x <- array(list(1910
, 61
,17
, 56
, 84
, 4
, 21
, 51
,2598
, 74
,19
, 73
, 47
, 3
, 15
, 48
,2144
, 57
,18
, 62
, 63
, 3
, 17
, 46
,1331
, 50
,15
, 42
, 28
, 3
, 20
, 42
,1431
, 48
,15
, 59
, 22
, 2
, 12
, 38
,7334
, 2
,12
, 27
, 18
, 6
, 4
, 38
,1133
, 41
,15
, 59
, 20
, 5
, 9
, 36
,1195
, 31
,20
, 78
, 27
, 5
, 11
, 35
,1522
, 61
,14
, 56
, 37
, 5
, 12
, 35
,1551
, 12
,12
, 47
, 23
, 6
, 7
, 35
,2108
, 46
,13
, 51
, 67
, 5
, 14
, 34
,1335
, 31
,17
, 47
, 28
, 4
, 11
, 34
,1065
, 33
,12
, 48
, 28
, 5
, 9
, 31
, 842
, 49
,10
, 35
, 45
, 3
, 14
, 31
,1539
, 15
,13
, 47
, 15
, 5
, 4
, 31
,1508
, 59
,15
, 55
, 36
, 5
, 11
, 31
,1598
, 28
,12
, 42
, 12
, 2
, 10
, 30
,1219
, 55
,16
, 55
, 30
, 6
, 9
, 30
,1443
, 35
,13
, 47
, 28
, 9
, 8
, 30
,1546
, 44
,15
, 54
, 27
, 2
, 14
, 30
, 914
, 41
,15
, 60
, 43
, 5
, 13
, 30
,1371
, 26
,13
, 51
, 10
, 3
, 10
, 28
,1318
, 28
,12
, 47
, 22
, 4
, 9
, 27
,1313
, 40
,15
, 52
, 27
, 4
, 11
, 27
,1743
, 28
,12
, 38
, 21
,11
, 7
, 27
,1102
, 67
,12
, 12
, 24
, 5
, 10
, 26
,1275
, 56
,12
, 48
, 52
, 3
, 15
, 26
,1253
, 54
,12
, 48
, 24
, 5
, 7
, 26
,1487
, 25
, 8
, 32
, 19
, 5
, 10
, 26
,1098
, 19
, 9
, 27
, 12
,--
, 4
, 26
,1176
, 36
,12
, 47
, 21
, 3
, 10
, 25
, 903
, 42
,16
, 58
, 71
, 4
, 13
, 25
,1290
, 19
,14
, 47
, 19
, 4
, 5
, 25
,1050
, 57
,13
, 46
, 24
, 5
, 10
, 25
, 930
, 28
,15
, 60
, 12
, 2
, 10
, 25
, 821
, 32
,15
, 56
, 29
, 5
, 11
, 24
, 826
, 10
,12
, 41
, 13
, 3
, 7
, 24
,1402
, 28
,12
, 45
, 22
,11
, 6
, 24
,1495
, 41
,12
, 48
, 27
, 5
, 8
, 24
,1064
, 48
,15
, 60
, 36
, 5
, 10
, 24
,1469
, 57
,12
, 48
, 27
, 3
, 9
, 24
,1493
, 35
,13
, 42
, 21
, 5
, 8
, 24
,1239
, 30
,12
, 47
, 28
, 4
, 11
, 24
,1317
, 39
,12
, 41
, 17
, 3
, 5
, 23
, 708
, 17
,15
, 49
, 15
, 8
, 5
, 23
, 872
, 33
,12
, 39
, 26
, 3
, 10
, 23
, 853
, 55
,12
, 39
, 19
, 3
, 8
, 23
,1174
, 30
,12
, 42
, 34
,11
, 9
, 23
, 982
, 22
,13
, 50
, 21
, 4
, 7
, 23
,1202
, 42
,12
, 41
, 32
, 6
, 8
, 23
, 873
, 49
,15
, 52
, 14
,14
, 5
, 23
,1000
, 13
, 9
, 36
, 17
, 6
, 5
, 22
,1131
, 15
,13
, 45
, 16
, 3
, 7
, 22
, 793
, 24
,12
, 46
, 18
, 5
, 10
, 22
,1106
, 3
,13
, 55
, 8
, 8
, 2
, 22
,1205
, 35
,13
, 49
, 30
, 8
, 5
, 22
,1671
, 37
,13
, 48
, 31
, 3
, 13
, 22
,1374
, 28
,13
, 39
, 19
, 3
, 10
, 21
, 775
, 19
,12
, 48
, 10
, 3
, 5
, 21
, 804
, 38
,15
, 45
, 24
, 5
, 10
, 21
,1224
, 29
,14
, 52
, 28
, 6
, 8
, 21
,1233
, 38
,15
, 51
, 27
, 3
, 7
, 20
,1170
, 35
,14
, 41
, 16
, 3
, 10
, 20
, 923
, 23
, 9
, 32
, 17
, 3
, 5
, 20
, 613
, 27
,14
, 52
, 30
, 3
, 9
, 20
,1204
, 32
,16
, 54
, 20
, 4
, 6
, 19
, 933
, 7
, 9
, 27
, 10
, 5
, 6
, 18
, 861
, 57
,12
, 41
, 30
, 3
, 9
, 18
, 932
, 39
,12
, 45
, 34
, 5
, 11
, 18
, 705
, 18
,13
, 52
, 13
,13
, 6
, 18
, 828
, 18
,16
, 57
, 10
, 5
, 3
, 17
, 893
, 22
,12
, 22
, 14
, 5
, 6
, 17
,1082
, 41
,12
, 47
, 29
, 6
, 9
, 17
, 918
, 37
,10
, 31
, 22
, 4
, 9
, 16
, 779
, 33
,12
, 41
, 31
, 4
, 6
, 16
, 587
, 35
,12
, 43
, 16
, 4
, 10
, 16
, 843
, 34
,12
, 24
