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

14	0	0	7	17	22
21	0	1	8	19	39
20	0	1	8	18	40
20	0	1	10	17	34
20	0	1	8	17	38
18	1	1	9	19	39
18	0	1	8	19	39
17	0	0	10	12	38
15	0	0	7	15	31
18	0	1	10	16	34
16	1	1	8	16	32
17	1	0	8	14	37
19	1	1	6	15	36
21	0	0	7	16	38
15	0	0	9	14	29
21	1	1	9	18	33
16	0	0	8	15	35
18	1	1	8	18	34
18	1	1	10	19	45
17	0	0	7	15	30
18	0	1	7	17	33
16	0	0	7	9	30
15	0	0	6	18	40
15	0	1	9	17	34
19	1	0	7	15	31
14	1	1	8	13	27
19	0	1	10	17	33
19	0	0	9	14	42
15	0	0	8	15	36
17	0	0	8	14	33
21	1	1	10	17	42
13	0	0	8	14	33
12	0	1	4	13	21
15	0	1	6	19	43
19	0	1	7	15	34
19	1	1	7	14	32
14	1	0	3	11	34
18	1	1	8	16	28
11	1	0	8	13	30
17	1	1	6	15	27
18	1	0	10	17	29
13	0	0	8	15	40
12	1	1	4	12	29
17	0	0	8	15	41
20	0	0	7	15	33
16	0	1	6	8	42
22	0	1	9	16	39
16	0	1	10	12	35
23	0	1	9	13	33
20	0	1	7	16	33
23	0	1	10	16	44
13	1	0	7	8	34
18	0	0	10	14	30
18	1	0	9	15	30
17	1	1	7	16	35
17	1	1	10	16	39
18	0	0	8	17	34
21	1	1	8	18	39
13	0	0	6	9	25
19	0	0	9	19	39
16	0	1	7	14	33
17	0	1	8	14	34
18	0	1	8	15	36
18	0	1	9	19	34
12	1	0	5	12	31
19	0	1	9	17	35
16	0	1	6	16	34
20	0	1	8	17	36
21	0	1	10	15	40
18	0	1	7	11	31
13	1	1	5	8	33
17	0	0	4	16	28
20	1	1	9	20	42
21	0	1	10	20	38
19	0	0	8	13	35
15	0	1	6	11	34
14	0	0	6	15	28
15	0	1	9	15	35
16	0	1	3	14	25
19	0	0	7	16	39
17	0	0	9	15	25
17	0	1	7	15	32
15	0	0	8	16	35
19	1	0	9	19	41
21	0	1	9	20	34
19	1	1	8	14	33
18	0	0	9	16	32
18	0	0	6	14	34
15	0	0	7	11	25
19	0	1	8	16	38
19	0	1	7	16	37
18	0	1	9	15	38
20	0	1	9	16	36
18	1	0	5	12	39
12	0	0	6	13	31
15	0	0	8	11	40
17	1	0	10	20	34
15	1	0	5	11	33
17	0	0	8	14	32
20	0	1	8	16	33
11	0	1	10	15	32
14	0	0	7	13	28
14	0	0	9	15	32
12	0	0	8	13	34
19	0	1	8	17	36
22	0	1	10	18	38
16	0	0	9	14	31
15	0	1	9	13	36
15	0	1	6	12	27
18	0	0	8	17	31
12	1	1	5	6	28
17	1	1	3	9	30
10	1	1	6	15	29
10	1	1	6	15	29
18	0	1	10	17	31
16	1	1	9	19	35
22	0	1	9	20	42
12	0	0	5	10	28
10	0	1	6	9	38
20	0	1	7	15	34
20	0	1	8	16	28
19	0	1	9	16	30
10	1	0	3	9	26
13	1	0	5	10	27
15	1	0	5	9	31
19	0	0	9	17	35
17	1	1	10	17	33
15	1	1	7	19	34
12	0	0	8	10	30
14	0	1	6	12	28
13	1	0	5	9	30
15	1	1	8	11	29
20	1	1	7	17	32
12	1	1	5	9	34
16	1	0	6	14	34
15	1	1	10	19	35
17	1	1	10	17	40
15	1	1	6	13	34
12	1	1	4	11	28
17	1	0	8	14	35
11	1	1	5	7	31
16	1	1	7	17	33
16	1	1	10	16	36
15	1	1	8	12	30
17	0	0	7	10	27
7	0	1	2	10	30
14	0	1	7	8	25
21	0	1	9	18	39
20	1	1	8	15	36
15	0	0	5	18	31
13	1	0	8	14	33
20	0	0	6	16	30
15	1	0	7	11	31
16	1	1	10	16	32
19	0	0	8	17	33
16	1	1	10	20	43
19	1	0	9	14	35
17	1	1	8	16	36
19	1	1	10	17	42
14	0	0	4	11	31
16	0	1	6	13	26
16	0	0	9	11	38
14	1	0	4	8	27
11	1	1	6	9	27
17	0	0	7	9	31
20	0	1	9	12	32
20	1	1	8	15	36
