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(19,80.2,18,74.8,19,77.8,19,73,22,72,23,75.8,20,72.6,14,71.9,14,74.8,14,72.9,15,72.9,11,79.9,17,74,16,76,20,69.6,24,77.3,23,75.2,20,75.8,21,77.6,19,76.7,23,77,23,77.9,23,76.7,23,71.9,27,73.4,26,72.5,17,73.7,24,69.5,26,74.7,24,72.5,27,72.1,27,70.7,26,71.4,24,69.5,23,73.5,23,72.4,24,74.5,17,72.2,21,73,19,73.3,22,71.3,22,73.6,18,71.3,16,71.2,14,81.4,12,76.1,14,71.1,16,75.7,8,70,3,68.5,0,56.7,5,57.9,1,58.8,1,59.3,3,61.3,6,62.9,7,61.4,8,64.5,14,63.8,14,61.6,13,64.7),dim=c(2,61),dimnames=list(c('indcvtr','dzcg
'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('indcvtr','dzcg
'),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 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '2'
> #'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
dzcg\r indcvtr
1 80.2 19
2 74.8 18
3 77.8 19
4 73.0 19
5 72.0 22
6 75.8 23
7 72.6 20
8 71.9 14
9 74.8 14
10 72.9 14
11 72.9 15
12 79.9 11
13 74.0 17
14 76.0 16
15 69.6 20
16 77.3 24
17 75.2 23
18 75.8 20
19 77.6 21
20 76.7 19
21 77.0 23
22 77.9 23
23 76.7 23
24 71.9 23
25 73.4 27
26 72.5 26
27 73.7 17
28 69.5 24
29 74.7 26
30 72.5 24
31 72.1 27
32 70.7 27
33 71.4 26
34 69.5 24
35 73.5 23
36 72.4 23
37 74.5 24
38 72.2 17
39 73.0 21
40 73.3 19
41 71.3 22
42 73.6 22
43 71.3 18
44 71.2 16
45 81.4 14
46 76.1 12
47 71.1 14
48 75.7 16
49 70.0 8
50 68.5 3
51 56.7 0
52 57.9 5
53 58.8 1
54 59.3 1
55 61.3 3
56 62.9 6
57 61.4 7
58 64.5 8
59 63.8 14
60 61.6 14
61 64.7 13
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) indcvtr
62.7286 0.5132
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-8.313 -3.184 -0.392 2.808 11.527
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 62.72862 1.46519 42.813 < 2e-16 ***
indcvtr 0.51317 0.07852 6.535 1.65e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 4.369 on 59 degrees of freedom
Multiple R-squared: 0.4199, Adjusted R-squared: 0.4101
F-statistic: 42.71 on 1 and 59 DF, p-value: 1.647e-08
> 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,] 3.999484e-01 0.7998967692 0.600051615
[2,] 2.988143e-01 0.5976286955 0.701185652
[3,] 2.317774e-01 0.4635547948 0.768222603
[4,] 2.107813e-01 0.4215626794 0.789218660
[5,] 1.370906e-01 0.2741812554 0.862909372
[6,] 8.623333e-02 0.1724666542 0.913766673
[7,] 5.156298e-02 0.1031259638 0.948437018
[8,] 1.546681e-01 0.3093362055 0.845331897
[9,] 1.068128e-01 0.2136255838 0.893187208
[10,] 8.106224e-02 0.1621244775 0.918937761
[11,] 1.082443e-01 0.2164886068 0.891755697
[12,] 1.030634e-01 0.2061267475 0.896936626
[13,] 6.908950e-02 0.1381789917 0.930910504
[14,] 4.931928e-02 0.0986385620 0.950680719
[15,] 4.678881e-02 0.0935776128 0.953211194
[16,] 3.953047e-02 0.0790609394 0.960469530
[17,] 3.067383e-02 0.0613476635 0.969326168
[18,] 2.828178e-02 0.0565635627 0.971718219
[19,] 2.059707e-02 0.0411941360 0.979402932
[20,] 1.983136e-02 0.0396627115 0.980168644
[21,] 1.376813e-02 0.0275362642 0.986231868
[22,] 1.037876e-02 0.0207575198 0.989621240
