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(1217.00
+ ,1210.00
+ ,31.00
+ ,48.00
+ ,961.00
+ ,2304.00
+ ,1202.00
+ ,1209.00
+ ,34.40
+ ,38.00
+ ,1183.36
+ ,1444.00
+ ,1180.00
+ ,1207.00
+ ,35.60
+ ,37.00
+ ,1267.36
+ ,1369.00
+ ,1167.00
+ ,1206.00
+ ,32.80
+ ,48.00
+ ,1075.84
+ ,2304.00
+ ,1186.00
+ ,1204.00
+ ,23.30
+ ,81.00
+ ,542.89
+ ,6561.00
+ ,1168.00
+ ,1201.00
+ ,20.00
+ ,58.00
+ ,400.00
+ ,3364.00
+ ,1142.00
+ ,1199.00
+ ,16.70
+ ,93.00
+ ,278.89
+ ,8649.00
+ ,1147.00
+ ,1198.00
+ ,17.80
+ ,86.00
+ ,316.84
+ ,7396.00
+ ,1183.00
+ ,1196.00
+ ,21.20
+ ,68.00
+ ,449.44
+ ,4624.00
+ ,1149.00
+ ,1195.00
+ ,23.90
+ ,68.00
+ ,571.21
+ ,4624.00
+ ,1197.00
+ ,1193.00
+ ,28.80
+ ,68.00
+ ,829.44
+ ,4624.00
+ ,1210.00
+ ,1191.00
+ ,25.60
+ ,59.00
+ ,655.36
+ ,3481.00
+ ,1206.00
+ ,1190.00
+ ,29.40
+ ,43.00
+ ,864.36
+ ,1849.00
+ ,1196.00
+ ,1188.00
+ ,22.80
+ ,59.00
+ ,519.84
+ ,3481.00
+ ,1190.00
+ ,1187.00
+ ,16.10
+ ,31.00
+ ,259.21
+ ,961.00
+ ,1175.00
+ ,1185.00
+ ,16.10
+ ,49.00
+ ,259.21
+ ,2401.00
+ ,1186.00
+ ,1183.00
+ ,20.00
+ ,52.00
+ ,400.00
+ ,2704.00
+ ,1172.00
+ ,1182.00
+ ,20.60
+ ,75.00
+ ,424.36
+ ,5625.00
+ ,1152.00
+ ,1185.00
+ ,18.30
+ ,90.00
+ ,334.89
+ ,8100.00
+ ,1154.00
+ ,1179.00
+ ,21.60
+ ,86.00
+ ,466.56
+ ,7396.00
+ ,1168.00
+ ,1177.00
+ ,22.80
+ ,87.00
+ ,519.84
+ ,7569.00
+ ,1180.00
+ ,1175.00
+ ,22.80
+ ,47.00
+ ,519.84
+ ,2209.00
+ ,1169.00
+ ,1174.00
+ ,17.20
+ ,70.00
+ ,295.84
+ ,4900.00
+ ,1166.00
+ ,1170.00
+ ,22.20
+ ,61.00
+ ,492.84
+ ,3721.00
+ ,1177.00
+ ,1169.00
+ ,20.60
+ ,48.00
+ ,424.36
+ ,2304.00
+ ,1168.00
+ ,1167.00
+ ,18.30
+ ,67.00
+ ,334.89
+ ,4489.00
+ ,1160.00
+ ,1166.00
+ ,16.70
+ ,74.00
+ ,278.89
+ ,5476.00
+ ,1147.00
+ ,1164.00
+ ,22.80
+ ,55.00
+ ,519.84
+ ,3025.00
+ ,1161.00
+ ,1162.00
+ ,13.90
+ ,47.00
+ ,193.21
+ ,2209.00
+ ,1143.00
+ ,1161.00
+ ,10.00
+ ,65.00
+ ,100.00
+ ,4225.00
+ ,1161.00
+ ,1159.00
+ ,16.10
+ ,28.00
+ ,259.21
+ ,784.00
+ ,1161.00
+ ,1158.00
+ ,20.60
+ ,30.00
+ ,424.36
+ ,900.00
+ ,1168.00
+ ,1156.00
+ ,19.40
+ ,67.00
+ ,376.36
+ ,4489.00
+ ,1172.00
+ ,1155.00
+ ,25.60
+ ,32.00
+ ,655.36
+ ,1024.00)
+ ,dim=c(6
+ ,34)
+ ,dimnames=list(c('15thbird'
+ ,'Sunset'
+ ,'Temp'
+ ,'humidity'
+ ,'Temp^2'
+ ,'Hum^2')
+ ,1:34))
> y <- array(NA,dim=c(6,34),dimnames=list(c('15thbird','Sunset','Temp','humidity','Temp^2','Hum^2'),1:34))
> 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
15thbird Sunset Temp humidity Temp^2 Hum^2
1 1217 1210 31.0 48 961.00 2304
2 1202 1209 34.4 38 1183.36 1444
3 1180 1207 35.6 37 1267.36 1369
4 1167 1206 32.8 48 1075.84 2304
5 1186 1204 23.3 81 542.89 6561
6 1168 1201 20.0 58 400.00 3364
7 1142 1199 16.7 93 278.89 8649
8 1147 1198 17.8 86 316.84 7396
9 1183 1196 21.2 68 449.44 4624
10 1149 1195 23.9 68 571.21 4624
11 1197 1193 28.8 68 829.44 4624
12 1210 1191 25.6 59 655.36 3481
13 1206 1190 29.4 43 864.36 1849
14 1196 1188 22.8 59 519.84 3481
15 1190 1187 16.1 31 259.21 961
16 1175 1185 16.1 49 259.21 2401
17 1186 1183 20.0 52 400.00 2704
18 1172 1182 20.6 75 424.36 5625
19 1152 1185 18.3 90 334.89 8100
20 1154 1179 21.6 86 466.56 7396
21 1168 1177 22.8 87 519.84 7569
22 1180 1175 22.8 47 519.84 2209
23 1169 1174 17.2 70 295.84 4900
24 1166 1170 22.2 61 492.84 3721
25 1177 1169 20.6 48 424.36 2304
26 1168 1167 18.3 67 334.89 4489
27 1160 1166 16.7 74 278.89 5476
28 1147 1164 22.8 55 519.84 3025
29 1161 1162 13.9 47 193.21 2209
30 1143 1161 10.0 65 100.00 4225
31 1161 1159 16.1 28 259.21 784
