R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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(116.24
+ ,112.42
+ ,120.58
+ ,116.03
+ ,112
+ ,120.17
+ ,115.94
+ ,111.72
+ ,120.02
+ ,114.19
+ ,111.67
+ ,120.49
+ ,115.74
+ ,111.55
+ ,120.38
+ ,115.4
+ ,111.33
+ ,120.09
+ ,115.2
+ ,111.06
+ ,119.62
+ ,114.82
+ ,110.97
+ ,118.93
+ ,114.33
+ ,110.81
+ ,119.09
+ ,111.84
+ ,110.62
+ ,118.59
+ ,113.16
+ ,110.71
+ ,117.87
+ ,112.52
+ ,110.51
+ ,117.74
+ ,112.39
+ ,110.5
+ ,117.61
+ ,112.24
+ ,110.37
+ ,117.55
+ ,112.1
+ ,110.38
+ ,117.06
+ ,109.85
+ ,110.26
+ ,117.08
+ ,111.89
+ ,110.28
+ ,117.21
+ ,111.88
+ ,110.25
+ ,117.58
+ ,111.48
+ ,110.09
+ ,117.27
+ ,110.98
+ ,110.01
+ ,117.14
+ ,110.42
+ ,109.75
+ ,116.52
+ ,107.9
+ ,109.57
+ ,116.16
+ ,109.46
+ ,109.59
+ ,114.79
+ ,109.23
+ ,109.45
+ ,114.97
+ ,109.02
+ ,109.21
+ ,114.66
+ ,109.04
+ ,109
+ ,114.3
+ ,109.49
+ ,108.83
+ ,114.48
+ ,107.23
+ ,108.62
+ ,114.96
+ ,109
+ ,108.56
+ ,115.44
+ ,109.12
+ ,108.41
+ ,116.38
+ ,109.24
+ ,108.27
+ ,116.5
+ ,108.92
+ ,108.03
+ ,116.2
+ ,109.53
+ ,107.67
+ ,116.37
+ ,107.06
+ ,107.31
+ ,116.46
+ ,109.11
+ ,107.14
+ ,115.07
+ ,109.26
+ ,107.02
+ ,115.03
+ ,109.99
+ ,106.79
+ ,115.15
+ ,110.17
+ ,106.49
+ ,114.71
+ ,110.28
+ ,106.14
+ ,114.67
+ ,109.13
+ ,105.94
+ ,115.49
+ ,110.15
+ ,105.87
+ ,114.65
+ ,109.39
+ ,105.71
+ ,114.92
+ ,108.45
+ ,105.48
+ ,114.17
+ ,108.23
+ ,105.31
+ ,112.8
+ ,107.44
+ ,105.09
+ ,112.28
+ ,104.86
+ ,104.88
+ ,112.05
+ ,106.23
+ ,104.76
+ ,111.03
+ ,105.85
+ ,104.62
+ ,110.4
+ ,104.95
+ ,104.49
+ ,109.08
+ ,104.46
+ ,104.29
+ ,107.89)
+ ,dim=c(3
+ ,50)
+ ,dimnames=list(c('prijsindex'
+ ,'gezondheid'
+ ,'tabak')
+ ,1:50))
> y <- array(NA,dim=c(3,50),dimnames=list(c('prijsindex','gezondheid','tabak'),1:50))
> 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
prijsindex gezondheid tabak
1 116.24 112.42 120.58
2 116.03 112.00 120.17
3 115.94 111.72 120.02
4 114.19 111.67 120.49
5 115.74 111.55 120.38
6 115.40 111.33 120.09
7 115.20 111.06 119.62
8 114.82 110.97 118.93
9 114.33 110.81 119.09
10 111.84 110.62 118.59
11 113.16 110.71 117.87
12 112.52 110.51 117.74
13 112.39 110.50 117.61
14 112.24 110.37 117.55
15 112.10 110.38 117.06
16 109.85 110.26 117.08
17 111.89 110.28 117.21
18 111.88 110.25 117.58
19 111.48 110.09 117.27
20 110.98 110.01 117.14
21 110.42 109.75 116.52
22 107.90 109.57 116.16
23 109.46 109.59 114.79
24 109.23 109.45 114.97
25 109.02 109.21 114.66
26 109.04 109.00 114.30
27 109.49 108.83 114.48
28 107.23 108.62 114.96
29 109.00 108.56 115.44
30 109.12 108.41 116.38
31 109.24 108.27 116.50
32 108.92 108.03 116.20
33 109.53 107.67 116.37
34 107.06 107.31 116.46
35 109.11 107.14 115.07
36 109.26 107.02 115.03
37 109.99 106.79 115.15
38 110.17 106.49 114.71
39 110.28 106.14 114.67
40 109.13 105.94 115.49
41 110.15 105.87 114.65
42 109.39 105.71 114.92
43 108.45 105.48 114.17
44 108.23 105.31 112.80
45 107.44 105.09 112.28
46 104.86 104.88 112.05
47 106.23 104.76 111.03
48 105.85 104.62 110.40
49 104.95 104.49 109.08
50 104.46 104.29 107.89
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) gezondheid tabak
