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(20366,1,22782,1,19169,1,13807,1,29743,1,25591,1,29096,1,26482,1,22405,1,27044,1,17970,1,18730,1,19684,1,19785,1,18479,1,10698,1,31956,1,29506,1,34506,1,27165,1,26736,1,23691,1,18157,1,17328,1,18205,1,20995,1,17382,1,9367,1,31124,1,26551,1,30651,1,25859,1,25100,1,25778,1,20418,1,18688,1,20424,1,24776,1,19814,1,12738,1,31566,1,30111,1,30019,1,31934,1,25826,1,26835,1,20205,1,17789,1,20520,1,22518,1,15572,0,11509,0,25447,0,24090,0,27786,0,26195,0,20516,0,22759,0,19028,0,16971,0),dim=c(2,60),dimnames=list(c('wagens','dummies'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('wagens','dummies'),1:60))
> 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
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
wagens dummies
1 20366 1
2 22782 1
3 19169 1
4 13807 1
5 29743 1
6 25591 1
7 29096 1
8 26482 1
9 22405 1
10 27044 1
11 17970 1
12 18730 1
13 19684 1
14 19785 1
15 18479 1
16 10698 1
17 31956 1
18 29506 1
19 34506 1
20 27165 1
21 26736 1
22 23691 1
23 18157 1
24 17328 1
25 18205 1
26 20995 1
27 17382 1
28 9367 1
29 31124 1
30 26551 1
31 30651 1
32 25859 1
33 25100 1
34 25778 1
35 20418 1
36 18688 1
37 20424 1
38 24776 1
39 19814 1
40 12738 1
41 31566 1
42 30111 1
43 30019 1
44 31934 1
45 25826 1
46 26835 1
47 20205 1
48 17789 1
49 20520 1
50 22518 1
51 15572 0
52 11509 0
53 25447 0
54 24090 0
55 27786 0
56 26195 0
57 20516 0
58 22759 0
59 19028 0
60 16971 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) dummies
20987 2134
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-13754.4 -4110.1 -405.3 3952.9 11384.6
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 20987 1818 11.543 <2e-16 ***
dummies 2134 1992 1.071 0.288
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5750 on 58 degrees of freedom
Multiple R-squared: 0.01941, Adjusted R-squared: 0.002503
F-statistic: 1.148 on 1 and 58 DF, p-value: 0.2884
> 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,] 0.7330093 0.5339815 0.2669907
[2,] 0.6425600 0.7148800 0.3574400
[3,] 0.6574996 0.6850009 0.3425004
[4,] 0.5680214 0.8639573 0.4319786
[5,] 0.4470440 0.8940880 0.5529560
[6,] 0.3776259 0.7552519 0.6223741
[7,] 0.3653893 0.7307787 0.6346107
[8,] 0.3217956 0.6435911 0.6782044
[9,] 0.2596890 0.5193781 0.7403110
[10,] 0.2031237 0.4062474 0.7968763
[11,] 0.1716949 0.3433898 0.8283051
[12,] 0.4148559 0.8297118 0.5851441
[13,] 0.5734411 0.8531177 0.4265589
[14,] 0.6031982 0.7936036 0.3968018
[15,] 0.7944388 0.4111224 0.2055612
[16,] 0.7606364 0.4787271 0.2393636
[17,] 0.7178430 0.5643139 0.2821570
[18,] 0.6472811 0.7054378 0.3527189
[19,] 0.6255659 0.7488682 0.3744341
[20,] 0.6212901 0.7574197 0.3787099
[21,] 0.5968945 0.8062109 0.4031055
[22,] 0.5302807 0.9394386 0.4697193
[23,] 0.5260581 0.9478837 0.4739419
[24,] 0.8311685 0.3376630 0.1688315
[25,] 0.8672380 0.2655240 0.1327620
[26,] 0.8366902 0.3266196 0.1633098
[27,] 0.8624889 0.2750222 0.1375111
[28,] 0.8252579 0.3494842 0.1747421
[29,] 0.7765401 0.4469198 0.2234599
[30,] 0.7264470 0.5471059 0.2735530
[31,] 0.6750722 0.6498557 0.3249278
[32,] 0.6509368 0.6981263 0.3490632
[33,] 0.5989220 0.8021560 0.4010780
[34,] 0.5239065 0.9521871 0.4760935
[35,] 0.4816831 0.9633662 0.5183169
[36,] 0.7235453 0.5529095 0.2764547
[37,] 0.7598531 0.4802939 0.2401469
[38,] 0.7648013 0.4703973 0.2351987
[39,] 0.7786528 0.4426944 0.2213472
[40,] 0.8712601 0.2574798 0.1287399
[41,] 0.8426468 0.3147065 0.1573532
[42,] 0.8470083 0.3059834 0.1529917
[43,] 0.7831081 0.4337838 0.2168919
