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.
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Type 'license()' or 'licence()' for distribution details.
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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(277128
+ ,0
+ ,277915
+ ,276687
+ ,283042
+ ,286602
+ ,277103
+ ,0
+ ,277128
+ ,277915
+ ,276687
+ ,283042
+ ,275037
+ ,0
+ ,277103
+ ,277128
+ ,277915
+ ,276687
+ ,270150
+ ,0
+ ,275037
+ ,277103
+ ,277128
+ ,277915
+ ,267140
+ ,0
+ ,270150
+ ,275037
+ ,277103
+ ,277128
+ ,264993
+ ,0
+ ,267140
+ ,270150
+ ,275037
+ ,277103
+ ,287259
+ ,0
+ ,264993
+ ,267140
+ ,270150
+ ,275037
+ ,291186
+ ,0
+ ,287259
+ ,264993
+ ,267140
+ ,270150
+ ,292300
+ ,0
+ ,291186
+ ,287259
+ ,264993
+ ,267140
+ ,288186
+ ,0
+ ,292300
+ ,291186
+ ,287259
+ ,264993
+ ,281477
+ ,0
+ ,288186
+ ,292300
+ ,291186
+ ,287259
+ ,282656
+ ,0
+ ,281477
+ ,288186
+ ,292300
+ ,291186
+ ,280190
+ ,0
+ ,282656
+ ,281477
+ ,288186
+ ,292300
+ ,280408
+ ,0
+ ,280190
+ ,282656
+ ,281477
+ ,288186
+ ,276836
+ ,0
+ ,280408
+ ,280190
+ ,282656
+ ,281477
+ ,275216
+ ,0
+ ,276836
+ ,280408
+ ,280190
+ ,282656
+ ,274352
+ ,0
+ ,275216
+ ,276836
+ ,280408
+ ,280190
+ ,271311
+ ,0
+ ,274352
+ ,275216
+ ,276836
+ ,280408
+ ,289802
+ ,0
+ ,271311
+ ,274352
+ ,275216
+ ,276836
+ ,290726
+ ,0
+ ,289802
+ ,271311
+ ,274352
+ ,275216
+ ,292300
+ ,0
+ ,290726
+ ,289802
+ ,271311
+ ,274352
+ ,278506
+ ,0
+ ,292300
+ ,290726
+ ,289802
+ ,271311
+ ,269826
+ ,0
+ ,278506
+ ,292300
+ ,290726
+ ,289802
+ ,265861
+ ,0
+ ,269826
+ ,278506
+ ,292300
+ ,290726
+ ,269034
+ ,0
+ ,265861
+ ,269826
+ ,278506
+ ,292300
+ ,264176
+ ,0
+ ,269034
+ ,265861
+ ,269826
+ ,278506
+ ,255198
+ ,0
+ ,264176
+ ,269034
+ ,265861
+ ,269826
+ ,253353
+ ,0
+ ,255198
+ ,264176
+ ,269034
+ ,265861
+ ,246057
+ ,0
+ ,253353
+ ,255198
+ ,264176
+ ,269034
+ ,235372
+ ,0
+ ,246057
+ ,253353
+ ,255198
+ ,264176
+ ,258556
+ ,0
+ ,235372
+ ,246057
+ ,253353
+ ,255198
+ ,260993
+ ,0
+ ,258556
+ ,235372
+ ,246057
+ ,253353
+ ,254663
+ ,0
+ ,260993
+ ,258556
+ ,235372
+ ,246057
+ ,250643
+ ,0
+ ,254663
+ ,260993
+ ,258556
+ ,235372
+ ,243422
+ ,0
+ ,250643
+ ,254663
+ ,260993
+ ,258556
+ ,247105
+ ,0
+ ,243422
+ ,250643
+ ,254663
+ ,260993
+ ,248541
+ ,0
+ ,247105
+ ,243422
+ ,250643
+ ,254663
+ ,245039
+ ,0
+ ,248541
+ ,247105
+ ,243422
+ ,250643
+ ,237080
+ ,0
+ ,245039
+ ,248541
+ ,247105
+ ,243422
+ ,237085
+ ,0
+ ,237080
+ ,245039
+ ,248541
+ ,247105
+ ,225554
+ ,0
+ ,237085
+ ,237080
+ ,245039
+ ,248541
+ ,226839
+ ,1
+ ,225554
+ ,237085
+ ,237080
+ ,245039
+ ,247934
+ ,1
+ ,226839
+ ,225554
+ ,237085
+ ,237080
+ ,248333
+ ,1
+ ,247934
+ ,226839
+ ,225554
+ ,237085
+ ,246969
+ ,1
+ ,248333
+ ,247934
+ ,226839