-6.4913 0.1941 0.8261
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-3.4928 -0.6266 0.1685 1.0125 1.5901
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -6.4913 8.0729 -0.804 0.425
gezondheid 0.1941 0.1669 1.163 0.251
tabak 0.8261 0.1377 6.001 2.68e-07 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.23 on 47 degrees of freedom
Multiple R-squared: 0.8427, Adjusted R-squared: 0.836
F-statistic: 125.9 on 2 and 47 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,] 0.17141100 0.34282200 0.82858900
[2,] 0.09637325 0.19274649 0.90362675
[3,] 0.09727715 0.19455431 0.90272285
[4,] 0.06792442 0.13584884 0.93207558
[5,] 0.37784109 0.75568219 0.62215891
[6,] 0.30148885 0.60297770 0.69851115
[7,] 0.23027650 0.46055300 0.76972350
[8,] 0.17292213 0.34584426 0.82707787
[9,] 0.12711516 0.25423032 0.87288484
[10,] 0.09862499 0.19724998 0.90137501
[11,] 0.23607255 0.47214510 0.76392745
[12,] 0.19664724 0.39329447 0.80335276
[13,] 0.15800479 0.31600957 0.84199521
[14,] 0.12402011 0.24804022 0.87597989
[15,] 0.09378592 0.18757185 0.90621408
[16,] 0.06558900 0.13117801 0.93441100
[17,] 0.19558594 0.39117189 0.80441406
[18,] 0.17202974 0.34405948 0.82797026
[19,] 0.13063545 0.26127091 0.86936455
[20,] 0.10484829 0.20969658 0.89515171
[21,] 0.10959750 0.21919500 0.89040250
[22,] 0.18780854 0.37561707 0.81219146
[23,] 0.17127733 0.34255465 0.82872267
[24,] 0.14287415 0.28574830 0.85712585
[25,] 0.10169352 0.20338704 0.89830648
[26,] 0.07075815 0.14151631 0.92924185
[27,] 0.05053045 0.10106089 0.94946955
[28,] 0.04066953 0.08133906 0.95933047
[29,] 0.48290694 0.96581387 0.51709306
[30,] 0.62789112 0.74421777 0.37210888
[31,] 0.79924937 0.40150127 0.20075063
[32,] 0.90159749 0.19680502 0.09840251
[33,] 0.96027550 0.07944900 0.03972450
[34,] 0.96656634 0.06686732 0.03343366
[35,] 0.97870746 0.04258509 0.02129254
[36,] 0.96784249 0.06431503 0.03215751
[37,] 0.92941173 0.14117654 0.07058827
[38,] 0.85152885 0.29694230 0.14847115
[39,] 0.73984516 0.52030968 0.26015484
> postscript(file="/var/wessaorg/rcomp/tmp/1gb111321949083.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2lozg1321949083.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3gkrx1321949083.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4ebpx1321949083.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5ft781321949083.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 = 50
Frequency = 1
1 2 3 4 5 6
1.29155242 1.50180329 1.59007985 -0.53849992 1.12567075 1.06795941
7 8 9 10 11 12
1.30865972 1.51616817 0.92504593 -1.11499967 0.78235021 0.28857383
13 14 15 16 17 18
0.26791338 0.19271828 0.45558594 -1.78764167 0.14107751 -0.16877074
19 20 21 22 23 24
-0.28160686 -0.65867844 -0.65599830 -2.84364486 -0.15571469 -0.50724228
25 26 27 28 29 30
-0.41454827 -0.05637104 0.27792518 -2.33785574 -0.95275565 -1.58020888
31 32 33 34 35 36
-1.53216802 -1.55773542 -1.01829374 -3.49276079 -0.26142374 -0.05508292
37 38 39 40 41 42
0.62042934 1.22216923 1.43315919 -0.35545082 1.37209620 0.42009849
43 44 45 46 47 48
