R version 2.8.0 (2008-10-20)
Copyright (C) 2008 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.
Natural language support but running in an English locale
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(0.301029996
+ ,1.62324929
+ ,3
+ ,0.255272505
+ ,2.79518459
+ ,4
+ ,-0.15490196
+ ,2.255272505
+ ,4
+ ,0.591064607
+ ,1.544068044
+ ,1
+ ,0
+ ,2.593286067
+ ,4
+ ,0.556302501
+ ,1.799340549
+ ,1
+ ,0.146128036
+ ,2.361727836
+ ,1
+ ,0.176091259
+ ,2.049218023
+ ,4
+ ,-0.15490196
+ ,2.44870632
+ ,5
+ ,0.322219295
+ ,1.62324929
+ ,1
+ ,0.612783857
+ ,1.62324929
+ ,2
+ ,0.079181246
+ ,2.079181246
+ ,2
+ ,-0.301029996
+ ,2.170261715
+ ,5
+ ,0.531478917
+ ,1.204119983
+ ,2
+ ,0.176091259
+ ,2.491361694
+ ,1
+ ,0.531478917
+ ,1.447158031
+ ,3
+ ,-0.096910013
+ ,1.832508913
+ ,4
+ ,-0.096910013
+ ,2.526339277
+ ,5
+ ,0.301029996
+ ,1.698970004
+ ,1
+ ,0.278753601
+ ,2.426511261
+ ,1
+ ,0.113943352
+ ,1.278753601
+ ,3
+ ,0.748188027
+ ,1.079181246
+ ,1
+ ,0.491361694
+ ,2.079181246
+ ,1
+ ,0.255272505
+ ,2.146128036
+ ,2
+ ,-0.045757491
+ ,2.230448921
+ ,4
+ ,0.255272505
+ ,1.230448921
+ ,2
+ ,0.278753601
+ ,2.06069784
+ ,4
+ ,-0.045757491
+ ,1.491361694
+ ,5
+ ,0.414973348
+ ,1.322219295
+ ,3
+ ,0.380211242
+ ,1.716003344
+ ,1
+ ,0.079181246
+ ,2.214843848
+ ,2
+ ,-0.045757491
+ ,2.352182518
+ ,2
+ ,-0.301029996
+ ,2.352182518
+ ,3
+ ,-0.22184875
+ ,2.178976947
+ ,5
+ ,0.361727836
+ ,1.77815125
+ ,2
+ ,-0.301029996
+ ,2.301029996
+ ,3
+ ,0.414973348
+ ,1.662757832
+ ,2
+ ,-0.22184875
+ ,2.322219295
+ ,4
+ ,0.819543936
+ ,1.146128036
+ ,1)
+ ,dim=c(3
+ ,39)
+ ,dimnames=list(c('PS'
+ ,'GEST'
+ ,'ODI')
+ ,1:39))
> y <- array(NA,dim=c(3,39),dimnames=list(c('PS','GEST','ODI'),1:39))
> 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
PS GEST ODI
1 0.30103000 1.623249 3
2 0.25527250 2.795185 4
3 -0.15490196 2.255273 4
4 0.59106461 1.544068 1
5 0.00000000 2.593286 4
6 0.55630250 1.799341 1
7 0.14612804 2.361728 1
8 0.17609126 2.049218 4
9 -0.15490196 2.448706 5
10 0.32221930 1.623249 1
11 0.61278386 1.623249 2
12 0.07918125 2.079181 2
13 -0.30103000 2.170262 5
14 0.53147892 1.204120 2
15 0.17609126 2.491362 1
16 0.53147892 1.447158 3
17 -0.09691001 1.832509 4
18 -0.09691001 2.526339 5
19 0.30103000 1.698970 1
20 0.27875360 2.426511 1
21 0.11394335 1.278754 3
22 0.74818803 1.079181 1
23 0.49136169 2.079181 1
24 0.25527250 2.146128 2
25 -0.04575749 2.230449 4
26 0.25527250 1.230449 2
27 0.27875360 2.060698 4
28 -0.04575749 1.491362 5
29 0.41497335 1.322219 3
30 0.38021124 1.716003 1
31 0.07918125 2.214844 2
32 -0.04575749 2.352183 2
33 -0.30103000 2.352183 3
34 -0.22184875 2.178977 5
35 0.36172784 1.778151 2
36 -0.30103000 2.301030 3
37 0.41497335 1.662758 2
38 -0.22184875 2.322219 4
39 0.81954394 1.146128 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) GEST ODI
1.0745 -0.3035 -0.1105
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.34555 -0.14523 0.04349 0.12512 0.47125
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.07451 0.12875 8.346 6.16e-10 ***
GEST -0.30354 0.06890 -4.405 9.09e-05 ***
ODI -0.11051 0.02219 -4.980 1.60e-05 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.1818 on 36 degrees of freedom
Multiple R-squared: 0.6546, Adjusted R-squared: 0.6354
F-statistic: 34.12 on 2 and 36 DF, p-value: 4.888e-09
> 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,] 0.5979290 0.80414206 0.40207103
[2,] 0.8058150 0.38837005 0.19418502
[3,] 0.7209818 0.55803636 0.27901818
[4,] 0.6497648 0.70047042 0.35023521
[5,] 0.6130048 0.77399039 0.38699520
[6,] 0.6901072 0.61978563 0.30989281
[7,] 0.6911997 0.61760069 0.30880034
