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(96.3
+ ,94.0
+ ,96.2
+ ,100.0
+ ,107.2
+ ,91.1
+ ,96.3
+ ,96.2
+ ,114.9
+ ,93.1
+ ,107.2
+ ,96.3
+ ,92.6
+ ,93.9
+ ,114.9
+ ,107.2
+ ,115.0
+ ,92.6
+ ,92.6
+ ,114.9
+ ,107.1
+ ,94.4
+ ,115.0
+ ,92.6
+ ,117.8
+ ,96.3
+ ,107.1
+ ,115.0
+ ,107.4
+ ,100.4
+ ,117.8
+ ,107.1
+ ,106.3
+ ,101.5
+ ,107.4
+ ,117.8
+ ,114.5
+ ,99.4
+ ,106.3
+ ,107.4
+ ,98.0
+ ,99.7
+ ,114.5
+ ,106.3
+ ,103.1
+ ,101.7
+ ,98.0
+ ,114.5
+ ,100.3
+ ,103.7
+ ,103.1
+ ,98.0
+ ,104.6
+ ,103.1
+ ,100.3
+ ,103.1
+ ,111.2
+ ,101.0
+ ,104.6
+ ,100.3
+ ,105.0
+ ,102.3
+ ,111.2
+ ,104.6
+ ,109.9
+ ,101.6
+ ,105.0
+ ,111.2
+ ,111.5
+ ,99.6
+ ,109.9
+ ,105.0
+ ,132.5
+ ,95.7
+ ,111.5
+ ,109.9
+ ,100.3
+ ,96.6
+ ,132.5
+ ,111.5
+ ,123.1
+ ,96.3
+ ,100.3
+ ,132.5
+ ,114.2
+ ,95.4
+ ,123.1
+ ,100.3
+ ,104.6
+ ,96.0
+ ,114.2
+ ,123.1
+ ,109.1
+ ,96.9
+ ,104.6
+ ,114.2
+ ,107.0
+ ,94.9
+ ,109.1
+ ,104.6
+ ,133.7
+ ,92.5
+ ,107.0
+ ,109.1
+ ,124.9
+ ,94.0
+ ,133.7
+ ,107.0
+ ,122.5
+ ,93.5
+ ,124.9
+ ,133.7
+ ,116.8
+ ,92.3
+ ,122.5
+ ,124.9
+ ,116.0
+ ,90.4
+ ,116.8
+ ,122.5
+ ,129.8
+ ,90.4
+ ,116.0
+ ,116.8
+ ,125.2
+ ,91.0
+ ,129.8
+ ,116.0
+ ,143.8
+ ,89.1
+ ,125.2
+ ,129.8
+ ,127.9
+ ,89.7
+ ,143.8
+ ,125.2
+ ,130.3
+ ,87.9
+ ,127.9
+ ,143.8
+ ,108.4
+ ,85.9
+ ,130.3
+ ,127.9
+ ,129.4
+ ,83.2
+ ,108.4
+ ,130.3
+ ,143.7
+ ,83.9
+ ,129.4
+ ,108.4
+ ,131.9
+ ,83.0
+ ,143.7
+ ,129.4
+ ,117.6
+ ,82.8
+ ,131.9
+ ,143.7
+ ,119.0
+ ,78.7
+ ,117.6
+ ,131.9
+ ,104.8
+ ,77.6
+ ,119.0
+ ,117.6
+ ,134.6
+ ,78.5
+ ,104.8
+ ,119.0
+ ,140.4
+ ,78.6
+ ,134.6
+ ,104.8
+ ,143.8
+ ,77.5
+ ,140.4
+ ,134.6
+ ,153.4
+ ,81.6
+ ,143.8
+ ,140.4
+ ,153.3
+ ,85.0
+ ,153.4
+ ,143.8
+ ,127.3
+ ,91.7
+ ,153.3
+ ,153.4
+ ,153.6
+ ,96.0
+ ,127.3
+ ,153.3
+ ,136.9
+ ,90.8
+ ,153.6
+ ,127.3
+ ,131.8
+ ,92.3
+ ,136.9
+ ,153.6
+ ,144.3
+ ,95.6
+ ,131.8
+ ,136.9
+ ,107.4
+ ,93.6
+ ,144.3
+ ,131.8
+ ,113.6
+ ,92.6
+ ,107.4
+ ,144.3
+ ,124.2
+ ,89.5
+ ,113.6
