R version 2.12.0 (2010-10-15)
Copyright (C) 2010 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.
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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
+ ,19.00
+ ,30.00
+ ,1202.00
+ ,1209.00
+ ,34.40
+ ,38.00
+ ,1183.36
+ ,1444.00
+ ,18.30
+ ,29.95
+ ,1180.00
+ ,1207.00
+ ,35.60
+ ,37.00
+ ,1267.36
+ ,1369.00
+ ,18.90
+ ,29.94
+ ,1167.00
+ ,1206.00
+ ,32.80
+ ,48.00
+ ,1075.84
+ ,2304.00
+ ,20.60
+ ,29.83
+ ,1186.00
+ ,1204.00
+ ,23.30
+ ,81.00
+ ,542.89
+ ,6561.00
+ ,20.00
+ ,29.85
+ ,1168.00
+ ,1201.00
+ ,20.00
+ ,58.00
+ ,400.00
+ ,3364.00
+ ,11.76
+ ,29.92
+ ,1142.00
+ ,1199.00
+ ,16.70
+ ,93.00
+ ,278.89
+ ,8649.00
+ ,15.60
+ ,29.95
+ ,1147.00
+ ,1198.00
+ ,17.80
+ ,86.00
+ ,316.84
+ ,7396.00
+ ,15.60
+ ,29.94
+ ,1183.00
+ ,1196.00
+ ,21.20
+ ,68.00
+ ,449.44
+ ,4624.00
+ ,15.80
+ ,29.94
+ ,1149.00
+ ,1195.00
+ ,23.90
+ ,68.00
+ ,571.21
+ ,4624.00
+ ,17.80
+ ,30.00
+ ,1197.00
+ ,1193.00
+ ,28.80
+ ,68.00
+ ,829.44
+ ,4624.00
+ ,16.70
+ ,30.03
+ ,1210.00
+ ,1191.00
+ ,25.60
+ ,59.00
+ ,655.36
+ ,3481.00
+ ,17.20
+ ,29.99
+ ,1206.00
+ ,1190.00
+ ,29.40
+ ,43.00
+ ,864.36
+ ,1849.00
+ ,15.60
+ ,29.89
+ ,1196.00
+ ,1188.00
+ ,22.80
+ ,59.00
+ ,519.84
+ ,3481.00
+ ,14.40
+ ,29.98
+ ,1190.00
+ ,1187.00
+ ,16.10
+ ,31.00
+ ,259.21
+ ,961.00
+ ,-0.60
+ ,30.26
+ ,1175.00
+ ,1185.00
+ ,16.10
+ ,49.00
+ ,259.21
+ ,2401.00
+ ,5.60
+ ,30.26
+ ,1186.00
+ ,1183.00
+ ,20.00
+ ,52.00
+ ,400.00
+ ,2704.00
+ ,10.08
+ ,30.23
+ ,1172.00
+ ,1182.00
+ ,20.60
+ ,75.00
+ ,424.36
+ ,5625.00
+ ,16.10
+ ,30.16
+ ,1152.00
+ ,1185.00
+ ,18.30
+ ,90.00
+ ,334.89
+ ,8100.00
+ ,16.70
+ ,30.00
+ ,1154.00
+ ,1179.00
+ ,21.60
+ ,86.00
+ ,466.56
+ ,7396.00
+ ,18.30
+ ,30.60
+ ,1168.00
+ ,1177.00
+ ,22.80
+ ,87.00
+ ,519.84
+ ,7569.00
+ ,20.60
+ ,30.00
+ ,1180.00
+ ,1175.00
+ ,22.80
+ ,47.00
+ ,519.84
+ ,2209.00
+ ,11.10
+ ,30.06
+ ,1169.00
+ ,1174.00
+ ,17.20
+ ,70.00
+ ,295.84
+ ,4900.00
+ ,11.70
+ ,30.01
+ ,1166.00
+ ,1170.00
+ ,22.20
+ ,61.00
+ ,492.84
+ ,3721.00
+ ,14.40
+ ,29.86
+ ,1177.00
+ ,1169.00
+ ,20.60
+ ,48.00
+ ,424.36
+ ,2304.00
+ ,9.40
+ ,29.82
+ ,1168.00
+ ,1167.00
+ ,18.30
+ ,67.00
+ ,334.89
+ ,4489.00
+ ,12.20
+ ,29.83
+ ,1160.00
+ ,1166.00
+ ,16.70
+ ,74.00
+ ,278.89
+ ,5476.00
+ ,12.20
+ ,29.83
+ ,1147.00
+ ,1164.00
+ ,22.80
+ ,55.00
+ ,519.84
+ ,3025.00
+ ,13.30
+ ,29.71
+ ,1161.00
+ ,1162.00
+ ,13.90
+ ,47.00
+ ,193.21
+ ,2209.00
+ ,2.80
+ ,29.98
+ ,1143.00
+ ,1161.00
+ ,10.00
+ ,65.00
+ ,100.00
+ ,4225.00
+ ,3.90
+ ,30.18
+ ,1161.00