[23,] 7.634090e-03 0.0152681792 0.992365910
[24,] 1.288095e-02 0.0257618928 0.987119054
[25,] 7.693983e-03 0.0153879668 0.992306017
[26,] 5.071564e-03 0.0101431280 0.994928436
[27,] 3.663730e-03 0.0073274593 0.996336270
[28,] 3.937154e-03 0.0078743087 0.996062846
[29,] 3.417479e-03 0.0068349576 0.996582521
[30,] 5.571862e-03 0.0111437246 0.994428138
[31,] 3.290778e-03 0.0065815557 0.996709222
[32,] 2.211553e-03 0.0044231059 0.997788447
[33,] 1.293418e-03 0.0025868354 0.998706582
[34,] 8.851393e-04 0.0017702786 0.999114861
[35,] 4.876796e-04 0.0009753591 0.999512320
[36,] 2.529496e-04 0.0005058992 0.999747050
[37,] 2.243350e-04 0.0004486701 0.999775665
[38,] 1.248395e-04 0.0002496789 0.999875161
[39,] 9.645404e-05 0.0001929081 0.999903546
[40,] 7.001945e-05 0.0001400389 0.999929981
[41,] 2.801262e-03 0.0056025245 0.997198738
[42,] 1.242031e-02 0.0248406206 0.987579690
[43,] 1.383326e-02 0.0276665233 0.986166738
[44,] 6.913752e-02 0.1382750363 0.930862482
[45,] 2.929842e-01 0.5859684617 0.707015769
[46,] 9.235822e-01 0.1528356241 0.076417812
[47,] 9.766943e-01 0.0466114777 0.023305739
[48,] 9.930579e-01 0.0138842429 0.006942121
[49,] 9.901760e-01 0.0196479687 0.009823984
[50,] 9.863513e-01 0.0272973931 0.013648697
[51,] 9.663390e-01 0.0673220265 0.033661013
[52,] 9.044471e-01 0.1911057321 0.095552866
> postscript(file="/var/www/html/rcomp/tmp/1izax1260640075.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2k54c1260640075.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3e63c1260640075.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4eow81260640075.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/527eg1260640075.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 7
7.7211616 2.8343311 5.3211616 0.5211616 -2.0183472 1.2684833 -0.3920080
8 9 10 11 12 13 14
1.9870094 4.8870094 2.9870094 2.4738399 11.5265182 2.5475007 5.0606703
15 16 17 18 19 20 21
-3.3920080 2.2553137 0.6684833 2.8079920 4.0948224 4.2211616 2.4684833
22 23 24 25 26 27 28
3.3684833 2.1684833 -2.6315167 -3.1841950 -3.5710255 2.2475007 -5.5446863
29 30 31 32 33 34 35
-1.3710255 -2.5446863 -4.4841950 -5.8841950 -4.6710255 -5.5446863 -1.0315167
36 37 38 39 40 41 42
-2.1315167 -0.5446863 0.7475007 -0.5051776 0.8211616 -2.7183472 -0.4183472
43 44 45 46 47 48 49
-0.6656689 0.2606703 11.4870094 7.2133486 1.1870094 4.7606703 3.1660269
50 51 52 53 54 55 56
4.2318748 -6.0286165 -7.3944644 -4.4417861 -3.9417861 -2.9681252 -2.9076340
57 58 59 60 61
-4.9208035 -2.3339731 -6.1129906 -8.3129906 -4.6998210
> postscript(file="/var/www/html/rcomp/tmp/6n5ar1260640075.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 7.7211616 NA
1 2.8343311 7.7211616
2 5.3211616 2.8343311
3 0.5211616 5.3211616
4 -2.0183472 0.5211616
5 1.2684833 -2.0183472
6 -0.3920080 1.2684833
7 1.9870094 -0.3920080
8 4.8870094 1.9870094
9 2.9870094 4.8870094
10 2.4738399 2.9870094
11 11.5265182 2.4738399
12 2.5475007 11.5265182
13 5.0606703 2.5475007
14 -3.3920080 5.0606703
15 2.2553137 -3.3920080
16 0.6684833 2.2553137
