445 226839 225554 237085 237080 0 0 0 0 0 0 0 0 0 0 1
48 248333 285257 247934 226839 225554 237085 0 0 0 0 0 0 0 0 0 0 0
49 246969 270976 248333 247934 226839 225554 1 0 0 0 0 0 0 0 0 0 0
50 245098 261076 246969 248333 247934 226839 0 1 0 0 0 0 0 0 0 0 0
51 246263 255603 245098 246969 248333 247934 0 0 1 0 0 0 0 0 0 0 0
52 255765 260376 246263 245098 246969 248333 0 0 0 1 0 0 0 0 0 0 0
53 264319 263903 255765 246263 245098 246969 0 0 0 0 1 0 0 0 0 0 0
54 268347 264291 264319 255765 246263 245098 0 0 0 0 0 1 0 0 0 0 0
55 273046 263276 268347 264319 255765 246263 0 0 0 0 0 0 1 0 0 0 0
56 273963 262572 273046 268347 264319 255765 0 0 0 0 0 0 0 1 0 0 0
57 267430 256167 273963 273046 268347 264319 0 0 0 0 0 0 0 0 1 0 0
58 271993 264221 267430 273963 273046 268347 0 0 0 0 0 0 0 0 0 1 0
59 292710 293860 271993 267430 273963 273046 0 0 0 0 0 0 0 0 0 0 1
60 295881 300713 292710 271993 267430 273963 0 0 0 0 0 0 0 0 0 0 0
61 293299 287224 295881 292710 271993 267430 1 0 0 0 0 0 0 0 0 0 0
t
1 1
2 2
3 3
4 4
5 5
6 6
7 7
8 8
9 9
10 10
11 11
12 12
13 13
14 14
15 15
16 16
17 17
18 18
19 19
20 20
21 21
22 22
23 23
24 24
25 25
26 26
27 27
28 28
29 29
30 30
31 31
32 32
33 33
34 34
35 35
36 36
37 37
38 38
39 39
40 40
41 41
42 42
43 43
44 44
45 45
46 46
47 47
48 48
49 49
50 50
51 51
52 52
53 53
54 54
55 55
56 56
57 57
58 58
59 59
60 60
61 61
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
-9.472e+04 5.923e-01 8.958e-01 -4.176e-01 2.702e-01 -1.577e-01
M1 M2 M3 M4 M5 M6
1.285e+04 8.052e+03 1.504e+04 1.943e+04 1.811e+04 1.865e+04
M7 M8 M9 M10 M11 t
1.767e+04 2.042e+04 1.757e+04 1.810e+04 2.010e+04 5.201e+02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-7389.4 -2053.2 -226.4 2380.5 10163.4
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -9.472e+04 3.154e+04 -3.003 0.004436 **
X 5.923e-01 1.673e-01 3.540 0.000977 ***
Y1 8.958e-01 1.618e-01 5.537 1.71e-06 ***
Y2 -4.176e-01 1.816e-01 -2.300 0.026368 *
Y3 2.702e-01 1.524e-01 1.773 0.083382 .
Y4 -1.577e-01 1.083e-01 -1.457 0.152496
M1 1.285e+04 4.885e+03 2.631 0.011774 *
M2 8.052e+03 5.757e+03 1.399 0.169094
M3 1.504e+04 6.456e+03 2.330 0.024569 *
M4 1.943e+04 5.730e+03 3.392 0.001501 **
M5 1.811e+04 5.143e+03 3.521 0.001032 **
M6 1.865e+04 5.874e+03 3.175 0.002770 **
M7 1.767e+04 6.625e+03 2.668 0.010720 *
M8 2.042e+04 6.769e+03 3.017 0.004281 **
M9 1.757e+04 7.007e+03 2.508 0.016013 *
M10 1.810e+04 6.211e+03 2.914 0.005639 **
M11 2.010e+04 3.930e+03 5.116 6.92e-06 ***
t 5.201e+02 1.547e+02 3.362 0.001632 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 3686 on 43 degrees of freedom
Multiple R-squared: 0.9705, Adjusted R-squared: 0.9588
F-statistic: 83.13 on 17 and 43 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.3029924 0.6059848 0.69700762
[2,] 0.1886025 0.3772050 0.81139751
[3,] 0.1273817 0.2547634 0.87261829
[4,] 0.1454559 0.2909118 0.85454411
[5,] 0.0988623 0.1977246 0.90113770
[6,] 0.5604252 0.8791495 0.43957477
[7,] 0.6840168 0.6319663 0.31598316
[8,] 0.7630174 0.4739651 0.23698256
[9,] 0.8050516 0.3898968 0.19494840
[10,] 0.7171874 0.5656252 0.28281258
[11,] 0.6351433 0.7297134 0.36485668
[12,] 0.5943517 0.8112965 0.40564826
[13,] 0.6706982 0.6586036 0.32930181
[14,] 0.9089812 0.1820376 0.09101882
[15,] 0.9146957 0.1706087 0.08530435
[16,] 0.9197917 0.1604167 0.08020835
[17,] 0.8702267 0.2595466 0.12977329
[18,] 0.8165997 0.3668005 0.18340027
[19,] 0.6859553 0.6280894 0.31404471
[20,] 0.6757538 0.6484924 0.32424622
> postscript(file="/var/www/html/rcomp/tmp/13v2o1259608580.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2mlnq1259608580.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/39n2h1259608580.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4dnjs1259608580.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5fdzi1259608580.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 = 61
Frequency = 1
1 2 3 4 5 6
