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(0.30102999566398
+ ,3
+ ,1.6232492903979
+ ,0.25527250510331
+ ,4
+ ,2.79518458968242
+ ,-0.15490195998574
+ ,4
+ ,2.25527250510331
+ ,0.5910646070265
+ ,1
+ ,1.54406804435028
+ ,0
+ ,4
+ ,2.59328606702046
+ ,0.55630250076729
+ ,1
+ ,1.79934054945358
+ ,0.14612803567824
+ ,1
+ ,2.36172783601759
+ ,0.17609125905568
+ ,4
+ ,2.04921802267018
+ ,-0.15490195998574
+ ,5
+ ,2.44870631990508
+ ,0.32221929473392
+ ,1
+ ,1.6232492903979
+ ,0.61278385671974
+ ,2
+ ,1.6232492903979
+ ,0.079181246047625
+ ,2
+ ,2.07918124604762
+ ,-0.30102999566398
+ ,5
+ ,2.17026171539496
+ ,0.53147891704226
+ ,2
+ ,1.20411998265592
+ ,0.17609125905568
+ ,1
+ ,2.49136169383427
+ ,0.53147891704226
+ ,3
+ ,1.44715803134222
+ ,-0.096910013008056
+ ,4
+ ,1.83250891270624
+ ,-0.096910013008056
+ ,5
+ ,2.52633927738984
+ ,0.30102999566398
+ ,1
+ ,1.69897000433602
+ ,0.27875360095283
+ ,1
+ ,2.42651126136458
+ ,0.11394335230684
+ ,3
+ ,1.27875360095283
+ ,0.7481880270062
+ ,1
+ ,1.07918124604762
+ ,0.49136169383427
+ ,1
+ ,2.07918124604762
+ ,0.25527250510331
+ ,2
+ ,2.14612803567824
+ ,-0.045757490560675
+ ,4
+ ,2.23044892137827
+ ,0.25527250510331
+ ,2
+ ,1.23044892137827
+ ,0.27875360095283
+ ,4
+ ,2.06069784035361
+ ,-0.045757490560675
+ ,5
+ ,1.49136169383427
+ ,0.41497334797082
+ ,3
+ ,1.32221929473392
+ ,0.38021124171161
+ ,1
+ ,1.7160033436348
+ ,0.079181246047625
+ ,2
+ ,2.2148438480477
+ ,-0.045757490560675
+ ,2
+ ,2.35218251811136
+ ,-0.30102999566398
+ ,3
+ ,2.35218251811136
+ ,-0.22184874961636
+ ,5
+ ,2.17897694729317
+ ,0.36172783601759
+ ,2
+ ,1.77815125038364
+ ,-0.30102999566398
+ ,3
+ ,2.30102999566398
+ ,0.41497334797082
+ ,2
+ ,1.66275783168157
+ ,-0.22184874961636
+ ,4
+ ,2.32221929473392
+ ,0.81954393554187
+ ,1
+ ,1.14612803567824)
+ ,dim=c(3
+ ,39)
+ ,dimnames=list(c('logPS'
+ ,'D'
+ ,'logtg')
+ ,1:39))
> y <- array(NA,dim=c(3,39),dimnames=list(c('logPS','D','logtg'),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
logPS D logtg
1 0.30103000 3 1.623249
2 0.25527251 4 2.795185
3 -0.15490196 4 2.255273
4 0.59106461 1 1.544068
5 0.00000000 4 2.593286
6 0.55630250 1 1.799341
7 0.14612804 1 2.361728
8 0.17609126 4 2.049218
9 -0.15490196 5 2.448706
10 0.32221929 1 1.623249
11 0.61278386 2 1.623249
12 0.07918125 2 2.079181
13 -0.30103000 5 2.170262
14 0.53147892 2 1.204120
15 0.17609126 1 2.491362
16 0.53147892 3 1.447158
17 -0.09691001 4 1.832509
18 -0.09691001 5 2.526339
19 0.30103000 1 1.698970
20 0.27875360 1 2.426511
21 0.11394335 3 1.278754
22 0.74818803 1 1.079181
23 0.49136169 1 2.079181
24 0.25527251 2 2.146128
25 -0.04575749 4 2.230449
26 0.25527251 2 1.230449
27 0.27875360 4 2.060698
28 -0.04575749 5 1.491362
29 0.41497335 3 1.322219
30 0.38021124 1 1.716003
31 0.07918125 2 2.214844
32 -0.04575749 2 2.352183
33 -0.30103000 3 2.352183
34 -0.22184875 5 2.178977
35 0.36172784 2 1.778151
36 -0.30103000 3 2.301030
37 0.41497335 2 1.662758
38 -0.22184875 4 2.322219
39 0.81954394 1 1.146128
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) D logtg
1.0745 -0.1105 -0.3035
> (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 ***
D -0.11051 0.02219 -4.980 1.60e-05 ***