17 2.8079920 0.6684833
18 4.0948224 2.8079920
19 4.2211616 4.0948224
20 2.4684833 4.2211616
21 3.3684833 2.4684833
22 2.1684833 3.3684833
23 -2.6315167 2.1684833
24 -3.1841950 -2.6315167
25 -3.5710255 -3.1841950
26 2.2475007 -3.5710255
27 -5.5446863 2.2475007
28 -1.3710255 -5.5446863
29 -2.5446863 -1.3710255
30 -4.4841950 -2.5446863
31 -5.8841950 -4.4841950
32 -4.6710255 -5.8841950
33 -5.5446863 -4.6710255
34 -1.0315167 -5.5446863
35 -2.1315167 -1.0315167
36 -0.5446863 -2.1315167
37 0.7475007 -0.5446863
38 -0.5051776 0.7475007
39 0.8211616 -0.5051776
40 -2.7183472 0.8211616
41 -0.4183472 -2.7183472
42 -0.6656689 -0.4183472
43 0.2606703 -0.6656689
44 11.4870094 0.2606703
45 7.2133486 11.4870094
46 1.1870094 7.2133486
47 4.7606703 1.1870094
48 3.1660269 4.7606703
49 4.2318748 3.1660269
50 -6.0286165 4.2318748
51 -7.3944644 -6.0286165
52 -4.4417861 -7.3944644
53 -3.9417861 -4.4417861
54 -2.9681252 -3.9417861
55 -2.9076340 -2.9681252
56 -4.9208035 -2.9076340
57 -2.3339731 -4.9208035
58 -6.1129906 -2.3339731
59 -8.3129906 -6.1129906
60 -4.6998210 -8.3129906
61 NA -4.6998210
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 2.8343311 7.7211616
[2,] 5.3211616 2.8343311
[3,] 0.5211616 5.3211616
[4,] -2.0183472 0.5211616
[5,] 1.2684833 -2.0183472
[6,] -0.3920080 1.2684833
[7,] 1.9870094 -0.3920080
[8,] 4.8870094 1.9870094
[9,] 2.9870094 4.8870094
[10,] 2.4738399 2.9870094
[11,] 11.5265182 2.4738399
[12,] 2.5475007 11.5265182
[13,] 5.0606703 2.5475007
[14,] -3.3920080 5.0606703
[15,] 2.2553137 -3.3920080
[16,] 0.6684833 2.2553137
[17,] 2.8079920 0.6684833
[18,] 4.0948224 2.8079920
[19,] 4.2211616 4.0948224
[20,] 2.4684833 4.2211616
[21,] 3.3684833 2.4684833
[22,] 2.1684833 3.3684833
[23,] -2.6315167 2.1684833
[24,] -3.1841950 -2.6315167
[25,] -3.5710255 -3.1841950
[26,] 2.2475007 -3.5710255
[27,] -5.5446863 2.2475007
[28,] -1.3710255 -5.5446863
[29,] -2.5446863 -1.3710255
[30,] -4.4841950 -2.5446863
[31,] -5.8841950 -4.4841950
[32,] -4.6710255 -5.8841950
[33,] -5.5446863 -4.6710255
[34,] -1.0315167 -5.5446863
[35,] -2.1315167 -1.0315167
[36,] -0.5446863 -2.1315167
[37,] 0.7475007 -0.5446863
[38,] -0.5051776 0.7475007
[39,] 0.8211616 -0.5051776
[40,] -2.7183472 0.8211616
[41,] -0.4183472 -2.7183472
[42,] -0.6656689 -0.4183472
[43,] 0.2606703 -0.6656689
[44,] 11.4870094 0.2606703
[45,] 7.2133486 11.4870094
[46,] 1.1870094 7.2133486
[47,] 4.7606703 1.1870094
[48,] 3.1660269 4.7606703
[49,] 4.2318748 3.1660269
[50,] -6.0286165 4.2318748
[51,] -7.3944644 -6.0286165
[52,] -4.4417861 -7.3944644
[53,] -3.9417861 -4.4417861
[54,] -2.9681252 -3.9417861
[55,] -2.9076340 -2.9681252
[56,] -4.9208035 -2.9076340
[57,] -2.3339731 -4.9208035
[58,] -6.1129906 -2.3339731
[59,] -8.3129906 -6.1129906
[60,] -4.6998210 -8.3129906
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 2.8343311 7.7211616
2 5.3211616 2.8343311
3 0.5211616 5.3211616
4 -2.0183472 0.5211616
5 1.2684833 -2.0183472
6 -0.3920080 1.2684833
7 1.9870094 -0.3920080
8 4.8870094 1.9870094
