• QR Code (size=2)
• QR Code (size=3)
• QR Code (size=4)
• QR Code (size=5)
• QR Code (size=6)

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2011 8 22 1 1 62 139 39 "'12.2'"
2011 14 22 1 0 54 148 32 "'12.8'"
2011 16 18 1 1 71 158 62 "'7.4'"
2011 14 23 1 1 54 128 33 "'6.7'"
2011 13 12 1 1 65 224 52 "'12.6'"
2011 15 20 1 0 73 159 62 "'14.8'"
2011 13 22 1 1 52 105 77 "'13.3'"
2011 20 21 1 1 84 159 76 "'11.1'"
2011 17 19 1 1 42 167 41 "'8.2'"
2011 15 22 1 1 66 165 48 "'11.4'"
2011 16 15 1 1 65 159 63 "'6.4'"
2011 12 20 1 1 78 119 30 "'10.6'"
2011 17 19 1 0 73 176 78 12
2011 11 18 1 0 75 54 19 "'6.3'"
2011 16 15 0 0 72 91 31 "'11.3'"
2011 16 20 1 1 66 163 66 "'11.9'"
2011 15 21 1 0 70 124 35 "'9.3'"
2011 13 21 0 1 61 137 42 "'9.6'"
2011 14 15 1 0 81 121 45 10
2011 19 16 1 1 71 153 21 "'6.4'"
2011 16 23 1 1 69 148 25 "'13.8'"
2011 17 21 1 0 71 221 44 "'10.8'"
2011 10 18 1 1 72 188 69 "'13.8'"
2011 15 25 1 1 68 149 54 "'11.7'"
2011 14 9 1 1 70 244 74 "'10.9'"
2011 14 30 0 1 68 148 80 "'16.1'"
2011 16 20 0 0 61 92 42 "'13.4'"
2011 15 23 1 1 67 150 61 "'9.9'"
2011 17 16 1 0 76 153 41 "'11.5'"
2011 14 16 1 0 70 94 46 "'8.3'"
2011 16 19 1 0 60 156 39 "'11.7'"
2011 15 25 1 1 72 132 34 9
2011 16 18 1 1 69 161 51 "'9.7'"
2011 16 23 1 1 71 105 42 "'10.8'"
2011 10 21 1 1 62 97 31 "'10.3'"
2011 8 10 1 0 70 151 39 "'10.4'"
2011 17 14 0 1 64 131 20 "'12.7'"
2011 14 22 1 1 58 166 49 "'9.3'"
2011 10 26 1 0 76 157 53 "'11.8'"
2011 14 23 1 1 52 111 31 "'5.9'"
2011 12 23 1 1 59 145 39 "'11.4'"
2011 16 24 1 1 68 162 54 13
2011 16 24 1 1 76 163 49 "'10.8'"
2011 16 18 0 1 65 59 34 "'12.3'"
2011 8 23 1 0 67 187 46 "'11.3'"
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2011 15 19 0 1 69 90 42 "'7.9'"
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2011 9 21 1 0 75 99 40 "'7.6'"
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2011 12 19 1 0 60 186 37 "'9.2'"
2011 12 20 0 1 62 66 25 "'9.1'"
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2011 15 19 0 0 64 104 35 "'12.2'"
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2011 14 19 1 0 64 126 29 "'11.4'"
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2011 7 14 1 0 78 139 50 "'12.6'"
2011 13 28 1 1 53 78 3 NA
2011 15 16 1 0 67 162 59 13
2011 12 24 0 1 59 108 27 "'12.6'"
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2011 16 22 0 0 72 87 48 "'10.9'"
2011 13 20 0 1 71 97 25 "'4.3'"
2011 16 10 0 0 59 127 44 "'10.3'"
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2011 16 17 0 1 66 80 32 "'11.2'"
2011 10 22 0 0 78 74 20 "'11.4'"
2011 12 24 0 0 68 91 28 "'8.6'"
2011 12 18 0 0 73 133 34 "'13.2'"
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2011 12 20 0 1 65 114 26 "'5.6'"
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2011 13 19 0 1 60 98 21 "'7.7'"
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2011 15 26 0 1 65 126 33 "'7.3'"
2011 12 23 0 1 68 98 16 "'11.4'"
2011 8 24 0 1 64 95 20 "'13.6'"
2011 10 21 0 1 74 110 37 "'7.9'"
2011 16 21 0 1 69 70 35 "'10.7'"
2011 16 19 0 0 76 102 33 "'10.3'"
2011 10 8 0 1 68 86 27 "'8.3'"
2011 18 17 0 1 72 130 41 "'9.6'"
2011 12 20 0 1 67 96 40 "'14.2'"
2011 16 11 0 0 63 102 35 "'8.5'"
2011 10 8 0 0 59 100 28 "'13.5'"
2011 14 15 0 0 73 94 32 "'4.9'"
2011 12 18 0 0 66 52 22 "'6.4'"
2011 11 18 0 0 62 98 44 "'9.6'"
2011 15 19 0 0 69 118 27 "'11.6'"
2011 7 19 0 1 66 99 17 "'11.1'"
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2012 13 19 1 1 72 114 35 "'14.75'"
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2012 17 19 1 1 51 117 72 "'16.1'"
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2012 15 3 1 1 73 154 61 "'15.25'"
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2012 16 22 0 0 68 82 57 "'11.35'"
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2012 15 25 1 1 60 165 29 "'15.4'"
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2012 15 25 0 0 62 110 55 "'16.1'"
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2012 12 24 0 0 66 115 2 "'12.15'"
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2012 14 26 0 1 62 60 27 "'10.35'"