[44,] 0.7340075 0.5319851 0.2659925
[45,] 0.6473465 0.7053071 0.3526535
[46,] 0.5397035 0.9205930 0.4602965
[47,] 0.5210376 0.9579248 0.4789624
[48,] 0.8139590 0.3720819 0.1860410
[49,] 0.7588039 0.4823922 0.2411961
[50,] 0.6426314 0.7147373 0.3573686
[51,] 0.6997152 0.6005696 0.3002848
> postscript(file="/var/www/html/rcomp/tmp/1z09u1261769933.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/246r71261769933.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/355k21261769933.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/418ma1261769933.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5zl2x1261769933.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 = 60
Frequency = 1
1 2 3 4 5 6 7 8
-2755.38 -339.38 -3952.38 -9314.38 6621.62 2469.62 5974.62 3360.62
9 10 11 12 13 14 15 16
-716.38 3922.62 -5151.38 -4391.38 -3437.38 -3336.38 -4642.38 -12423.38
17 18 19 20 21 22 23 24
8834.62 6384.62 11384.62 4043.62 3614.62 569.62 -4964.38 -5793.38
25 26 27 28 29 30 31 32
-4916.38 -2126.38 -5739.38 -13754.38 8002.62 3429.62 7529.62 2737.62
33 34 35 36 37 38 39 40
1978.62 2656.62 -2703.38 -4433.38 -2697.38 1654.62 -3307.38 -10383.38
41 42 43 44 45 46 47 48
8444.62 6989.62 6897.62 8812.62 2704.62 3713.62 -2916.38 -5332.38
49 50 51 52 53 54 55 56
-2601.38 -603.38 -5415.30 -9478.30 4459.70 3102.70 6798.70 5207.70
57 58 59 60
-471.30 1771.70 -1959.30 -4016.30
> postscript(file="/var/www/html/rcomp/tmp/61dyy1261769933.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 -2755.38 NA
1 -339.38 -2755.38
2 -3952.38 -339.38
3 -9314.38 -3952.38
4 6621.62 -9314.38
5 2469.62 6621.62
6 5974.62 2469.62
7 3360.62 5974.62
8 -716.38 3360.62
9 3922.62 -716.38
10 -5151.38 3922.62
11 -4391.38 -5151.38
12 -3437.38 -4391.38
13 -3336.38 -3437.38
14 -4642.38 -3336.38
15 -12423.38 -4642.38
16 8834.62 -12423.38
17 6384.62 8834.62
18 11384.62 6384.62
19 4043.62 11384.62
20 3614.62 4043.62
21 569.62 3614.62
22 -4964.38 569.62
23 -5793.38 -4964.38
24 -4916.38 -5793.38
25 -2126.38 -4916.38
26 -5739.38 -2126.38
27 -13754.38 -5739.38
28 8002.62 -13754.38
29 3429.62 8002.62
30 7529.62 3429.62
31 2737.62 7529.62
32 1978.62 2737.62
33 2656.62 1978.62
34 -2703.38 2656.62
35 -4433.38 -2703.38
36 -2697.38 -4433.38
37 1654.62 -2697.38
38 -3307.38 1654.62
39 -10383.38 -3307.38
40 8444.62 -10383.38
41 6989.62 8444.62
42 6897.62 6989.62
43 8812.62 6897.62
44 2704.62 8812.62
45 3713.62 2704.62
46 -2916.38 3713.62
47 -5332.38 -2916.38
48 -2601.38 -5332.38
49 -603.38 -2601.38
50 -5415.30 -603.38
51 -9478.30 -5415.30
52 4459.70 -9478.30
53 3102.70 4459.70
54 6798.70 3102.70
55 5207.70 6798.70
56 -471.30 5207.70
57 1771.70 -471.30
58 -1959.30 1771.70
59 -4016.30 -1959.30
60 NA -4016.30
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -339.38 -2755.38
[2,] -3952.38 -339.38
[3,] -9314.38 -3952.38
[4,] 6621.62 -9314.38
[5,] 2469.62 6621.62
[6,] 5974.62 2469.62
[7,] 3360.62 5974.62
[8,] -716.38 3360.62
[9,] 3922.62 -716.38
[10,] -5151.38 3922.62
[11,] -4391.38 -5151.38
[12,] -3437.38 -4391.38
[13,] -3336.38 -3437.38
[14,] -4642.38 -3336.38
[15,] -12423.38 -4642.38
[16,] 8834.62 -12423.38
[17,] 6384.62 8834.62
[18,] 11384.62 6384.62
[19,] 4043.62 11384.62
[20,] 3614.62 4043.62
[21,] 569.62 3614.62
[22,] -4964.38 569.62
[23,] -5793.38 -4964.38
[24,] -4916.38 -5793.38
[25,] -2126.38 -4916.38
[26,] -5739.38 -2126.38
[27,] -13754.38 -5739.38
[28,] 8002.62 -13754.38
[29,] 3429.62 8002.62
[30,] 7529.62 3429.62
[31,] 2737.62 7529.62
[32,] 1978.62 2737.62
[33,] 2656.62 1978.62
[34,] -2703.38 2656.62