+ ,1159.00
+ ,16.10
+ ,28.00
+ ,259.21
+ ,784.00
+ ,-2.20
+ ,30.88
+ ,1161.00
+ ,1158.00
+ ,20.60
+ ,30.00
+ ,424.36
+ ,900.00
+ ,5.00
+ ,30.13
+ ,1168.00
+ ,1156.00
+ ,19.40
+ ,67.00
+ ,376.36
+ ,4489.00
+ ,13.30
+ ,30.24
+ ,1172.00
+ ,1155.00
+ ,25.60
+ ,32.00
+ ,655.36
+ ,1024.00
+ ,7.80
+ ,30.24)
+ ,dim=c(8
+ ,34)
+ ,dimnames=list(c('15thbird'
+ ,'Sunset'
+ ,'Temp'
+ ,'humidity'
+ ,'Temp^2'
+ ,'Hum^2'
+ ,'Dew'
+ ,'pressure')
+ ,1:34))
> y <- array(NA,dim=c(8,34),dimnames=list(c('15thbird','Sunset','Temp','humidity','Temp^2','Hum^2','Dew','pressure'),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 Dew pressure
1 1217 1210 31.0 48 961.00 2304 19.00 30.00
2 1202 1209 34.4 38 1183.36 1444 18.30 29.95
3 1180 1207 35.6 37 1267.36 1369 18.90 29.94
4 1167 1206 32.8 48 1075.84 2304 20.60 29.83
5 1186 1204 23.3 81 542.89 6561 20.00 29.85
6 1168 1201 20.0 58 400.00 3364 11.76 29.92
7 1142 1199 16.7 93 278.89 8649 15.60 29.95
8 1147 1198 17.8 86 316.84 7396 15.60 29.94
9 1183 1196 21.2 68 449.44 4624 15.80 29.94
10 1149 1195 23.9 68 571.21 4624 17.80 30.00
11 1197 1193 28.8 68 829.44 4624 16.70 30.03
12 1210 1191 25.6 59 655.36 3481 17.20 29.99
13 1206 1190 29.4 43 864.36 1849 15.60 29.89
14 1196 1188 22.8 59 519.84 3481 14.40 29.98
15 1190 1187 16.1 31 259.21 961 -0.60 30.26
16 1175 1185 16.1 49 259.21 2401 5.60 30.26
17 1186 1183 20.0 52 400.00 2704 10.08 30.23
18 1172 1182 20.6 75 424.36 5625 16.10 30.16
19 1152 1185 18.3 90 334.89 8100 16.70 30.00
20 1154 1179 21.6 86 466.56 7396 18.30 30.60
21 1168 1177 22.8 87 519.84 7569 20.60 30.00
22 1180 1175 22.8 47 519.84 2209 11.10 30.06
23 1169 1174 17.2 70 295.84 4900 11.70 30.01
24 1166 1170 22.2 61 492.84 3721 14.40 29.86
25 1177 1169 20.6 48 424.36 2304 9.40 29.82
26 1168 1167 18.3 67 334.89 4489 12.20 29.83
27 1160 1166 16.7 74 278.89 5476 12.20 29.83
28 1147 1164 22.8 55 519.84 3025 13.30 29.71
29 1161 1162 13.9 47 193.21 2209 2.80 29.98
30 1143 1161 10.0 65 100.00 4225 3.90 30.18
31 1161 1159 16.1 28 259.21 784 -2.20 30.88
32 1161 1158 20.6 30 424.36 900 5.00 30.13
33 1168 1156 19.4 67 376.36 4489 13.30 30.24
34 1172 1155 25.6 32 655.36 1024 7.80 30.24
> 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`
153.35011 0.50176 8.11586 2.45122 -0.11223 -0.01931
Dew pressure
-2.40327 8.85446
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-34.065 -6.509 2.313 6.693 23.225
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 153.35011 504.81619 0.304 0.7637
Sunset 0.50176 0.20829 2.409 0.0234 *
Temp 8.11586 4.04376 2.007 0.0553 .