0.14435312 1.08916736 0.77146837 -1.57775268 0.65820599 0.82585234
49 50
1.04159448 1.57352720
> postscript(file="/var/wessaorg/rcomp/tmp/6u20s1321949083.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 = 50
Frequency = 1
lag(myerror, k = 1) myerror
0 1.29155242 NA
1 1.50180329 1.29155242
2 1.59007985 1.50180329
3 -0.53849992 1.59007985
4 1.12567075 -0.53849992
5 1.06795941 1.12567075
6 1.30865972 1.06795941
7 1.51616817 1.30865972
8 0.92504593 1.51616817
9 -1.11499967 0.92504593
10 0.78235021 -1.11499967
11 0.28857383 0.78235021
12 0.26791338 0.28857383
13 0.19271828 0.26791338
14 0.45558594 0.19271828
15 -1.78764167 0.45558594
16 0.14107751 -1.78764167
17 -0.16877074 0.14107751
18 -0.28160686 -0.16877074
19 -0.65867844 -0.28160686
20 -0.65599830 -0.65867844
21 -2.84364486 -0.65599830
22 -0.15571469 -2.84364486
23 -0.50724228 -0.15571469
24 -0.41454827 -0.50724228
25 -0.05637104 -0.41454827
26 0.27792518 -0.05637104
27 -2.33785574 0.27792518
28 -0.95275565 -2.33785574
29 -1.58020888 -0.95275565
30 -1.53216802 -1.58020888
31 -1.55773542 -1.53216802
32 -1.01829374 -1.55773542
33 -3.49276079 -1.01829374
34 -0.26142374 -3.49276079
35 -0.05508292 -0.26142374
36 0.62042934 -0.05508292
37 1.22216923 0.62042934
38 1.43315919 1.22216923
39 -0.35545082 1.43315919
40 1.37209620 -0.35545082
41 0.42009849 1.37209620
42 0.14435312 0.42009849
43 1.08916736 0.14435312
44 0.77146837 1.08916736
45 -1.57775268 0.77146837
46 0.65820599 -1.57775268
47 0.82585234 0.65820599
48 1.04159448 0.82585234
49 1.57352720 1.04159448
50 NA 1.57352720
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.50180329 1.29155242
[2,] 1.59007985 1.50180329
[3,] -0.53849992 1.59007985
[4,] 1.12567075 -0.53849992
[5,] 1.06795941 1.12567075
[6,] 1.30865972 1.06795941
[7,] 1.51616817 1.30865972
[8,] 0.92504593 1.51616817
[9,] -1.11499967 0.92504593
[10,] 0.78235021 -1.11499967
[11,] 0.28857383 0.78235021
[12,] 0.26791338 0.28857383
[13,] 0.19271828 0.26791338
[14,] 0.45558594 0.19271828
[15,] -1.78764167 0.45558594
[16,] 0.14107751 -1.78764167
[17,] -0.16877074 0.14107751
[18,] -0.28160686 -0.16877074
[19,] -0.65867844 -0.28160686
[20,] -0.65599830 -0.65867844
[21,] -2.84364486 -0.65599830
[22,] -0.15571469 -2.84364486
[23,] -0.50724228 -0.15571469
[24,] -0.41454827 -0.50724228
[25,] -0.05637104 -0.41454827
[26,] 0.27792518 -0.05637104
[27,] -2.33785574 0.27792518
[28,] -0.95275565 -2.33785574
[29,] -1.58020888 -0.95275565
[30,] -1.53216802 -1.58020888
[31,] -1.55773542 -1.53216802
[32,] -1.01829374 -1.55773542
[33,] -3.49276079 -1.01829374
[34,] -0.26142374 -3.49276079
[35,] -0.05508292 -0.26142374
[36,] 0.62042934 -0.05508292
[37,] 1.22216923 0.62042934
[38,] 1.43315919 1.22216923
[39,] -0.35545082 1.43315919
[40,] 1.37209620 -0.35545082
[41,] 0.42009849 1.37209620
[42,] 0.14435312 0.42009849
[43,] 1.08916736 0.14435312
[44,] 0.77146837 1.08916736
[45,] -1.57775268 0.77146837
[46,] 0.65820599 -1.57775268
[47,] 0.82585234 0.65820599
[48,] 1.04159448 0.82585234
[49,] 1.57352720 1.04159448
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.50180329 1.29155242
2 1.59007985 1.50180329