9 2.9870094 4.8870094
10 2.4738399 2.9870094
11 11.5265182 2.4738399
12 2.5475007 11.5265182
13 5.0606703 2.5475007
14 -3.3920080 5.0606703
15 2.2553137 -3.3920080
16 0.6684833 2.2553137
17 2.8079920 0.6684833
18 4.0948224 2.8079920
19 4.2211616 4.0948224
20 2.4684833 4.2211616
21 3.3684833 2.4684833
22 2.1684833 3.3684833
23 -2.6315167 2.1684833
24 -3.1841950 -2.6315167
25 -3.5710255 -3.1841950
26 2.2475007 -3.5710255
27 -5.5446863 2.2475007
28 -1.3710255 -5.5446863
29 -2.5446863 -1.3710255
30 -4.4841950 -2.5446863
31 -5.8841950 -4.4841950
32 -4.6710255 -5.8841950
33 -5.5446863 -4.6710255
34 -1.0315167 -5.5446863
35 -2.1315167 -1.0315167
36 -0.5446863 -2.1315167
37 0.7475007 -0.5446863
38 -0.5051776 0.7475007
39 0.8211616 -0.5051776
40 -2.7183472 0.8211616
41 -0.4183472 -2.7183472
42 -0.6656689 -0.4183472
43 0.2606703 -0.6656689
44 11.4870094 0.2606703
45 7.2133486 11.4870094
46 1.1870094 7.2133486
47 4.7606703 1.1870094
48 3.1660269 4.7606703
49 4.2318748 3.1660269
50 -6.0286165 4.2318748
51 -7.3944644 -6.0286165
52 -4.4417861 -7.3944644
53 -3.9417861 -4.4417861
54 -2.9681252 -3.9417861
55 -2.9076340 -2.9681252
56 -4.9208035 -2.9076340
57 -2.3339731 -4.9208035
58 -6.1129906 -2.3339731
59 -8.3129906 -6.1129906
60 -4.6998210 -8.3129906
> 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/7h8ph1260640075.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8c4tn1260640075.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9mdbu1260640075.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10kwqn1260640075.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11xgh91260640075.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/12f6ph1260640075.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/13jz811260640075.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/14t7ji1260640075.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/15glr41260640075.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/16prw31260640075.tab")
+ }
>
> try(system("convert tmp/1izax1260640075.ps tmp/1izax1260640075.png",intern=TRUE))
character(0)
> try(system("convert tmp/2k54c1260640075.ps tmp/2k54c1260640075.png",intern=TRUE))
character(0)
> try(system("convert tmp/3e63c1260640075.ps tmp/3e63c1260640075.png",intern=TRUE))
character(0)
> try(system("convert tmp/4eow81260640075.ps tmp/4eow81260640075.png",intern=TRUE))
character(0)
> try(system("convert tmp/527eg1260640075.ps tmp/527eg1260640075.png",intern=TRUE))
character(0)
> try(system("convert tmp/6n5ar1260640075.ps tmp/6n5ar1260640075.png",intern=TRUE))
character(0)
> try(system("convert tmp/7h8ph1260640075.ps tmp/7h8ph1260640075.png",intern=TRUE))
character(0)
> try(system("convert tmp/8c4tn1260640075.ps tmp/8c4tn1260640075.png",intern=TRUE))
character(0)
> try(system("convert tmp/9mdbu1260640075.ps tmp/9mdbu1260640075.png",intern=TRUE))
character(0)
> try(system("convert tmp/10kwqn1260640075.ps tmp/10kwqn1260640075.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.442 1.550 2.856