humidity 2.45122 1.44761 1.693 0.1024
`Temp^2` -0.11223 0.06264 -1.792 0.0848 .
`Hum^2` -0.01931 0.00869 -2.222 0.0352 *
Dew -2.40327 2.74925 -0.874 0.3900
pressure 8.85446 14.15183 0.626 0.5370
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 14.39 on 26 degrees of freedom
Multiple R-squared: 0.5719, Adjusted R-squared: 0.4567
F-statistic: 4.963 on 7 and 26 DF, p-value: 0.001150
> 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,] 0.9800965 0.03980708 0.019903540
[2,] 0.9927838 0.01443244 0.007216222
[3,] 0.9882936 0.02341279 0.011706395
[4,] 0.9844989 0.03100217 0.015501085
[5,] 0.9811040 0.03779210 0.018896050
[6,] 0.9682564 0.06348727 0.031743637
[7,] 0.9443213 0.11135733 0.055678667
[8,] 0.8948482 0.21030351 0.105151756
[9,] 0.8296857 0.34062852 0.170314258
[10,] 0.8746475 0.25070510 0.125352548
[11,] 0.7708265 0.45834704 0.229173518
[12,] 0.6870408 0.62591838 0.312959191
[13,] 0.5364628 0.92707446 0.463537229
> postscript(file="/var/www/rcomp/tmp/1fdld1331049287.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2ivzp1331049287.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/36fuz1331049287.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4n1xm1331049287.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5fm8m1331049287.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 7
19.641498 9.171160 -9.603443 -24.720876 12.262781 -19.264910 -5.848105
8 9 10 11 12 13 14
-11.962888 3.404028 -34.065362 1.242678 23.225277 17.089008 11.604775
15 16 17 18 19 20 21
12.676761 -2.735079 2.947164 2.427146 3.429496 -8.821556 14.152219
22 23 24 25 26 27 28
-1.659092 5.621368 -6.729775 2.913262 5.801591 6.904152 -24.606311
29 30 31 32 33 34
2.198075 1.570209 -7.673137 -3.875841 6.061011 -2.777286
> postscript(file="/var/www/rcomp/tmp/6cih31331049287.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 19.641498 NA
1 9.171160 19.641498
2 -9.603443 9.171160
3 -24.720876 -9.603443
4 12.262781 -24.720876
5 -19.264910 12.262781
6 -5.848105 -19.264910
7 -11.962888 -5.848105
8 3.404028 -11.962888
9 -34.065362 3.404028
10 1.242678 -34.065362
11 23.225277 1.242678
12 17.089008 23.225277
13 11.604775 17.089008
14 12.676761 11.604775
15 -2.735079 12.676761
16 2.947164 -2.735079
17 2.427146 2.947164
18 3.429496 2.427146
19 -8.821556 3.429496
20 14.152219 -8.821556
21 -1.659092 14.152219
22 5.621368 -1.659092
23 -6.729775 5.621368
24 2.913262 -6.729775
25 5.801591 2.913262
26 6.904152 5.801591
27 -24.606311 6.904152
28 2.198075 -24.606311
29 1.570209 2.198075
30 -7.673137 1.570209
31 -3.875841 -7.673137
32 6.061011 -3.875841
33 -2.777286 6.061011
34 NA -2.777286
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 9.171160 19.641498
[2,] -9.603443 9.171160
[3,] -24.720876 -9.603443
[4,] 12.262781 -24.720876
[5,] -19.264910 12.262781
[6,] -5.848105 -19.264910
[7,] -11.962888 -5.848105
[8,] 3.404028 -11.962888
[9,] -34.065362 3.404028
[10,] 1.242678 -34.065362
[11,] 23.225277 1.242678
[12,] 17.089008 23.225277
[13,] 11.604775 17.089008
[14,] 12.676761 11.604775
[15,] -2.735079 12.676761