+ ,225554
+ ,245098
+ ,1
+ ,246969
+ ,248333
+ ,247934
+ ,226839
+ ,246263
+ ,1
+ ,245098
+ ,246969
+ ,248333
+ ,247934
+ ,255765
+ ,1
+ ,246263
+ ,245098
+ ,246969
+ ,248333
+ ,264319
+ ,1
+ ,255765
+ ,246263
+ ,245098
+ ,246969
+ ,268347
+ ,1
+ ,264319
+ ,255765
+ ,246263
+ ,245098
+ ,273046
+ ,1
+ ,268347
+ ,264319
+ ,255765
+ ,246263
+ ,273963
+ ,1
+ ,273046
+ ,268347
+ ,264319
+ ,255765
+ ,267430
+ ,1
+ ,273963
+ ,273046
+ ,268347
+ ,264319
+ ,271993
+ ,1
+ ,267430
+ ,273963
+ ,273046
+ ,268347
+ ,292710
+ ,1
+ ,271993
+ ,267430
+ ,273963
+ ,273046
+ ,295881
+ ,1
+ ,292710
+ ,271993
+ ,267430
+ ,273963)
+ ,dim=c(6
+ ,56)
+ ,dimnames=list(c('nwwmb'
+ ,'dummy_variable'
+ ,'y[t-1]'
+ ,'y[t-2]'
+ ,'y[t-3]'
+ ,'y[t-4]
')
+ ,1:56))
> y <- array(NA,dim=c(6,56),dimnames=list(c('nwwmb','dummy_variable','y[t-1]','y[t-2]','y[t-3]','y[t-4]
'),1:56))
> 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
nwwmb dummy_variable y[t-1] y[t-2] y[t-3] y[t-4]\r M1 M2 M3 M4 M5 M6 M7 M8
1 277128 0 277915 276687 283042 286602 1 0 0 0 0 0 0 0
2 277103 0 277128 277915 276687 283042 0 1 0 0 0 0 0 0
3 275037 0 277103 277128 277915 276687 0 0 1 0 0 0 0 0
4 270150 0 275037 277103 277128 277915 0 0 0 1 0 0 0 0
5 267140 0 270150 275037 277103 277128 0 0 0 0 1 0 0 0
6 264993 0 267140 270150 275037 277103 0 0 0 0 0 1 0 0
7 287259 0 264993 267140 270150 275037 0 0 0 0 0 0 1 0
8 291186 0 287259 264993 267140 270150 0 0 0 0 0 0 0 1
9 292300 0 291186 287259 264993 267140 0 0 0 0 0 0 0 0
10 288186 0 292300 291186 287259 264993 0 0 0 0 0 0 0 0
11 281477 0 288186 292300 291186 287259 0 0 0 0 0 0 0 0
12 282656 0 281477 288186 292300 291186 0 0 0 0 0 0 0 0
13 280190 0 282656 281477 288186 292300 1 0 0 0 0 0 0 0
14 280408 0 280190 282656 281477 288186 0 1 0 0 0 0 0 0
15 276836 0 280408 280190 282656 281477 0 0 1 0 0 0 0 0
16 275216 0 276836 280408 280190 282656 0 0 0 1 0 0 0 0
17 274352 0 275216 276836 280408 280190 0 0 0 0 1 0 0 0
18 271311 0 274352 275216 276836 280408 0 0 0 0 0 1 0 0
19 289802 0 271311 274352 275216 276836 0 0 0 0 0 0 1 0
20 290726 0 289802 271311 274352 275216 0 0 0 0 0 0 0 1
21 292300 0 290726 289802 271311 274352 0 0 0 0 0 0 0 0
22 278506 0 292300 290726 289802 271311 0 0 0 0 0 0 0 0
23 269826 0 278506 292300 290726 289802 0 0 0 0 0 0 0 0
24 265861 0 269826 278506 292300 290726 0 0 0 0 0 0 0 0
25 269034 0 265861 269826 278506 292300 1 0 0 0 0 0 0 0
26 264176 0 269034 265861 269826 278506 0 1 0 0 0 0 0 0
27 255198 0 264176 269034 265861 269826 0 0 1 0 0 0 0 0
28 253353 0 255198 264176 269034 265861 0 0 0 1 0 0 0 0
29 246057 0 253353 255198 264176 269034 0 0 0 0 1 0 0 0
30 235372 0 246057 253353 255198 264176 0 0 0 0 0 1 0 0
31 258556 0 235372 246057 253353 255198 0 0 0 0 0 0 1 0
32 260993 0 258556 235372 246057 253353 0 0 0 0 0 0 0 1