[35,] -4433.38 -2703.38
[36,] -2697.38 -4433.38
[37,] 1654.62 -2697.38
[38,] -3307.38 1654.62
[39,] -10383.38 -3307.38
[40,] 8444.62 -10383.38
[41,] 6989.62 8444.62
[42,] 6897.62 6989.62
[43,] 8812.62 6897.62
[44,] 2704.62 8812.62
[45,] 3713.62 2704.62
[46,] -2916.38 3713.62
[47,] -5332.38 -2916.38
[48,] -2601.38 -5332.38
[49,] -603.38 -2601.38
[50,] -5415.30 -603.38
[51,] -9478.30 -5415.30
[52,] 4459.70 -9478.30
[53,] 3102.70 4459.70
[54,] 6798.70 3102.70
[55,] 5207.70 6798.70
[56,] -471.30 5207.70
[57,] 1771.70 -471.30
[58,] -1959.30 1771.70
[59,] -4016.30 -1959.30
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -339.38 -2755.38
2 -3952.38 -339.38
3 -9314.38 -3952.38
4 6621.62 -9314.38
5 2469.62 6621.62
6 5974.62 2469.62
7 3360.62 5974.62
8 -716.38 3360.62
9 3922.62 -716.38
10 -5151.38 3922.62
11 -4391.38 -5151.38
12 -3437.38 -4391.38
13 -3336.38 -3437.38
14 -4642.38 -3336.38
15 -12423.38 -4642.38
16 8834.62 -12423.38
17 6384.62 8834.62
18 11384.62 6384.62
19 4043.62 11384.62
20 3614.62 4043.62
21 569.62 3614.62
22 -4964.38 569.62
23 -5793.38 -4964.38
24 -4916.38 -5793.38
25 -2126.38 -4916.38
26 -5739.38 -2126.38
27 -13754.38 -5739.38
28 8002.62 -13754.38
29 3429.62 8002.62
30 7529.62 3429.62
31 2737.62 7529.62
32 1978.62 2737.62
33 2656.62 1978.62
34 -2703.38 2656.62
35 -4433.38 -2703.38
36 -2697.38 -4433.38
37 1654.62 -2697.38
38 -3307.38 1654.62
39 -10383.38 -3307.38
40 8444.62 -10383.38
41 6989.62 8444.62
42 6897.62 6989.62
43 8812.62 6897.62
44 2704.62 8812.62
45 3713.62 2704.62
46 -2916.38 3713.62
47 -5332.38 -2916.38
48 -2601.38 -5332.38
49 -603.38 -2601.38
50 -5415.30 -603.38
51 -9478.30 -5415.30
52 4459.70 -9478.30
53 3102.70 4459.70
54 6798.70 3102.70
55 5207.70 6798.70
56 -471.30 5207.70
57 1771.70 -471.30
58 -1959.30 1771.70
59 -4016.30 -1959.30
> 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/78umr1261769933.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8ral51261769933.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9rlk91261769933.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/1025pf1261769933.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11803y1261769933.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/12mnn81261769933.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/13wsvf1261769933.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/14c32b1261769933.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/151wt61261769933.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/16kmtl1261769933.tab")
+ }
>
> try(system("convert tmp/1z09u1261769933.ps tmp/1z09u1261769933.png",intern=TRUE))
character(0)
> try(system("convert tmp/246r71261769933.ps tmp/246r71261769933.png",intern=TRUE))
character(0)
> try(system("convert tmp/355k21261769933.ps tmp/355k21261769933.png",intern=TRUE))
character(0)
> try(system("convert tmp/418ma1261769933.ps tmp/418ma1261769933.png",intern=TRUE))
character(0)
> try(system("convert tmp/5zl2x1261769933.ps tmp/5zl2x1261769933.png",intern=TRUE))
character(0)
> try(system("convert tmp/61dyy1261769933.ps tmp/61dyy1261769933.png",intern=TRUE))
character(0)
> try(system("convert tmp/78umr1261769933.ps tmp/78umr1261769933.png",intern=TRUE))
character(0)
> try(system("convert tmp/8ral51261769933.ps tmp/8ral51261769933.png",intern=TRUE))
character(0)
> try(system("convert tmp/9rlk91261769933.ps tmp/9rlk91261769933.png",intern=TRUE))
character(0)
> try(system("convert tmp/1025pf1261769933.ps tmp/1025pf1261769933.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.393 1.509 3.634