, 18
, 9
, 7
, 16
,1060
, 35
,15
, 30
, 31
, 5
, 10
, 16
, 649
, 16
,10
, 40
, 7
, 7
, 5
, 16
, 792
, 0
,12
, 46
, 0
,--
, 0
, 16
, 846
, 17
,14
, 44
, 9
, 9
, 3
, 15
, 547
, 26
,15
, 32
, 22
, 7
, 7
, 15
, 575
, 25
,12
, 45
, 27
, 2
, 8
, 15
, 486
, 40
,12
, 37
, 24
, 3
, 10
, 15
, 861
, 54
,12
, 32
, 55
, 6
, 8
, 15
, 503
, 13
,13
, 46
, 10
, 3
, 5
, 15
, 743
, 30
,13
, 9
, 25
, 8
, 7
, 15
, 634
, 9
,16
, 64
, 9
, 5
, 5
, 15
, 715
, 29
,12
, 20
, 11
, 3
, 6
, 14
, 871
, 25
,12
, 21
, 8
, 8
, 4
, 14
, 812
, 40
,12
, 33
, 14
, 4
, 5
, 14
, 970
, 32
,13
, 26
, 8
, 3
, 5
, 14
, 959
, 17
,12
, 36
, 29
, 7
, 6
, 13
, 960
, 18
,11
, 33
, 16
, 3
, 5
, 13
, 646
, 17
,16
, 20
, 13
, 7
, 5
, 13
, 562
, 15
, 8
, 31
, 16
, 3
, 5
, 13
, 636
, 28
,12
, 13
, 10
, 5
, 5
, 13
, 646
, 18
,13
, 35
, 10
,--
, 0
, 13
, 830
, 10
,12
, 40
, 5
, 5
, 2
, 12
, 428
, 10
,11
, 24
, 10
, 5
, 2
, 12
, 781
, 10
,12
, 15
, 26
, 5
, 8
, 12
, 475
, 16
,15
, 58
, 11
, 3
, 6
, 12
, 567
, 2
,13
, 34
, 1
,--
, 0
, 12
, 485
, 28
, 8
, 21
, 6
, 6
, 3
, 12
, 694
, 25
,13
, 32
, 12
, 4
, 4
, 12
, 480
, 7
, 8
, 21
, 61
,--
, 3
, 11
, 613
, 25
,12
, 31
, 19
, 6
, 3
, 11
, 582
, 27
,14
, 26
, 24
, 6
, 8
, 11
, 569
, 16
,16
, 47
, 10
, 5
, 3
, 11
, 559
, 7
,12
, 37
, 5
, 5
, 2
, 11
, 507
, 16
, 9
, 28
, 7
, 2
, 2
, 10
, 488
, 0
, 5
, 9
, 37
,37
, 1
, 10
, 383
, 2
, 8
, 19
, 1
, 1
, 2
, 10
, 475
, 36
,13
, 45
, 13
, 4
, 4
, 9
, 630
, 15
,10
, 32
, 69
,23
, 3
, 9
, 386
, 5
,13
, 35
, 38
, 5
, 7
, 9
, 510
, 14
,12
, 29
, 30
,10
, 3
, 9
, 566
, 43
,13
, 1
, 8
, 4
, 6
, 9
, 580
, 10
,12
, 20
, 2
,--
, 1
, 9
, 516
, 0
, 4
, 15
, 3
, 3
, 1
, 9
, 413
, 8
,12
, 11
, 2
,--
, 2
, 8
, 478
, 10
,13
, 18
, 8
, 4
, 4
, 8
, 495
, 12
,12
, 33
, 11
, 6
, 2
, 8
, 350
, 39
, 5
, 10
, 23
, 6
, 5
, 7
, 427
, 0
,12
, 41
, 0
,--
, 0
, 7
, 349
, 10
, 9
, 10
, 4
, 2
, 3
, 6
, 335
, 7
, 6
, 0
, 2
,--
, 0
, 6
, 470
, 8
,15
, 28
, 0
,--
, 0
, 5
, 250
, 0
, 9
, 31
, 10
,--
, 0
, 5
, 308
, 3
,12
, 24
, 4
, 4
, 2
, 5
, 229
, 0
,11
, 38
, 9
, 9
, 1
, 5
, 244
, 8
, 0
, 0
, 13
, 4
, 4
, 5
, 242
, 1
, 8
, 25
, 0
,--
, 0
, 5
, 352
, 0
,12
, 40
, 0
,--
, 0
, 5
, 428
, 8
, 3
, 4
, 5
, 5
, 3
, 5
, 270
, 3
, 9
, 23
, 1
,--
, 1
, 5
, 242
, 0
, 4
, 13
, 0
,--
, 0
, 4
, 291
, 0
,14
, 6
, 39
,--
, 2
, 4
, 135
, 0
, 0
, 0
, 1
,--
, 1
, 3
, 210
, 3
, 1
, 3
, 3
, 3
, 3
, 3
, 231
, 0
, 0
, 0
, 0
,--
, 0
, 2
, 267
, 0
, 6
, 7
, 0
,--
, 0
, 2
, 126
, 0
, 6
, 2
, 0
,--
, 0
, 2
, 340
, 0
, 0
, 0
, 0
,--
, 0
, 2
, 44
, 0
, 0
, 0
, 0
,--
, 0
, 2
, 25
, 0
, 0
, 0
, 0
,--
, 0
, 1
, 104
, 0
, 0
, 0
, 0
,--
, 0
, 1
, 142
, 2
, 2
, 5
, 0
,--
, 0
, 1
, 11
, 0
, 0
, 0
, 0
,--
, 0
, 0)
,dim=c(8
,149)
,dimnames=list(c('1'
,'2'
,'3'
,'4'
,'5'
,'6'
,'7'
,'8')
,1:149))
y <- array(NA,dim=c(8,149),dimnames=list(c('1','2','3','4','5','6','7','8'),1:149))
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 = '8'
par3 <- 'No Linear Trend'
par2 <- 'Do not include Seasonal Dummies'
par1 <- '8'