33 254663 0 260993 258556 235372 246057 0 0 0 0 0 0 0 0
34 250643 0 254663 260993 258556 235372 0 0 0 0 0 0 0 0
35 243422 0 250643 254663 260993 258556 0 0 0 0 0 0 0 0
36 247105 0 243422 250643 254663 260993 0 0 0 0 0 0 0 0
37 248541 0 247105 243422 250643 254663 1 0 0 0 0 0 0 0
38 245039 0 248541 247105 243422 250643 0 1 0 0 0 0 0 0
39 237080 0 245039 248541 247105 243422 0 0 1 0 0 0 0 0
40 237085 0 237080 245039 248541 247105 0 0 0 1 0 0 0 0
41 225554 0 237085 237080 245039 248541 0 0 0 0 1 0 0 0
42 226839 1 225554 237085 237080 245039 0 0 0 0 0 1 0 0
43 247934 1 226839 225554 237085 237080 0 0 0 0 0 0 1 0
44 248333 1 247934 226839 225554 237085 0 0 0 0 0 0 0 1
45 246969 1 248333 247934 226839 225554 0 0 0 0 0 0 0 0
46 245098 1 246969 248333 247934 226839 0 0 0 0 0 0 0 0
47 246263 1 245098 246969 248333 247934 0 0 0 0 0 0 0 0
48 255765 1 246263 245098 246969 248333 0 0 0 0 0 0 0 0
49 264319 1 255765 246263 245098 246969 1 0 0 0 0 0 0 0
50 268347 1 264319 255765 246263 245098 0 1 0 0 0 0 0 0
51 273046 1 268347 264319 255765 246263 0 0 1 0 0 0 0 0
52 273963 1 273046 268347 264319 255765 0 0 0 1 0 0 0 0
53 267430 1 273963 273046 268347 264319 0 0 0 0 1 0 0 0
54 271993 1 267430 273963 273046 268347 0 0 0 0 0 1 0 0
55 292710 1 271993 267430 273963 273046 0 0 0 0 0 0 1 0
56 295881 1 292710 271993 267430 273963 0 0 0 0 0 0 0 1
M9 M10 M11 t
1 0 0 0 1
2 0 0 0 2
3 0 0 0 3
4 0 0 0 4
5 0 0 0 5
6 0 0 0 6
7 0 0 0 7
8 0 0 0 8
9 1 0 0 9
10 0 1 0 10
11 0 0 1 11
12 0 0 0 12
13 0 0 0 13
14 0 0 0 14
15 0 0 0 15
16 0 0 0 16
17 0 0 0 17
18 0 0 0 18
19 0 0 0 19
20 0 0 0 20
21 1 0 0 21
22 0 1 0 22
23 0 0 1 23
24 0 0 0 24
25 0 0 0 25
26 0 0 0 26
27 0 0 0 27
28 0 0 0 28
29 0 0 0 29
30 0 0 0 30
31 0 0 0 31
32 0 0 0 32
33 1 0 0 33
34 0 1 0 34
35 0 0 1 35
36 0 0 0 36
37 0 0 0 37
38 0 0 0 38
39 0 0 0 39
40 0 0 0 40
41 0 0 0 41
42 0 0 0 42
43 0 0 0 43
44 0 0 0 44
45 1 0 0 45
46 0 1 0 46
47 0 0 1 47
48 0 0 0 48
49 0 0 0 49
50 0 0 0 50
51 0 0 0 51
52 0 0 0 52
53 0 0 0 53
54 0 0 0 54
55 0 0 0 55
56 0 0 0 56
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) dummy_variable `y[t-1]` `y[t-2]` `y[t-3]`
1.938e+04 5.208e+03 9.257e-01 1.709e-01 1.551e-01
`y[t-4]\r` M1 M2 M3 M4
-3.053e-01 8.377e+02 -2.931e+03 -8.038e+03 -5.572e+03
M5 M6 M7 M8 M9
-8.599e+03 -5.579e+03 1.766e+04 1.153e+03 -6.680e+03
M10 M11 t
-1.611e+04 -9.459e+03 -9.901e+01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-5461.9 -2009.5 385.6 2049.1 5224.7
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.938e+04 1.292e+04 1.500 0.141936
dummy_variable 5.208e+03 2.030e+03 2.566 0.014350 *
`y[t-1]` 9.257e-01 1.463e-01 6.327 2.03e-07 ***
`y[t-2]` 1.709e-01 2.085e-01 0.820 0.417506
`y[t-3]` 1.551e-01 2.142e-01 0.724 0.473358