+ ,107.4
+ ,102.1
+ ,87.2
+ ,124.2
+ ,113.6
+ ,96.4
+ ,86.7
+ ,102.1
+ ,124.2
+ ,111.7
+ ,85.6
+ ,96.4
+ ,102.1)
+ ,dim=c(4
+ ,58)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2')
+ ,1:58))
> y <- array(NA,dim=c(4,58),dimnames=list(c('Y','X','Y1','Y2'),1:58))
> 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 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 96.3 94.0 96.2 100.0 1 0 0 0 0 0 0 0 0 0 0 1
2 107.2 91.1 96.3 96.2 0 1 0 0 0 0 0 0 0 0 0 2
3 114.9 93.1 107.2 96.3 0 0 1 0 0 0 0 0 0 0 0 3
4 92.6 93.9 114.9 107.2 0 0 0 1 0 0 0 0 0 0 0 4
5 115.0 92.6 92.6 114.9 0 0 0 0 1 0 0 0 0 0 0 5
6 107.1 94.4 115.0 92.6 0 0 0 0 0 1 0 0 0 0 0 6
7 117.8 96.3 107.1 115.0 0 0 0 0 0 0 1 0 0 0 0 7
8 107.4 100.4 117.8 107.1 0 0 0 0 0 0 0 1 0 0 0 8
9 106.3 101.5 107.4 117.8 0 0 0 0 0 0 0 0 1 0 0 9
10 114.5 99.4 106.3 107.4 0 0 0 0 0 0 0 0 0 1 0 10
11 98.0 99.7 114.5 106.3 0 0 0 0 0 0 0 0 0 0 1 11
12 103.1 101.7 98.0 114.5 0 0 0 0 0 0 0 0 0 0 0 12
13 100.3 103.7 103.1 98.0 1 0 0 0 0 0 0 0 0 0 0 13
14 104.6 103.1 100.3 103.1 0 1 0 0 0 0 0 0 0 0 0 14
15 111.2 101.0 104.6 100.3 0 0 1 0 0 0 0 0 0 0 0 15
16 105.0 102.3 111.2 104.6 0 0 0 1 0 0 0 0 0 0 0 16
17 109.9 101.6 105.0 111.2 0 0 0 0 1 0 0 0 0 0 0 17
18 111.5 99.6 109.9 105.0 0 0 0 0 0 1 0 0 0 0 0 18
19 132.5 95.7 111.5 109.9 0 0 0 0 0 0 1 0 0 0 0 19
20 100.3 96.6 132.5 111.5 0 0 0 0 0 0 0 1 0 0 0 20
21 123.1 96.3 100.3 132.5 0 0 0 0 0 0 0 0 1 0 0 21
22 114.2 95.4 123.1 100.3 0 0 0 0 0 0 0 0 0 1 0 22
23 104.6 96.0 114.2 123.1 0 0 0 0 0 0 0 0 0 0 1 23
24 109.1 96.9 104.6 114.2 0 0 0 0 0 0 0 0 0 0 0 24
25 107.0 94.9 109.1 104.6 1 0 0 0 0 0 0 0 0 0 0 25
26 133.7 92.5 107.0 109.1 0 1 0 0 0 0 0 0 0 0 0 26
27 124.9 94.0 133.7 107.0 0 0 1 0 0 0 0 0 0 0 0 27
28 122.5 93.5 124.9 133.7 0 0 0 1 0 0 0 0 0 0 0 28
29 116.8 92.3 122.5 124.9 0 0 0 0 1 0 0 0 0 0 0 29
30 116.0 90.4 116.8 122.5 0 0 0 0 0 1 0 0 0 0 0 30
31 129.8 90.4 116.0 116.8 0 0 0 0 0 0 1 0 0 0 0 31
32 125.2 91.0 129.8 116.0 0 0 0 0 0 0 0 1 0 0 0 32