logtg -0.30354 0.06890 -4.405 9.09e-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 0.38837004 0.19418502
[3,] 0.7209818 0.55803636 0.27901818
[4,] 0.6497648 0.70047041 0.35023521
[5,] 0.6130048 0.77399039 0.38699519
[6,] 0.6901072 0.61978562 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 0.94743822 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/rcomp/tmp/15rl61268941015.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2srtl1268941015.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3jrs71268941015.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/447f51268941015.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/50oyx1268941015.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 = 39
Frequency = 1
1 2 3 4 5 6
0.05077341 0.47125433 -0.10280444 0.09575243 0.15469778 0.13847545
7 8 9 10 11 12
-0.10099261 0.16564324 0.06642074 -0.14905829 0.25201677 -0.14319277
13 14 15 16 17 18
-0.16422605 0.04348979 -0.03168047 0.22777179 -0.17313767 0.14797731
19 20 21 22 23 24
-0.14726341 0.05129724 -0.24088107 0.11176464 0.15847718 0.05321944
25 26 27 28 29 30
-0.00119489 -0.22472476 0.27179015 -0.11502609 0.07334246 -0.06291189
31 32 33 34 35 36
-0.10201390 -0.18526501 -0.33002702 -0.08239939 0.04797951 -0.34555380
37 38 39
0.06619864 -0.14943027 0.20344150
> postscript(file="/var/www/html/rcomp/tmp/6wsu11268941015.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 = 39
Frequency = 1
lag(myerror, k = 1) myerror
0 0.05077341 NA
1 0.47125433 0.05077341
2 -0.10280444 0.47125433
3 0.09575243 -0.10280444
4 0.15469778 0.09575243
5 0.13847545 0.15469778
6 -0.10099261 0.13847545
7 0.16564324 -0.10099261
8 0.06642074 0.16564324
9 -0.14905829 0.06642074
10 0.25201677 -0.14905829
11 -0.14319277 0.25201677
12 -0.16422605 -0.14319277
13 0.04348979 -0.16422605
14 -0.03168047 0.04348979
15 0.22777179 -0.03168047
16 -0.17313767 0.22777179
17 0.14797731 -0.17313767
18 -0.14726341 0.14797731
19 0.05129724 -0.14726341
20 -0.24088107 0.05129724
21 0.11176464 -0.24088107
22 0.15847718 0.11176464
23 0.05321944 0.15847718
24 -0.00119489 0.05321944
25 -0.22472476 -0.00119489
26 0.27179015 -0.22472476
27 -0.11502609 0.27179015
28 0.07334246 -0.11502609
29 -0.06291189 0.07334246
30 -0.10201390 -0.06291189
31 -0.18526501 -0.10201390
32 -0.33002702 -0.18526501
33 -0.08239939 -0.33002702
34 0.04797951 -0.08239939
35 -0.34555380 0.04797951
36 0.06619864 -0.34555380
37 -0.14943027 0.06619864
38 0.20344150 -0.14943027
39 NA 0.20344150
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.47125433 0.05077341
[2,] -0.10280444 0.47125433
[3,] 0.09575243 -0.10280444
[4,] 0.15469778 0.09575243
[5,] 0.13847545 0.15469778
[6,] -0.10099261 0.13847545
[7,] 0.16564324 -0.10099261
[8,] 0.06642074 0.16564324
[9,] -0.14905829 0.06642074
[10,] 0.25201677 -0.14905829
[11,] -0.14319277 0.25201677
[12,] -0.16422605 -0.14319277
[13,] 0.04348979 -0.16422605
[14,] -0.03168047 0.04348979
[15,] 0.22777179 -0.03168047
[16,] -0.17313767 0.22777179
[17,] 0.14797731 -0.17313767
[18,] -0.14726341 0.14797731
[19,] 0.05129724 -0.14726341
[20,] -0.24088107 0.05129724
[21,] 0.11176464 -0.24088107
[22,] 0.15847718 0.11176464
[23,] 0.05321944 0.15847718