`y[t-4]\r` -3.053e-01 1.562e-01 -1.955 0.057942 .
M1 8.377e+02 2.719e+03 0.308 0.759669
M2 -2.931e+03 2.998e+03 -0.978 0.334330
M3 -8.038e+03 2.789e+03 -2.882 0.006463 **
M4 -5.572e+03 2.547e+03 -2.187 0.034932 *
M5 -8.599e+03 2.449e+03 -3.512 0.001166 **
M6 -5.579e+03 2.466e+03 -2.262 0.029494 *
M7 1.766e+04 2.403e+03 7.350 8.30e-09 ***
M8 1.153e+03 4.661e+03 0.247 0.805994
M9 -6.680e+03 5.009e+03 -1.334 0.190280
M10 -1.611e+04 4.385e+03 -3.674 0.000733 ***
M11 -9.459e+03 2.597e+03 -3.642 0.000804 ***
t -9.901e+01 5.497e+01 -1.801 0.079596 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 3475 on 38 degrees of freedom
Multiple R-squared: 0.9746, Adjusted R-squared: 0.9633
F-statistic: 85.85 on 17 and 38 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,] 0.02563042 0.05126084 0.9743696
[2,] 0.59559048 0.80881904 0.4044095
[3,] 0.44733857 0.89467715 0.5526614
[4,] 0.48083412 0.96166823 0.5191659
[5,] 0.46737397 0.93474794 0.5326260
[6,] 0.36825051 0.73650101 0.6317495
[7,] 0.34618817 0.69237635 0.6538118
[8,] 0.45345705 0.90691409 0.5465430
[9,] 0.36202098 0.72404195 0.6379790
[10,] 0.48117075 0.96234150 0.5188293
[11,] 0.56645888 0.86708225 0.4335411
[12,] 0.74521859 0.50956281 0.2547814
[13,] 0.68220302 0.63559396 0.3177970
[14,] 0.63627733 0.72744535 0.3637227
[15,] 0.46498211 0.92996422 0.5350179
> postscript(file="/var/www/html/rcomp/tmp/1eith1258909059.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/29hc51258909059.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3aua81258909059.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/494nk1258909059.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/55lkw1258909059.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 = 56
Frequency = 1
1 2 3 4 5 6 7
-3944.5014 316.1000 1482.9418 -3357.8653 1399.2640 265.2580 2015.5499
8 9 10 11 12 13 14
1284.3084 2302.6885 1907.7791 -1547.1886 -1788.8014 -3959.9183 1992.0381
15 16 17 18 19 20 21
1614.4376 1638.6417 5224.6626 959.5306 -1570.9801 -993.3664 4703.9505
22 23 24 25 26 27 28
-4970.8983 -2201.6864 -5096.4686 5111.9276 -1002.5569 -2855.1328 370.6724
29 30 31 32 33 34 35
1166.0211 -5461.9448 3260.1693 3242.0846 -1945.4349 2149.8903 -120.3388
36 37 38 39 40 41 42
3299.6539 512.7737 -1187.1489 -3719.8847 2785.3866 -3281.6136 712.2364
43 44 45 46 47 48 49
-2987.0156 -3933.5715 -5061.2041 913.2289 3869.2138 3585.6162 2279.7184
50 51 52 53 54 55 56
-118.4322 3477.6381 -1436.8354 -4508.3341 3524.9198 -717.7235 400.5447
> postscript(file="/var/www/html/rcomp/tmp/6l6sv1258909059.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 = 56
Frequency = 1
lag(myerror, k = 1) myerror
0 -3944.5014 NA
1 316.1000 -3944.5014
2 1482.9418 316.1000
3 -3357.8653 1482.9418
4 1399.2640 -3357.8653