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2012 15 13 0 0 66 111 39 "'18.2'"
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2012 16 30 0 1 47 73 43 "'14.85'"
2012 14 25 1 0 72 151 57 "'14.75'"
2012 16 4 0 0 62 89 43 "'14.1'"
2012 12 16 0 0 64 78 23 "'14.9'"
2012 16 21 0 0 64 110 44 "'16.25'"
2012 16 23 1 1 19 220 54 "'19.25'"
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2012 11 20 1 1 79 122 16 "'12.75'"
2012 15 22 0 0 69 63 23 "'14.6'"
2012 18 16 1 1 71 44 40 "'9.85'"
2012 13 23 0 1 48 52 24 "'12.65'"
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2012 7 18 0 1 74 101 57 "'16.6'"
2012 17 25 0 1 66 42 37 "'11.2'"
2012 18 23 1 1 71 152 27 "'15.25'"
2012 15 12 1 0 74 107 61 "'11.9'"
2012 8 18 0 0 78 77 27 "'13.2'"
2012 13 24 1 0 75 154 69 "'16.35'"
2012 13 11 1 1 53 103 34 "'12.4'"
2012 15 18 0 1 60 96 44 "'15.85'"
2012 18 23 1 1 70 175 34 "'18.15'"
2012 16 24 0 1 69 57 39 "'11.15'"
2012 14 29 0 0 65 112 51 "'15.65'"
2012 15 18 1 0 78 143 34 "'17.75'"
2012 19 15 0 0 78 49 31 "'7.65'"
2012 16 29 1 1 59 110 13 "'12.35'"
2012 12 16 1 1 72 131 12 "'15.6'"
2012 16 19 1 0 70 167 51 "'19.3'"
2012 11 22 0 0 63 56 24 "'15.2'"
2012 16 16 1 0 63 137 19 "'17.1'"
2012 15 23 0 1 71 86 30 "'15.6'"
2012 19 23 1 1 74 121 81 "'18.4'"
2012 15 19 1 0 67 149 42 "'19.05'"
2012 14 4 1 0 66 168 22 "'18.55'"
2012 14 20 1 0 62 140 85 "'19.1'"
2012 17 24 0 1 80 88 27 "'13.1'"
2012 16 20 1 1 73 168 25 "'12.85'"
2012 20 4 1 1 67 94 22 "'9.5'"
2012 16 24 1 1 61 51 19 "'4.5'"
2012 9 22 0 0 73 48 14 "'11.85'"
2012 13 16 1 1 74 145 45 "'13.6'"
2012 15 3 1 1 32 66 45 "'11.7'"
2012 19 15 0 1 69 85 28 "'12.4'"
2012 16 24 1 0 69 109 51 "'13.35'"
2012 17 17 0 0 84 63 41 "'11.4'"
2012 16 20 0 1 64 102 31 "'14.9'"
2012 9 27 0 0 58 162 74 "'19.9'"
2012 11 26 0 1 59 86 19 "'11.2'"
2012 14 23 0 1 78 114 51 "'14.6'"
2012 19 17 1 0 57 164 73 "'17.6'"
2012 13 20 1 1 60 119 24 "'14.05'"
2012 14 22 1 0 68 126 61 "'16.1'"
2012 15 19 1 1 68 132 23 "'13.35'"
2012 15 24 1 1 73 142 14 "'11.85'"
2012 14 19 1 0 69 83 54 "'11.95'"
2012 16 23 0 1 67 94 51 "'14.75'"
2012 17 15 0 0 60 81 62 "'15.15'"
2012 12 27 1 1 65 166 36 "'13.2'"
2012 15 26 0 0 66 110 59 "'16.85'"
2012 17 22 0 1 74 64 24 "'7.85'"
2012 15 22 1 0 81 93 26 "'7.7'"
2012 10 18 0 0 72 104 54 "'12.6'"
2012 16 15 0 1 55 105 39 "'7.85'"
2012 15 22 0 1 49 49 16 "'10.95'"
2012 11 27 0 0 74 88 36 "'12.35'"
2012 16 10 0 1 53 95 31 "'9.95'"
2012 16 20 0 1 64 102 31 "'14.9'"
2012 16 17 0 0 65 99 42 "'16.65'"
2012 14 23 0 1 57 63 39 "'13.4'"
2012 14 19 0 0 51 76 25 "'13.95'"
2012 16 13 0 0 80 109 31 "'15.7'"
2012 16 27 0 1 67 117 38 "'16.85'"
2012 18 23 0 1 70 57 31 "'10.95'"
2012 14 16 0 0 74 120 17 "'15.35'"
2012 20 25 0 1 75 73 22 "'12.2'"
2012 15 2 0 0 70 91 55 "'15.1'"
2012 16 26 0 0 69 108 62 "'17.75'"
2012 16 20 0 1 65 105 51 "'15.2'"
2012 16 23 1 0 55 117 30 "'14.6'"
2012 12 22 0 0 71 119 49 "'16.65'"
2012 8 24 0 1 65 31 16 "'8.1'"

par3 <- 'No Linear Trend'
par2 <- 'Do not include Seasonal Dummies'
par1 <- '1'
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)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
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()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
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) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='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$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
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, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.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,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.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,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
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,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
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,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
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='mytable6.tab')
}