33 143.8 89.1 125.2 129.8 0 0 0 0 0 0 0 0 1 0 0 33
34 127.9 89.7 143.8 125.2 0 0 0 0 0 0 0 0 0 1 0 34
35 130.3 87.9 127.9 143.8 0 0 0 0 0 0 0 0 0 0 1 35
36 108.4 85.9 130.3 127.9 0 0 0 0 0 0 0 0 0 0 0 36
37 129.4 83.2 108.4 130.3 1 0 0 0 0 0 0 0 0 0 0 37
38 143.7 83.9 129.4 108.4 0 1 0 0 0 0 0 0 0 0 0 38
39 131.9 83.0 143.7 129.4 0 0 1 0 0 0 0 0 0 0 0 39
40 117.6 82.8 131.9 143.7 0 0 0 1 0 0 0 0 0 0 0 40
41 119.0 78.7 117.6 131.9 0 0 0 0 1 0 0 0 0 0 0 41
42 104.8 77.6 119.0 117.6 0 0 0 0 0 1 0 0 0 0 0 42
43 134.6 78.5 104.8 119.0 0 0 0 0 0 0 1 0 0 0 0 43
44 140.4 78.6 134.6 104.8 0 0 0 0 0 0 0 1 0 0 0 44
45 143.8 77.5 140.4 134.6 0 0 0 0 0 0 0 0 1 0 0 45
46 153.4 81.6 143.8 140.4 0 0 0 0 0 0 0 0 0 1 0 46
47 153.3 85.0 153.4 143.8 0 0 0 0 0 0 0 0 0 0 1 47
48 127.3 91.7 153.3 153.4 0 0 0 0 0 0 0 0 0 0 0 48
49 153.6 96.0 127.3 153.3 1 0 0 0 0 0 0 0 0 0 0 49
50 136.9 90.8 153.6 127.3 0 1 0 0 0 0 0 0 0 0 0 50
51 131.8 92.3 136.9 153.6 0 0 1 0 0 0 0 0 0 0 0 51
52 144.3 95.6 131.8 136.9 0 0 0 1 0 0 0 0 0 0 0 52
53 107.4 93.6 144.3 131.8 0 0 0 0 1 0 0 0 0 0 0 53
54 113.6 92.6 107.4 144.3 0 0 0 0 0 1 0 0 0 0 0 54
55 124.2 89.5 113.6 107.4 0 0 0 0 0 0 1 0 0 0 0 55
56 102.1 87.2 124.2 113.6 0 0 0 0 0 0 0 1 0 0 0 56
57 96.4 86.7 102.1 124.2 0 0 0 0 0 0 0 0 1 0 0 57
58 111.7 85.6 96.4 102.1 0 0 0 0 0 0 0 0 0 1 0 58
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 M1 M2
56.66882 -0.41455 0.33464 0.43666 13.87102 21.80948
M3 M4 M5 M6 M7 M8
13.40853 4.64012 4.34175 4.82811 23.95296 7.17288
M9 M10 M11 t
11.36575 16.14628 5.96355 -0.06853
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-20.1877 -7.5815 0.7094 6.5224 22.3003
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 56.66882 35.49524 1.597 0.11787
X -0.41455 0.28441 -1.458 0.15240
Y1 0.33464 0.14150 2.365 0.02273 *
Y2 0.43666 0.16111 2.710 0.00969 **
M1 13.87102 7.78780 1.781 0.08213 .
M2 21.80948 8.07614 2.700 0.00994 **
M3 13.40853 7.85937 1.706 0.09538 .