5 265.2580 1399.2640
6 2015.5499 265.2580
7 1284.3084 2015.5499
8 2302.6885 1284.3084
9 1907.7791 2302.6885
10 -1547.1886 1907.7791
11 -1788.8014 -1547.1886
12 -3959.9183 -1788.8014
13 1992.0381 -3959.9183
14 1614.4376 1992.0381
15 1638.6417 1614.4376
16 5224.6626 1638.6417
17 959.5306 5224.6626
18 -1570.9801 959.5306
19 -993.3664 -1570.9801
20 4703.9505 -993.3664
21 -4970.8983 4703.9505
22 -2201.6864 -4970.8983
23 -5096.4686 -2201.6864
24 5111.9276 -5096.4686
25 -1002.5569 5111.9276
26 -2855.1328 -1002.5569
27 370.6724 -2855.1328
28 1166.0211 370.6724
29 -5461.9448 1166.0211
30 3260.1693 -5461.9448
31 3242.0846 3260.1693
32 -1945.4349 3242.0846
33 2149.8903 -1945.4349
34 -120.3388 2149.8903
35 3299.6539 -120.3388
36 512.7737 3299.6539
37 -1187.1489 512.7737
38 -3719.8847 -1187.1489
39 2785.3866 -3719.8847
40 -3281.6136 2785.3866
41 712.2364 -3281.6136
42 -2987.0156 712.2364
43 -3933.5715 -2987.0156
44 -5061.2041 -3933.5715
45 913.2289 -5061.2041
46 3869.2138 913.2289
47 3585.6162 3869.2138
48 2279.7184 3585.6162
49 -118.4322 2279.7184
50 3477.6381 -118.4322
51 -1436.8354 3477.6381
52 -4508.3341 -1436.8354
53 3524.9198 -4508.3341
54 -717.7235 3524.9198
55 400.5447 -717.7235
56 NA 400.5447
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 316.1000 -3944.5014
[2,] 1482.9418 316.1000
[3,] -3357.8653 1482.9418
[4,] 1399.2640 -3357.8653
[5,] 265.2580 1399.2640
[6,] 2015.5499 265.2580
[7,] 1284.3084 2015.5499
[8,] 2302.6885 1284.3084
[9,] 1907.7791 2302.6885
[10,] -1547.1886 1907.7791
[11,] -1788.8014 -1547.1886
[12,] -3959.9183 -1788.8014
[13,] 1992.0381 -3959.9183
[14,] 1614.4376 1992.0381
[15,] 1638.6417 1614.4376
[16,] 5224.6626 1638.6417
[17,] 959.5306 5224.6626
[18,] -1570.9801 959.5306
[19,] -993.3664 -1570.9801
[20,] 4703.9505 -993.3664
[21,] -4970.8983 4703.9505
[22,] -2201.6864 -4970.8983
[23,] -5096.4686 -2201.6864
[24,] 5111.9276 -5096.4686
[25,] -1002.5569 5111.9276
[26,] -2855.1328 -1002.5569
[27,] 370.6724 -2855.1328
[28,] 1166.0211 370.6724
[29,] -5461.9448 1166.0211
[30,] 3260.1693 -5461.9448
[31,] 3242.0846 3260.1693
[32,] -1945.4349 3242.0846
[33,] 2149.8903 -1945.4349
[34,] -120.3388 2149.8903
[35,] 3299.6539 -120.3388
[36,] 512.7737 3299.6539
[37,] -1187.1489 512.7737
[38,] -3719.8847 -1187.1489
[39,] 2785.3866 -3719.8847
[40,] -3281.6136 2785.3866
[41,] 712.2364 -3281.6136
[42,] -2987.0156 712.2364
[43,] -3933.5715 -2987.0156
[44,] -5061.2041 -3933.5715
[45,] 913.2289 -5061.2041
[46,] 3869.2138 913.2289
[47,] 3585.6162 3869.2138
[48,] 2279.7184 3585.6162
[49,] -118.4322 2279.7184
[50,] 3477.6381 -118.4322
[51,] -1436.8354 3477.6381
[52,] -4508.3341 -1436.8354
[53,] 3524.9198 -4508.3341
[54,] -717.7235 3524.9198
[55,] 400.5447 -717.7235
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 316.1000 -3944.5014