[8,] 0.7378984 0.52420315 0.26210158
[9,] 0.6517731 0.69645381 0.34822690
[10,] 0.5666430 0.86671405 0.43335703
[11,] 0.5946891 0.81062186 0.40531093
[12,] 0.6108801 0.77823971 0.38911985
[13,] 0.6134411 0.77311783 0.38655892
[14,] 0.5892054 0.82158927 0.41079464
[15,] 0.5034278 0.99314435 0.49657218
[16,] 0.5914000 0.81719994 0.40859997
[17,] 0.5262809 0.94743823 0.47371911
[18,] 0.5343516 0.93129677 0.46564839
[19,] 0.4829137 0.96582748 0.51708626
[20,] 0.4143011 0.82860226 0.58569887
[21,] 0.6028548 0.79429032 0.39714516
[22,] 0.9605582 0.07888351 0.03944176
[23,] 0.9705527 0.05889463 0.02944732
[24,] 0.9617218 0.07655637 0.03827818
[25,] 0.9327455 0.13450903 0.06725451
[26,] 0.9136053 0.17278945 0.08639473
[27,] 0.9363536 0.12729272 0.06364636
[28,] 0.8803570 0.23928601 0.11964301
> postscript(file="/var/www/html/freestat/rcomp/tmp/1ng2m1292319354.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2y71o1292319354.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/html/freestat/rcomp/tmp/3y71o1292319354.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4y71o1292319354.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/58g091292319354.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 = 39
Frequency = 1
1 2 3 4 5 6
0.050773408 0.471254332 -0.102804437 0.095752433 0.154697777 0.138475455
7 8 9 10 11 12
-0.100992610 0.165643238 0.066420745 -0.149058293 0.252016769 -0.143192772
13 14 15 16 17 18
-0.164226052 0.043489793 -0.031680472 0.227771787 -0.173137672 0.147977311
19 20 21 22 23 24
-0.147263412 0.051297243 -0.240881068 0.111764641 0.158477176 0.053219440
25 26 27 28 29 30
-0.001194890 -0.224724763 0.271790151 -0.115026091 0.073342456 -0.062911885
31 32 33 34 35 36
-0.102013899 -0.185265012 -0.330027017 -0.082399394 0.047979514 -0.345553796
37 38 39
0.066198638 -0.149430274 0.203441502
> postscript(file="/var/www/html/freestat/rcomp/tmp/68g091292319354.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 = 39
Frequency = 1
lag(myerror, k = 1) myerror
0 0.050773408 NA
1 0.471254332 0.050773408
2 -0.102804437 0.471254332
3 0.095752433 -0.102804437
4 0.154697777 0.095752433
5 0.138475455 0.154697777
6 -0.100992610 0.138475455
7 0.165643238 -0.100992610
8 0.066420745 0.165643238
9 -0.149058293 0.066420745
10 0.252016769 -0.149058293
11 -0.143192772 0.252016769
12 -0.164226052 -0.143192772
13 0.043489793 -0.164226052
14 -0.031680472 0.043489793
15 0.227771787 -0.031680472
16 -0.173137672 0.227771787
17 0.147977311 -0.173137672
18 -0.147263412 0.147977311
19 0.051297243 -0.147263412
20 -0.240881068 0.051297243
21 0.111764641 -0.240881068
22 0.158477176 0.111764641
23 0.053219440 0.158477176
24 -0.001194890 0.053219440
25 -0.224724763 -0.001194890
26 0.271790151 -0.224724763
27 -0.115026091 0.271790151
28 0.073342456 -0.115026091
29 -0.062911885 0.073342456
30 -0.102013899 -0.062911885
31 -0.185265012 -0.102013899
32 -0.330027017 -0.185265012
33 -0.082399394 -0.330027017
34 0.047979514 -0.082399394
35 -0.345553796 0.047979514
36 0.066198638 -0.345553796
37 -0.149430274 0.066198638
38 0.203441502 -0.149430274
39 NA 0.203441502
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.471254332 0.050773408
[2,] -0.102804437 0.471254332
[3,] 0.095752433 -0.102804437
[4,] 0.154697777 0.095752433
[5,] 0.138475455 0.154697777
[6,] -0.100992610 0.138475455
[7,] 0.165643238 -0.100992610
[8,] 0.066420745 0.165643238
[9,] -0.149058293 0.066420745
[10,] 0.252016769 -0.149058293
[11,] -0.143192772 0.252016769
[12,] -0.164226052 -0.143192772
[13,] 0.043489793 -0.164226052
[14,] -0.031680472 0.043489793
[15,] 0.227771787 -0.031680472
[16,] -0.173137672 0.227771787