10163.357054 3424.747501 1439.566378 -226.373383 623.091249 2774.297510
7 8 9 10 11 12
1233.591884 -856.610572 3418.872706 -772.043610 3194.414582 3404.566093
13 14 15 16 17 18
-1922.009189 -359.555114 -2053.202878 -1506.447686 -4985.999604 139.753192
19 20 21 22 23 24
-1607.978042 3.903232 1314.717125 -3580.478715 -2038.020438 -2536.414174
25 26 27 28 29 30
-2332.521671 -7389.448753 -80.153409 -4553.919890 3251.081230 -2931.731863
31 32 33 34 35 36
-1215.363304 521.398545 -237.511345 -3547.264884 2870.049119 -2681.977140
37 38 39 40 41 42
-3314.865645 1943.724440 -2907.776261 2315.645884 -2395.815125 -1921.304401
43 44 45 46 47 48
-3686.393450 325.792654 -5491.609529 2562.051463 -3681.493002 -1793.367393
49 50 51 52 53 54
-1784.536144 2380.531926 3601.566169 3971.095076 3507.642250 1938.985562
55 56 57 58 59 60
5276.142913 5.516142 995.531043 5337.735746 -344.950262 3607.192615
61
-809.424406
> postscript(file="/var/www/html/rcomp/tmp/6fs8d1259608580.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 = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 10163.357054 NA
1 3424.747501 10163.357054
2 1439.566378 3424.747501
3 -226.373383 1439.566378
4 623.091249 -226.373383
5 2774.297510 623.091249
6 1233.591884 2774.297510
7 -856.610572 1233.591884
8 3418.872706 -856.610572
9 -772.043610 3418.872706
10 3194.414582 -772.043610
11 3404.566093 3194.414582
12 -1922.009189 3404.566093
13 -359.555114 -1922.009189
14 -2053.202878 -359.555114
15 -1506.447686 -2053.202878
16 -4985.999604 -1506.447686
17 139.753192 -4985.999604
18 -1607.978042 139.753192
19 3.903232 -1607.978042
20 1314.717125 3.903232
21 -3580.478715 1314.717125
22 -2038.020438 -3580.478715
23 -2536.414174 -2038.020438
24 -2332.521671 -2536.414174
25 -7389.448753 -2332.521671
26 -80.153409 -7389.448753
27 -4553.919890 -80.153409
28 3251.081230 -4553.919890
29 -2931.731863 3251.081230
30 -1215.363304 -2931.731863
31 521.398545 -1215.363304
32 -237.511345 521.398545
33 -3547.264884 -237.511345
34 2870.049119 -3547.264884
35 -2681.977140 2870.049119
36 -3314.865645 -2681.977140
37 1943.724440 -3314.865645
38 -2907.776261 1943.724440
39 2315.645884 -2907.776261
40 -2395.815125 2315.645884
41 -1921.304401 -2395.815125
42 -3686.393450 -1921.304401
43 325.792654 -3686.393450
44 -5491.609529 325.792654
45 2562.051463 -5491.609529
46 -3681.493002 2562.051463
47 -1793.367393 -3681.493002
48 -1784.536144 -1793.367393
49 2380.531926 -1784.536144
50 3601.566169 2380.531926
51 3971.095076 3601.566169
52 3507.642250 3971.095076
53 1938.985562 3507.642250
54 5276.142913 1938.985562
55 5.516142 5276.142913
56 995.531043 5.516142
57 5337.735746 995.531043
58 -344.950262 5337.735746
59 3607.192615 -344.950262
60 -809.424406 3607.192615
61 NA -809.424406
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 3424.747501 10163.357054
[2,] 1439.566378 3424.747501
[3,] -226.373383 1439.566378
[4,] 623.091249 -226.373383
[5,] 2774.297510 623.091249
[6,] 1233.591884 2774.297510
[7,] -856.610572 1233.591884
[8,] 3418.872706 -856.610572
[9,] -772.043610 3418.872706
[10,] 3194.414582 -772.043610
[11,] 3404.566093 3194.414582
[12,] -1922.009189 3404.566093
[13,] -359.555114 -1922.009189
[14,] -2053.202878 -359.555114
[15,] -1506.447686 -2053.202878
[16,] -4985.999604 -1506.447686
[17,] 139.753192 -4985.999604
[18,] -1607.978042 139.753192
[19,] 3.903232 -1607.978042
[20,] 1314.717125 3.903232
[21,] -3580.478715 1314.717125
[22,] -2038.020438 -3580.478715
[23,] -2536.414174 -2038.020438
[24,] -2332.521671 -2536.414174
[25,] -7389.448753 -2332.521671
[26,] -80.153409 -7389.448753
[27,] -4553.919890 -80.153409
[28,] 3251.081230 -4553.919890
[29,] -2931.731863 3251.081230
[30,] -1215.363304 -2931.731863
[31,] 521.398545 -1215.363304
[32,] -237.511345 521.398545
[33,] -3547.264884 -237.511345
[34,] 2870.049119 -3547.264884
[35,] -2681.977140 2870.049119
[36,] -3314.865645 -2681.977140