#'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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
#Source of accompanying publication: Office for Research, Development, and Education
#Technical description: Write here your technical program description (don't use hard returns!)
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$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
}
postscript(file="/var/wessaorg/rcomp/tmp/14dr51352123012.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$resid)
grid()
dev.off()
postscript(file="/var/wessaorg/rcomp/tmp/20pq11352123012.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
postscript(file="/var/wessaorg/rcomp/tmp/3fzdr1352123012.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
postscript(file="/var/wessaorg/rcomp/tmp/43bpy1352123012.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
postscript(file="/var/wessaorg/rcomp/tmp/52pyc1352123012.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()
(myerror <- as.ts(mysum$resid))
postscript(file="/var/wessaorg/rcomp/tmp/6vfq51352123012.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
postscript(file="/var/wessaorg/rcomp/tmp/75j7o1352123012.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
postscript(file="/var/wessaorg/rcomp/tmp/864rf1352123012.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
postscript(file="/var/wessaorg/rcomp/tmp/9qp7y1352123012.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
postscript(file="/var/wessaorg/rcomp/tmp/10t63n1352123012.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
#Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
load(file="/var/wessaorg/rcomp/createtable")
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$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/11c9ul1352123012.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/12jy491352123012.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/13uvvw1352123013.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/14ot0s1352123013.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/15m9zl1352123013.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/16k09h1352123013.tab")
}
try(system("convert tmp/14dr51352123012.ps tmp/14dr51352123012.png",intern=TRUE))
try(system("convert tmp/20pq11352123012.ps tmp/20pq11352123012.png",intern=TRUE))
try(system("convert tmp/3fzdr1352123012.ps tmp/3fzdr1352123012.png",intern=TRUE))
try(system("convert tmp/43bpy1352123012.ps tmp/43bpy1352123012.png",intern=TRUE))
try(system("convert tmp/52pyc1352123012.ps tmp/52pyc1352123012.png",intern=TRUE))
try(system("convert tmp/6vfq51352123012.ps tmp/6vfq51352123012.png",intern=TRUE))
try(system("convert tmp/75j7o1352123012.ps tmp/75j7o1352123012.png",intern=TRUE))
try(system("convert tmp/864rf1352123012.ps tmp/864rf1352123012.png",intern=TRUE))
try(system("convert tmp/9qp7y1352123012.ps tmp/9qp7y1352123012.png",intern=TRUE))
try(system("convert tmp/10t63n1352123012.ps tmp/10t63n1352123012.png",intern=TRUE))