M4 4.64012 7.65385 0.606 0.54761
M5 4.34175 7.70778 0.563 0.57623
M6 4.82811 7.87274 0.613 0.54301
M7 23.95296 8.03343 2.982 0.00476 **
M8 7.17288 8.33558 0.861 0.39439
M9 11.36575 7.77975 1.461 0.15147
M10 16.14628 8.02186 2.013 0.05058 .
M11 5.96355 8.10663 0.736 0.46604
t -0.06853 0.14526 -0.472 0.63956
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 11.38 on 42 degrees of freedom
Multiple R-squared: 0.6132, Adjusted R-squared: 0.4751
F-statistic: 4.439 on 15 and 42 DF, p-value: 6.608e-05
> 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,] 0.0517249140 0.1034498281 0.9482751
[2,] 0.0217229742 0.0434459484 0.9782770
[3,] 0.0102476507 0.0204953013 0.9897523
[4,] 0.0031940976 0.0063881952 0.9968059
[5,] 0.0012258084 0.0024516167 0.9987742
[6,] 0.0004083086 0.0008166172 0.9995917
[7,] 0.0001539230 0.0003078460 0.9998461
[8,] 0.0072055329 0.0144110658 0.9927945
[9,] 0.0073298701 0.0146597403 0.9926701
[10,] 0.0049143558 0.0098287116 0.9950856
[11,] 0.0026725513 0.0053451027 0.9973274
[12,] 0.0026231345 0.0052462690 0.9973769
[13,] 0.0016566905 0.0033133810 0.9983433
[14,] 0.0008018773 0.0016037546 0.9991981
[15,] 0.0027478898 0.0054957797 0.9972521
[16,] 0.0017116056 0.0034232113 0.9982884
[17,] 0.0022987229 0.0045974458 0.9977013
[18,] 0.0037648942 0.0075297884 0.9962351
[19,] 0.0025030836 0.0050061672 0.9974969
[20,] 0.0014389263 0.0028778526 0.9985611
[21,] 0.0021957402 0.0043914804 0.9978043
> postscript(file="/var/www/html/rcomp/tmp/1rd0w1258748789.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2xnga1258748789.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3aca01258748789.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/44dda1258748789.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5z1jm1258748789.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 = 58
Frequency = 1
1 2 3 4 5 6
-11.0626466 -7.6089199 5.6983495 -14.7694167 11.5588804 6.2286622
7 8 9 10 11 12
-8.4774721 -0.4603338 -6.4206152 1.1061878 -7.2819491 6.6202573
13 14 15 16 17 18
-3.6549738 -8.7635805 5.2190147 4.3085758 8.4781440 9.8987350
19 20 21 22 23 24
7.5506292 -15.1538752 5.0031539 -2.5514459 -8.6289278 9.3750867
25 26 27 28 29 30
-4.6704843 11.9024697 4.1757272 1.6914880 0.5066715 1.4566499
31 32 33 34 35 36
-1.0430005 7.1855536 16.3870536 -8.1919892 0.9120967 -9.6452012
37 38 39 40 41 42
2.7137673 11.9693002 -5.6895654 -13.5309431 -3.5256955 -12.8238239
43 44 45 46 47 48
2.4335828 21.3517694 5.2180673 8.1352894 14.9987801 -6.3501428
49 50 51 52 53 54
16.6743374 -7.4992695 -9.4035261 22.3002959 -17.0180003 -4.7602231
55 56 57 58
-0.4637395 -12.9231140 -20.1876596 1.5019579
> postscript(file="/var/www/html/rcomp/tmp/6o7uu1258748789.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 = 58
Frequency = 1
lag(myerror, k = 1) myerror
0 -11.0626466 NA
1 -7.6089199 -11.0626466
2 5.6983495 -7.6089199
3 -14.7694167 5.6983495
4 11.5588804 -14.7694167