[37,] 1943.724440 -3314.865645
[38,] -2907.776261 1943.724440
[39,] 2315.645884 -2907.776261
[40,] -2395.815125 2315.645884
[41,] -1921.304401 -2395.815125
[42,] -3686.393450 -1921.304401
[43,] 325.792654 -3686.393450
[44,] -5491.609529 325.792654
[45,] 2562.051463 -5491.609529
[46,] -3681.493002 2562.051463
[47,] -1793.367393 -3681.493002
[48,] -1784.536144 -1793.367393
[49,] 2380.531926 -1784.536144
[50,] 3601.566169 2380.531926
[51,] 3971.095076 3601.566169
[52,] 3507.642250 3971.095076
[53,] 1938.985562 3507.642250
[54,] 5276.142913 1938.985562
[55,] 5.516142 5276.142913
[56,] 995.531043 5.516142
[57,] 5337.735746 995.531043
[58,] -344.950262 5337.735746
[59,] 3607.192615 -344.950262
[60,] -809.424406 3607.192615
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 3424.747501 10163.357054
2 1439.566378 3424.747501
3 -226.373383 1439.566378
4 623.091249 -226.373383
5 2774.297510 623.091249
6 1233.591884 2774.297510
7 -856.610572 1233.591884
8 3418.872706 -856.610572
9 -772.043610 3418.872706
10 3194.414582 -772.043610
11 3404.566093 3194.414582
12 -1922.009189 3404.566093
13 -359.555114 -1922.009189
14 -2053.202878 -359.555114
15 -1506.447686 -2053.202878
16 -4985.999604 -1506.447686
17 139.753192 -4985.999604
18 -1607.978042 139.753192
19 3.903232 -1607.978042
20 1314.717125 3.903232
21 -3580.478715 1314.717125
22 -2038.020438 -3580.478715
23 -2536.414174 -2038.020438
24 -2332.521671 -2536.414174
25 -7389.448753 -2332.521671
26 -80.153409 -7389.448753
27 -4553.919890 -80.153409
28 3251.081230 -4553.919890
29 -2931.731863 3251.081230
30 -1215.363304 -2931.731863
31 521.398545 -1215.363304
32 -237.511345 521.398545
33 -3547.264884 -237.511345
34 2870.049119 -3547.264884
35 -2681.977140 2870.049119
36 -3314.865645 -2681.977140
37 1943.724440 -3314.865645
38 -2907.776261 1943.724440
39 2315.645884 -2907.776261
40 -2395.815125 2315.645884
41 -1921.304401 -2395.815125
42 -3686.393450 -1921.304401
43 325.792654 -3686.393450
44 -5491.609529 325.792654
45 2562.051463 -5491.609529
46 -3681.493002 2562.051463
47 -1793.367393 -3681.493002
48 -1784.536144 -1793.367393
49 2380.531926 -1784.536144
50 3601.566169 2380.531926
51 3971.095076 3601.566169
52 3507.642250 3971.095076
53 1938.985562 3507.642250
54 5276.142913 1938.985562
55 5.516142 5276.142913
56 995.531043 5.516142
57 5337.735746 995.531043
58 -344.950262 5337.735746
59 3607.192615 -344.950262
60 -809.424406 3607.192615
> 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/73giw1259608580.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8ztpc1259608580.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9quke1259608580.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10dm551259608580.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11p7d61259608580.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/12lly11259608580.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/13qrhd1259608580.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/14kc891259608580.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/15yud91259608580.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/161h2d1259608581.tab")
+ }
>
> system("convert tmp/13v2o1259608580.ps tmp/13v2o1259608580.png")
> system("convert tmp/2mlnq1259608580.ps tmp/2mlnq1259608580.png")
> system("convert tmp/39n2h1259608580.ps tmp/39n2h1259608580.png")
> system("convert tmp/4dnjs1259608580.ps tmp/4dnjs1259608580.png")
> system("convert tmp/5fdzi1259608580.ps tmp/5fdzi1259608580.png")
> system("convert tmp/6fs8d1259608580.ps tmp/6fs8d1259608580.png")
> system("convert tmp/73giw1259608580.ps tmp/73giw1259608580.png")
> system("convert tmp/8ztpc1259608580.ps tmp/8ztpc1259608580.png")
> system("convert tmp/9quke1259608580.ps tmp/9quke1259608580.png")
> system("convert tmp/10dm551259608580.ps tmp/10dm551259608580.png")
>
>
> proc.time()
user system elapsed
2.458 1.649 3.628