32 1161 1158 20.6 30 424.36 900
33 1168 1156 19.4 67 376.36 4489
34 1172 1155 25.6 32 655.36 1024
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Sunset Temp humidity `Temp^2` `Hum^2`
548.77412 0.45792 5.51273 1.09184 -0.10208 -0.01311
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-34.043 -6.412 1.898 7.921 22.846
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 548.774117 240.427948 2.282 0.0303 *
Sunset 0.457920 0.204089 2.244 0.0329 *
Temp 5.512728 2.802577 1.967 0.0592 .
humidity 1.091837 0.875570 1.247 0.2227
`Temp^2` -0.102084 0.060835 -1.678 0.1045
`Hum^2` -0.013113 0.007202 -1.821 0.0793 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 14.31 on 28 degrees of freedom
Multiple R-squared: 0.5445, Adjusted R-squared: 0.4631
F-statistic: 6.693 on 5 and 28 DF, p-value: 0.0003236
> 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,] 0.5289642 0.942071556 0.471035778
[2,] 0.9745896 0.050820716 0.025410358
[3,] 0.9959292 0.008141671 0.004070836
[4,] 0.9960678 0.007864470 0.003932235
[5,] 0.9946837 0.010632570 0.005316285
[6,] 0.9933456 0.013308865 0.006654432
[7,] 0.9892337 0.021532624 0.010766312
[8,] 0.9851907 0.029618656 0.014809328
[9,] 0.9742520 0.051495943 0.025747972
[10,] 0.9508112 0.098377662 0.049188831
[11,] 0.9204557 0.159088604 0.079544302
[12,] 0.9236107 0.152778506 0.076389253
[13,] 0.8607632 0.278473599 0.139236799
[14,] 0.8311130 0.337773940 0.168886970
[15,] 0.7467550 0.506489935 0.253244968
[16,] 0.6218232 0.756353651 0.378176825
[17,] 0.6372081 0.725583863 0.362791931
> postscript(file="/var/wessaorg/rcomp/tmp/1po531331048128.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/251gc1331048128.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3s74c1331048128.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4g5fg1331048128.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/51qg21331048128.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 = 34
Frequency = 1
1 2 3 4 5 6
19.1542540 8.2095846 -10.8064488 -27.2136966 10.4580920 -19.3721784
7 8 9 10 11 12
-7.5409333 -13.0603955 1.9528940 -34.0428322 14.2216875 22.8461693
13 14 15 16 17 18
15.7605273 11.8211984 14.1355739 -0.7192455 4.7669663 3.5941867
19 20 21 22 23 24
1.8428569 -3.0243278 11.8919263 -1.8032565 5.8334568 -8.4214703
25 26 27 28 29 30
0.4792000 3.8474180 4.7084764 -27.8008040 0.8694164 2.0940639
31 32 33 34
-1.0881207 -9.2409619 7.0539429 -1.4072202
> postscript(file="/var/wessaorg/rcomp/tmp/6rne11331048128.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 = 34
Frequency = 1
lag(myerror, k = 1) myerror
0 19.1542540 NA
1 8.2095846 19.1542540
2 -10.8064488 8.2095846
3 -27.2136966 -10.8064488
4 10.4580920 -27.2136966
5 -19.3721784 10.4580920
6 -7.5409333 -19.3721784
7 -13.0603955 -7.5409333
8 1.9528940 -13.0603955
9 -34.0428322 1.9528940
10 14.2216875 -34.0428322
11 22.8461693 14.2216875
12 15.7605273 22.8461693
13 11.8211984 15.7605273
14 14.1355739 11.8211984
15 -0.7192455 14.1355739
16 4.7669663 -0.7192455
17 3.5941867 4.7669663
18 1.8428569 3.5941867
19 -3.0243278 1.8428569
20 11.8919263 -3.0243278
21 -1.8032565 11.8919263
22 5.8334568 -1.8032565
23 -8.4214703 5.8334568
24 0.4792000 -8.4214703
25 3.8474180 0.4792000
26 4.7084764 3.8474180
27 -27.8008040 4.7084764
28 0.8694164 -27.8008040
29 2.0940639 0.8694164
30 -1.0881207 2.0940639
31 -9.2409619 -1.0881207
32 7.0539429 -9.2409619
33 -1.4072202 7.0539429
34 NA -1.4072202
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 8.2095846 19.1542540