5 6.2286622 11.5588804
6 -8.4774721 6.2286622
7 -0.4603338 -8.4774721
8 -6.4206152 -0.4603338
9 1.1061878 -6.4206152
10 -7.2819491 1.1061878
11 6.6202573 -7.2819491
12 -3.6549738 6.6202573
13 -8.7635805 -3.6549738
14 5.2190147 -8.7635805
15 4.3085758 5.2190147
16 8.4781440 4.3085758
17 9.8987350 8.4781440
18 7.5506292 9.8987350
19 -15.1538752 7.5506292
20 5.0031539 -15.1538752
21 -2.5514459 5.0031539
22 -8.6289278 -2.5514459
23 9.3750867 -8.6289278
24 -4.6704843 9.3750867
25 11.9024697 -4.6704843
26 4.1757272 11.9024697
27 1.6914880 4.1757272
28 0.5066715 1.6914880
29 1.4566499 0.5066715
30 -1.0430005 1.4566499
31 7.1855536 -1.0430005
32 16.3870536 7.1855536
33 -8.1919892 16.3870536
34 0.9120967 -8.1919892
35 -9.6452012 0.9120967
36 2.7137673 -9.6452012
37 11.9693002 2.7137673
38 -5.6895654 11.9693002
39 -13.5309431 -5.6895654
40 -3.5256955 -13.5309431
41 -12.8238239 -3.5256955
42 2.4335828 -12.8238239
43 21.3517694 2.4335828
44 5.2180673 21.3517694
45 8.1352894 5.2180673
46 14.9987801 8.1352894
47 -6.3501428 14.9987801
48 16.6743374 -6.3501428
49 -7.4992695 16.6743374
50 -9.4035261 -7.4992695
51 22.3002959 -9.4035261
52 -17.0180003 22.3002959
53 -4.7602231 -17.0180003
54 -0.4637395 -4.7602231
55 -12.9231140 -0.4637395
56 -20.1876596 -12.9231140
57 1.5019579 -20.1876596
58 NA 1.5019579
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -7.6089199 -11.0626466
[2,] 5.6983495 -7.6089199
[3,] -14.7694167 5.6983495
[4,] 11.5588804 -14.7694167
[5,] 6.2286622 11.5588804
[6,] -8.4774721 6.2286622
[7,] -0.4603338 -8.4774721
[8,] -6.4206152 -0.4603338
[9,] 1.1061878 -6.4206152
[10,] -7.2819491 1.1061878
[11,] 6.6202573 -7.2819491
[12,] -3.6549738 6.6202573
[13,] -8.7635805 -3.6549738
[14,] 5.2190147 -8.7635805
[15,] 4.3085758 5.2190147
[16,] 8.4781440 4.3085758
[17,] 9.8987350 8.4781440
[18,] 7.5506292 9.8987350
[19,] -15.1538752 7.5506292
[20,] 5.0031539 -15.1538752
[21,] -2.5514459 5.0031539
[22,] -8.6289278 -2.5514459
[23,] 9.3750867 -8.6289278
[24,] -4.6704843 9.3750867
[25,] 11.9024697 -4.6704843
[26,] 4.1757272 11.9024697
[27,] 1.6914880 4.1757272
[28,] 0.5066715 1.6914880
[29,] 1.4566499 0.5066715
[30,] -1.0430005 1.4566499
[31,] 7.1855536 -1.0430005
[32,] 16.3870536 7.1855536
[33,] -8.1919892 16.3870536
[34,] 0.9120967 -8.1919892
[35,] -9.6452012 0.9120967
[36,] 2.7137673 -9.6452012
[37,] 11.9693002 2.7137673
[38,] -5.6895654 11.9693002
[39,] -13.5309431 -5.6895654
[40,] -3.5256955 -13.5309431
[41,] -12.8238239 -3.5256955
[42,] 2.4335828 -12.8238239
[43,] 21.3517694 2.4335828
[44,] 5.2180673 21.3517694
[45,] 8.1352894 5.2180673
[46,] 14.9987801 8.1352894
[47,] -6.3501428 14.9987801
[48,] 16.6743374 -6.3501428
[49,] -7.4992695 16.6743374
[50,] -9.4035261 -7.4992695
[51,] 22.3002959 -9.4035261
[52,] -17.0180003 22.3002959
[53,] -4.7602231 -17.0180003
[54,] -0.4637395 -4.7602231
[55,] -12.9231140 -0.4637395
[56,] -20.1876596 -12.9231140