[16,] 2.947164 -2.735079
[17,] 2.427146 2.947164
[18,] 3.429496 2.427146
[19,] -8.821556 3.429496
[20,] 14.152219 -8.821556
[21,] -1.659092 14.152219
[22,] 5.621368 -1.659092
[23,] -6.729775 5.621368
[24,] 2.913262 -6.729775
[25,] 5.801591 2.913262
[26,] 6.904152 5.801591
[27,] -24.606311 6.904152
[28,] 2.198075 -24.606311
[29,] 1.570209 2.198075
[30,] -7.673137 1.570209
[31,] -3.875841 -7.673137
[32,] 6.061011 -3.875841
[33,] -2.777286 6.061011
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 9.171160 19.641498
2 -9.603443 9.171160
3 -24.720876 -9.603443
4 12.262781 -24.720876
5 -19.264910 12.262781
6 -5.848105 -19.264910
7 -11.962888 -5.848105
8 3.404028 -11.962888
9 -34.065362 3.404028
10 1.242678 -34.065362
11 23.225277 1.242678
12 17.089008 23.225277
13 11.604775 17.089008
14 12.676761 11.604775
15 -2.735079 12.676761
16 2.947164 -2.735079
17 2.427146 2.947164
18 3.429496 2.427146
19 -8.821556 3.429496
20 14.152219 -8.821556
21 -1.659092 14.152219
22 5.621368 -1.659092
23 -6.729775 5.621368
24 2.913262 -6.729775
25 5.801591 2.913262
26 6.904152 5.801591
27 -24.606311 6.904152
28 2.198075 -24.606311
29 1.570209 2.198075
30 -7.673137 1.570209
31 -3.875841 -7.673137
32 6.061011 -3.875841
33 -2.777286 6.061011
> 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/rcomp/tmp/7mzuy1331049287.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8wdzc1331049287.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9qlp91331049287.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10hpyn1331049287.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/115tns1331049287.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/rcomp/tmp/12vkfa1331049287.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/rcomp/tmp/137nxj1331049288.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/rcomp/tmp/145ems1331049288.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/rcomp/tmp/15ehqb1331049288.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/rcomp/tmp/16uqnl1331049288.tab")
+ }
>
> try(system("convert tmp/1fdld1331049287.ps tmp/1fdld1331049287.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ivzp1331049287.ps tmp/2ivzp1331049287.png",intern=TRUE))
character(0)
> try(system("convert tmp/36fuz1331049287.ps tmp/36fuz1331049287.png",intern=TRUE))
character(0)
> try(system("convert tmp/4n1xm1331049287.ps tmp/4n1xm1331049287.png",intern=TRUE))
character(0)
> try(system("convert tmp/5fm8m1331049287.ps tmp/5fm8m1331049287.png",intern=TRUE))
character(0)
> try(system("convert tmp/6cih31331049287.ps tmp/6cih31331049287.png",intern=TRUE))
character(0)
> try(system("convert tmp/7mzuy1331049287.ps tmp/7mzuy1331049287.png",intern=TRUE))
character(0)
> try(system("convert tmp/8wdzc1331049287.ps tmp/8wdzc1331049287.png",intern=TRUE))
character(0)
> try(system("convert tmp/9qlp91331049287.ps tmp/9qlp91331049287.png",intern=TRUE))
character(0)
> try(system("convert tmp/10hpyn1331049287.ps tmp/10hpyn1331049287.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.660 0.270 3.894