[2,] -10.8064488 8.2095846
[3,] -27.2136966 -10.8064488
[4,] 10.4580920 -27.2136966
[5,] -19.3721784 10.4580920
[6,] -7.5409333 -19.3721784
[7,] -13.0603955 -7.5409333
[8,] 1.9528940 -13.0603955
[9,] -34.0428322 1.9528940
[10,] 14.2216875 -34.0428322
[11,] 22.8461693 14.2216875
[12,] 15.7605273 22.8461693
[13,] 11.8211984 15.7605273
[14,] 14.1355739 11.8211984
[15,] -0.7192455 14.1355739
[16,] 4.7669663 -0.7192455
[17,] 3.5941867 4.7669663
[18,] 1.8428569 3.5941867
[19,] -3.0243278 1.8428569
[20,] 11.8919263 -3.0243278
[21,] -1.8032565 11.8919263
[22,] 5.8334568 -1.8032565
[23,] -8.4214703 5.8334568
[24,] 0.4792000 -8.4214703
[25,] 3.8474180 0.4792000
[26,] 4.7084764 3.8474180
[27,] -27.8008040 4.7084764
[28,] 0.8694164 -27.8008040
[29,] 2.0940639 0.8694164
[30,] -1.0881207 2.0940639
[31,] -9.2409619 -1.0881207
[32,] 7.0539429 -9.2409619
[33,] -1.4072202 7.0539429
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 8.2095846 19.1542540
2 -10.8064488 8.2095846
3 -27.2136966 -10.8064488
4 10.4580920 -27.2136966
5 -19.3721784 10.4580920
6 -7.5409333 -19.3721784
7 -13.0603955 -7.5409333
8 1.9528940 -13.0603955
9 -34.0428322 1.9528940
10 14.2216875 -34.0428322
11 22.8461693 14.2216875
12 15.7605273 22.8461693
13 11.8211984 15.7605273
14 14.1355739 11.8211984
15 -0.7192455 14.1355739
16 4.7669663 -0.7192455
17 3.5941867 4.7669663
18 1.8428569 3.5941867
19 -3.0243278 1.8428569
20 11.8919263 -3.0243278
21 -1.8032565 11.8919263
22 5.8334568 -1.8032565
23 -8.4214703 5.8334568
24 0.4792000 -8.4214703
25 3.8474180 0.4792000
26 4.7084764 3.8474180
27 -27.8008040 4.7084764
28 0.8694164 -27.8008040
29 2.0940639 0.8694164
30 -1.0881207 2.0940639
31 -9.2409619 -1.0881207
32 7.0539429 -9.2409619
33 -1.4072202 7.0539429
> 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/71jqu1331048128.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8t70j1331048128.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9v5n11331048128.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/1073ez1331048128.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11aicr1331048128.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/12or8q1331048128.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/13ips91331048128.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/14d6af1331048128.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/15p19j1331048128.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/1689241331048128.tab")
+ }
>
> try(system("convert tmp/1po531331048128.ps tmp/1po531331048128.png",intern=TRUE))
character(0)
> try(system("convert tmp/251gc1331048128.ps tmp/251gc1331048128.png",intern=TRUE))
character(0)
> try(system("convert tmp/3s74c1331048128.ps tmp/3s74c1331048128.png",intern=TRUE))
character(0)
> try(system("convert tmp/4g5fg1331048128.ps tmp/4g5fg1331048128.png",intern=TRUE))
character(0)
> try(system("convert tmp/51qg21331048128.ps tmp/51qg21331048128.png",intern=TRUE))
character(0)
> try(system("convert tmp/6rne11331048128.ps tmp/6rne11331048128.png",intern=TRUE))
character(0)
> try(system("convert tmp/71jqu1331048128.ps tmp/71jqu1331048128.png",intern=TRUE))
character(0)
> try(system("convert tmp/8t70j1331048128.ps tmp/8t70j1331048128.png",intern=TRUE))
character(0)
> try(system("convert tmp/9v5n11331048128.ps tmp/9v5n11331048128.png",intern=TRUE))
character(0)
> try(system("convert tmp/1073ez1331048128.ps tmp/1073ez1331048128.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.067 0.658 3.753