[57,] 1.5019579 -20.1876596
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -7.6089199 -11.0626466
2 5.6983495 -7.6089199
3 -14.7694167 5.6983495
4 11.5588804 -14.7694167
5 6.2286622 11.5588804
6 -8.4774721 6.2286622
7 -0.4603338 -8.4774721
8 -6.4206152 -0.4603338
9 1.1061878 -6.4206152
10 -7.2819491 1.1061878
11 6.6202573 -7.2819491
12 -3.6549738 6.6202573
13 -8.7635805 -3.6549738
14 5.2190147 -8.7635805
15 4.3085758 5.2190147
16 8.4781440 4.3085758
17 9.8987350 8.4781440
18 7.5506292 9.8987350
19 -15.1538752 7.5506292
20 5.0031539 -15.1538752
21 -2.5514459 5.0031539
22 -8.6289278 -2.5514459
23 9.3750867 -8.6289278
24 -4.6704843 9.3750867
25 11.9024697 -4.6704843
26 4.1757272 11.9024697
27 1.6914880 4.1757272
28 0.5066715 1.6914880
29 1.4566499 0.5066715
30 -1.0430005 1.4566499
31 7.1855536 -1.0430005
32 16.3870536 7.1855536
33 -8.1919892 16.3870536
34 0.9120967 -8.1919892
35 -9.6452012 0.9120967
36 2.7137673 -9.6452012
37 11.9693002 2.7137673
38 -5.6895654 11.9693002
39 -13.5309431 -5.6895654
40 -3.5256955 -13.5309431
41 -12.8238239 -3.5256955
42 2.4335828 -12.8238239
43 21.3517694 2.4335828
44 5.2180673 21.3517694
45 8.1352894 5.2180673
46 14.9987801 8.1352894
47 -6.3501428 14.9987801
48 16.6743374 -6.3501428
49 -7.4992695 16.6743374
50 -9.4035261 -7.4992695
51 22.3002959 -9.4035261
52 -17.0180003 22.3002959
53 -4.7602231 -17.0180003
54 -0.4637395 -4.7602231
55 -12.9231140 -0.4637395
56 -20.1876596 -12.9231140
57 1.5019579 -20.1876596
> 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/7ks491258748789.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8cx871258748789.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9r3o41258748789.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ncft1258748789.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11c0gq1258748789.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/127ic31258748789.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/1368qx1258748789.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/145wfl1258748789.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/15ekf31258748789.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/16liep1258748789.tab")
+ }
>
> system("convert tmp/1rd0w1258748789.ps tmp/1rd0w1258748789.png")
> system("convert tmp/2xnga1258748789.ps tmp/2xnga1258748789.png")
> system("convert tmp/3aca01258748789.ps tmp/3aca01258748789.png")
> system("convert tmp/44dda1258748789.ps tmp/44dda1258748789.png")
> system("convert tmp/5z1jm1258748789.ps tmp/5z1jm1258748789.png")
> system("convert tmp/6o7uu1258748789.ps tmp/6o7uu1258748789.png")
> system("convert tmp/7ks491258748789.ps tmp/7ks491258748789.png")
> system("convert tmp/8cx871258748789.ps tmp/8cx871258748789.png")
> system("convert tmp/9r3o41258748789.ps tmp/9r3o41258748789.png")
> system("convert tmp/10ncft1258748789.ps tmp/10ncft1258748789.png")
>
>
> proc.time()
user system elapsed
2.367 1.550 2.744