[24,] -0.00119489 0.05321944
[25,] -0.22472476 -0.00119489
[26,] 0.27179015 -0.22472476
[27,] -0.11502609 0.27179015
[28,] 0.07334246 -0.11502609
[29,] -0.06291189 0.07334246
[30,] -0.10201390 -0.06291189
[31,] -0.18526501 -0.10201390
[32,] -0.33002702 -0.18526501
[33,] -0.08239939 -0.33002702
[34,] 0.04797951 -0.08239939
[35,] -0.34555380 0.04797951
[36,] 0.06619864 -0.34555380
[37,] -0.14943027 0.06619864
[38,] 0.20344150 -0.14943027
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.47125433 0.05077341
2 -0.10280444 0.47125433
3 0.09575243 -0.10280444
4 0.15469778 0.09575243
5 0.13847545 0.15469778
6 -0.10099261 0.13847545
7 0.16564324 -0.10099261
8 0.06642074 0.16564324
9 -0.14905829 0.06642074
10 0.25201677 -0.14905829
11 -0.14319277 0.25201677
12 -0.16422605 -0.14319277
13 0.04348979 -0.16422605
14 -0.03168047 0.04348979
15 0.22777179 -0.03168047
16 -0.17313767 0.22777179
17 0.14797731 -0.17313767
18 -0.14726341 0.14797731
19 0.05129724 -0.14726341
20 -0.24088107 0.05129724
21 0.11176464 -0.24088107
22 0.15847718 0.11176464
23 0.05321944 0.15847718
24 -0.00119489 0.05321944
25 -0.22472476 -0.00119489
26 0.27179015 -0.22472476
27 -0.11502609 0.27179015
28 0.07334246 -0.11502609
29 -0.06291189 0.07334246
30 -0.10201390 -0.06291189
31 -0.18526501 -0.10201390
32 -0.33002702 -0.18526501
33 -0.08239939 -0.33002702
34 0.04797951 -0.08239939
35 -0.34555380 0.04797951
36 0.06619864 -0.34555380
37 -0.14943027 0.06619864
38 0.20344150 -0.14943027
> 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/7ik7q1268941015.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/86nr31268941015.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9pb3s1268941015.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10uq521268941015.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11q3vi1268941015.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/12ei681268941015.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/132vkk1268941015.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/14cy8p1268941015.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/15po3j1268941015.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/16zsq81268941015.tab")
+ }
>
> try(system("convert tmp/15rl61268941015.ps tmp/15rl61268941015.png",intern=TRUE))
character(0)
> try(system("convert tmp/2srtl1268941015.ps tmp/2srtl1268941015.png",intern=TRUE))
character(0)
> try(system("convert tmp/3jrs71268941015.ps tmp/3jrs71268941015.png",intern=TRUE))
character(0)
> try(system("convert tmp/447f51268941015.ps tmp/447f51268941015.png",intern=TRUE))
character(0)
> try(system("convert tmp/50oyx1268941015.ps tmp/50oyx1268941015.png",intern=TRUE))
character(0)
> try(system("convert tmp/6wsu11268941015.ps tmp/6wsu11268941015.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ik7q1268941015.ps tmp/7ik7q1268941015.png",intern=TRUE))
character(0)
> try(system("convert tmp/86nr31268941015.ps tmp/86nr31268941015.png",intern=TRUE))
character(0)
> try(system("convert tmp/9pb3s1268941015.ps tmp/9pb3s1268941015.png",intern=TRUE))
character(0)
> try(system("convert tmp/10uq521268941015.ps tmp/10uq521268941015.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.220 1.516 2.953