[17,] 0.147977311 -0.173137672
[18,] -0.147263412 0.147977311
[19,] 0.051297243 -0.147263412
[20,] -0.240881068 0.051297243
[21,] 0.111764641 -0.240881068
[22,] 0.158477176 0.111764641
[23,] 0.053219440 0.158477176
[24,] -0.001194890 0.053219440
[25,] -0.224724763 -0.001194890
[26,] 0.271790151 -0.224724763
[27,] -0.115026091 0.271790151
[28,] 0.073342456 -0.115026091
[29,] -0.062911885 0.073342456
[30,] -0.102013899 -0.062911885
[31,] -0.185265012 -0.102013899
[32,] -0.330027017 -0.185265012
[33,] -0.082399394 -0.330027017
[34,] 0.047979514 -0.082399394
[35,] -0.345553796 0.047979514
[36,] 0.066198638 -0.345553796
[37,] -0.149430274 0.066198638
[38,] 0.203441502 -0.149430274
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.471254332 0.050773408
2 -0.102804437 0.471254332
3 0.095752433 -0.102804437
4 0.154697777 0.095752433
5 0.138475455 0.154697777
6 -0.100992610 0.138475455
7 0.165643238 -0.100992610
8 0.066420745 0.165643238
9 -0.149058293 0.066420745
10 0.252016769 -0.149058293
11 -0.143192772 0.252016769
12 -0.164226052 -0.143192772
13 0.043489793 -0.164226052
14 -0.031680472 0.043489793
15 0.227771787 -0.031680472
16 -0.173137672 0.227771787
17 0.147977311 -0.173137672
18 -0.147263412 0.147977311
19 0.051297243 -0.147263412
20 -0.240881068 0.051297243
21 0.111764641 -0.240881068
22 0.158477176 0.111764641
23 0.053219440 0.158477176
24 -0.001194890 0.053219440
25 -0.224724763 -0.001194890
26 0.271790151 -0.224724763
27 -0.115026091 0.271790151
28 0.073342456 -0.115026091
29 -0.062911885 0.073342456
30 -0.102013899 -0.062911885
31 -0.185265012 -0.102013899
32 -0.330027017 -0.185265012
33 -0.082399394 -0.330027017
34 0.047979514 -0.082399394
35 -0.345553796 0.047979514
36 0.066198638 -0.345553796
37 -0.149430274 0.066198638
38 0.203441502 -0.149430274
> 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/freestat/rcomp/tmp/718hc1292319354.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/818hc1292319354.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9uhgx1292319354.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10uhgx1292319354.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/11fzxl1292319354.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/freestat/rcomp/tmp/1210e91292319354.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/freestat/rcomp/tmp/13pjs31292319354.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/freestat/rcomp/tmp/140as61292319354.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/freestat/rcomp/tmp/15lbqt1292319354.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/freestat/rcomp/tmp/16h2o21292319354.tab")
+ }
>
> try(system("convert tmp/1ng2m1292319354.ps tmp/1ng2m1292319354.png",intern=TRUE))
character(0)
> try(system("convert tmp/2y71o1292319354.ps tmp/2y71o1292319354.png",intern=TRUE))
character(0)
> try(system("convert tmp/3y71o1292319354.ps tmp/3y71o1292319354.png",intern=TRUE))
character(0)
> try(system("convert tmp/4y71o1292319354.ps tmp/4y71o1292319354.png",intern=TRUE))
character(0)
> try(system("convert tmp/58g091292319354.ps tmp/58g091292319354.png",intern=TRUE))
character(0)
> try(system("convert tmp/68g091292319354.ps tmp/68g091292319354.png",intern=TRUE))
character(0)
> try(system("convert tmp/718hc1292319354.ps tmp/718hc1292319354.png",intern=TRUE))
character(0)
> try(system("convert tmp/818hc1292319354.ps tmp/818hc1292319354.png",intern=TRUE))
character(0)
> try(system("convert tmp/9uhgx1292319354.ps tmp/9uhgx1292319354.png",intern=TRUE))
character(0)
> try(system("convert tmp/10uhgx1292319354.ps tmp/10uhgx1292319354.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.580 2.391 3.890