3 -0.53849992 1.59007985
4 1.12567075 -0.53849992
5 1.06795941 1.12567075
6 1.30865972 1.06795941
7 1.51616817 1.30865972
8 0.92504593 1.51616817
9 -1.11499967 0.92504593
10 0.78235021 -1.11499967
11 0.28857383 0.78235021
12 0.26791338 0.28857383
13 0.19271828 0.26791338
14 0.45558594 0.19271828
15 -1.78764167 0.45558594
16 0.14107751 -1.78764167
17 -0.16877074 0.14107751
18 -0.28160686 -0.16877074
19 -0.65867844 -0.28160686
20 -0.65599830 -0.65867844
21 -2.84364486 -0.65599830
22 -0.15571469 -2.84364486
23 -0.50724228 -0.15571469
24 -0.41454827 -0.50724228
25 -0.05637104 -0.41454827
26 0.27792518 -0.05637104
27 -2.33785574 0.27792518
28 -0.95275565 -2.33785574
29 -1.58020888 -0.95275565
30 -1.53216802 -1.58020888
31 -1.55773542 -1.53216802
32 -1.01829374 -1.55773542
33 -3.49276079 -1.01829374
34 -0.26142374 -3.49276079
35 -0.05508292 -0.26142374
36 0.62042934 -0.05508292
37 1.22216923 0.62042934
38 1.43315919 1.22216923
39 -0.35545082 1.43315919
40 1.37209620 -0.35545082
41 0.42009849 1.37209620
42 0.14435312 0.42009849
43 1.08916736 0.14435312
44 0.77146837 1.08916736
45 -1.57775268 0.77146837
46 0.65820599 -1.57775268
47 0.82585234 0.65820599
48 1.04159448 0.82585234
49 1.57352720 1.04159448
> 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/wessaorg/rcomp/tmp/73j2k1321949083.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8jgbz1321949083.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9rd1d1321949083.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/1020ti1321949083.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/wessaorg/rcomp/tmp/11klgz1321949083.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/wessaorg/rcomp/tmp/12x6wc1321949083.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/wessaorg/rcomp/tmp/13z3ku1321949083.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/wessaorg/rcomp/tmp/146lna1321949083.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/wessaorg/rcomp/tmp/154puo1321949083.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/wessaorg/rcomp/tmp/1656ow1321949083.tab")
+ }
>
> try(system("convert tmp/1gb111321949083.ps tmp/1gb111321949083.png",intern=TRUE))
character(0)
> try(system("convert tmp/2lozg1321949083.ps tmp/2lozg1321949083.png",intern=TRUE))
character(0)
> try(system("convert tmp/3gkrx1321949083.ps tmp/3gkrx1321949083.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ebpx1321949083.ps tmp/4ebpx1321949083.png",intern=TRUE))
character(0)
> try(system("convert tmp/5ft781321949083.ps tmp/5ft781321949083.png",intern=TRUE))
character(0)
> try(system("convert tmp/6u20s1321949083.ps tmp/6u20s1321949083.png",intern=TRUE))
character(0)
> try(system("convert tmp/73j2k1321949083.ps tmp/73j2k1321949083.png",intern=TRUE))
character(0)
> try(system("convert tmp/8jgbz1321949083.ps tmp/8jgbz1321949083.png",intern=TRUE))
character(0)
> try(system("convert tmp/9rd1d1321949083.ps tmp/9rd1d1321949083.png",intern=TRUE))
character(0)
> try(system("convert tmp/1020ti1321949083.ps tmp/1020ti1321949083.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.138 0.502 3.716