2 1482.9418 316.1000
3 -3357.8653 1482.9418
4 1399.2640 -3357.8653
5 265.2580 1399.2640
6 2015.5499 265.2580
7 1284.3084 2015.5499
8 2302.6885 1284.3084
9 1907.7791 2302.6885
10 -1547.1886 1907.7791
11 -1788.8014 -1547.1886
12 -3959.9183 -1788.8014
13 1992.0381 -3959.9183
14 1614.4376 1992.0381
15 1638.6417 1614.4376
16 5224.6626 1638.6417
17 959.5306 5224.6626
18 -1570.9801 959.5306
19 -993.3664 -1570.9801
20 4703.9505 -993.3664
21 -4970.8983 4703.9505
22 -2201.6864 -4970.8983
23 -5096.4686 -2201.6864
24 5111.9276 -5096.4686
25 -1002.5569 5111.9276
26 -2855.1328 -1002.5569
27 370.6724 -2855.1328
28 1166.0211 370.6724
29 -5461.9448 1166.0211
30 3260.1693 -5461.9448
31 3242.0846 3260.1693
32 -1945.4349 3242.0846
33 2149.8903 -1945.4349
34 -120.3388 2149.8903
35 3299.6539 -120.3388
36 512.7737 3299.6539
37 -1187.1489 512.7737
38 -3719.8847 -1187.1489
39 2785.3866 -3719.8847
40 -3281.6136 2785.3866
41 712.2364 -3281.6136
42 -2987.0156 712.2364
43 -3933.5715 -2987.0156
44 -5061.2041 -3933.5715
45 913.2289 -5061.2041
46 3869.2138 913.2289
47 3585.6162 3869.2138
48 2279.7184 3585.6162
49 -118.4322 2279.7184
50 3477.6381 -118.4322
51 -1436.8354 3477.6381
52 -4508.3341 -1436.8354
53 3524.9198 -4508.3341
54 -717.7235 3524.9198
55 400.5447 -717.7235
> 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/7dg491258909059.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/87hm91258909059.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9uduu1258909059.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/103ak21258909059.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11z61m1258909059.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/12kzim1258909059.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/1331yj1258909059.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/14irmm1258909059.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/15hpk41258909059.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/160mbg1258909059.tab")
+ }
>
> system("convert tmp/1eith1258909059.ps tmp/1eith1258909059.png")
> system("convert tmp/29hc51258909059.ps tmp/29hc51258909059.png")
> system("convert tmp/3aua81258909059.ps tmp/3aua81258909059.png")
> system("convert tmp/494nk1258909059.ps tmp/494nk1258909059.png")
> system("convert tmp/55lkw1258909059.ps tmp/55lkw1258909059.png")
> system("convert tmp/6l6sv1258909059.ps tmp/6l6sv1258909059.png")
> system("convert tmp/7dg491258909059.ps tmp/7dg491258909059.png")
> system("convert tmp/87hm91258909059.ps tmp/87hm91258909059.png")
> system("convert tmp/9uduu1258909059.ps tmp/9uduu1258909059.png")
> system("convert tmp/103ak21258909059.ps tmp/103ak21258909059.png")
>
>
> proc.time()
user system elapsed
2.363 1.608 2.886