17	0	0	6	18	36
13	1	1	4	10	25
20	1	0	8	15	33
17	0	0	8	16	32
16	0	1	9	18	40
19	0	0	6	15	36
20	1	0	5	17	36
17	0	1	5	17	35
14	1	1	8	14	31
20	1	1	8	17	31
19	1	1	9	13	36
18	1	0	7	16	36
17	1	1	9	12	37
17	1	0	8	17	31
10	0	0	6	10	31
12	0	1	7	9	26
19	0	1	8	15	35
19	1	0	8	14	32
21	1	0	7	16	36
21	0	0	7	17	37
17	0	0	8	18	34
19	1	1	8	14	33
21	1	0	9	17	35
15	1	1	9	14	31
14	0	1	9	15	38
15	1	0	8	14	36
13	1	1	2	10	32
14	0	1	8	9	28
14	0	1	8	12	33
19	1	1	8	13	31
17	0	1	7	14	34
19	1	1	10	18	33
18	1	1	8	15	36
21	1	1	10	14	36
12	0	1	5	10	29
15	1	0	4	9	31
19	1	1	10	17	35
16	1	1	8	12	31
19	1	0	7	16	35
16	1	0	5	11	36
18	1	1	7	13	35
18	1	0	9	12	38
15	1	0	8	15	28
15	1	0	8	15	28
11	1	1	2	10	28
18	1	1	9	16	34
13	1	1	8	11	31
9	1	1	5	14	44
21	1	0	7	17	36
19	1	1	8	16	36
13	1	1	7	16	34
15	0	0	5	11	32
18	1	1	10	16	36
16	1	0	6	13	38
10	1	1	6	7	28
12	1	0	5	13	37
18	1	1	7	14	32
17	1	1	8	14	36
15	1	0	8	9	30
16	1	1	4	15	38
19	0	0	9	16	37
15	1	0	4	11	33
24	1	1	10	20	43
15	1	1	6	14	26
14	1	0	6	9	33
16	1	0	8	16	34
16	1	0	8	13	36
20	1	0	8	15	36
20	1	0	8	15	36
20	1	0	8	15	36
20	1	0	8	15	39
14	1	1	7	14	33
22	1	1	7	15	35
16	1	1	8	13	25
9	0	1	10	12	26
14	1	0	10	17	35
11	1	1	3	8	16
23	0	0	8	17	40
10	0	1	2	10	14
10	0	0	4	9	22
8	0	0	4	9	21
21	1	0	9	15	38
18	1	1	10	14	38
15	1	1	6	12	27
20	1	1	10	16	40
17	0	1	10	19	40
5	1	0	3	6	19
14	1	1	9	11	29
19	1	0	9	16	37
15	1	1	6	12	27
12	1	1	5	12	26
10	0	0	4	8	24
11	1	1	4	11	29
15	1	1	6	8	26
15	1	1	6	12	27
20	0	1	8	16	35
20	1	1	8	18	39
20	1	1	5	16	38
19	0	1	7	15	36
16	1	1	6	20	37
21	1	0	10	10	36
22	1	1	8	15	32
17	1	1	8	14	33
21	1	1	9	14	39
19	1	0	5	8	34
23	1	1	10	19	39
21	1	1	8	17	36
22	1	1	9	18	33
11	1	0	8	10	30
20	1	0	7	15	39
18	1	0	10	16	37
16	1	0	10	12	37
18	1	1	9	13	35
13	1	0	4	10	32
17	1	1	4	14	36
20	1	1	8	15	36
20	1	1	9	20	41
15	1	1	10	9	36
18	1	0	8	12	37
15	1	0	5	13	29
19	1	1	10	16	39
19	1	0	8	12	37
19	1	1	7	14	32
20	1	1	8	15	36
20	1	1	8	19	43
16	1	0	9	16	30
18	1	0	8	16	33
17	1	1	6	14	28
18	1	1	8	14	30
13	1	0	8	14	28
20	0	1	5	13	39
21	1	1	9	18	34
17	1	0	8	15	34
19	1	0	8	15	29
20	1	0	8	15	32
15	1	0	6	13	33
15	1	0	6	14	27
19	1	1	9	15	35
18	1	1	8	14	38
22	1	1	9	19	40
20	1	1	10	16	34
18	0	0	8	16	34
14	1	0	8	12	26
15	1	0	7	10	39
17	1	1	7	11	34
16	1	1	10	13	39
17	1	1	8	14	26
15	1	1	7	11	30
17	1	1	10	11	34
18	1	1	7	16	34
16	1	0	7	9	29
18	1	0	9	16	41
22	1	0	9	19	43
16	1	0	8	13	31
16	1	0	6	15	33
20	1	0	8	14	34
18	1	1	9	15	30
16	0	0	2	11	23
16	1	0	6	14	29
20	1	1	8	15	35
21	0	1	8	17	40
18	0	0	7	16	27
15	1	0	8	13	30
18	1	0	6	15	27
18	1	0	10	14	29
20	1	0	10	15	33
18	1	0	10	14	32
16	1	0	8	12	33
19	1	1	8	12	36
20	1	1	7	15	34
22	1	1	10	17	45
18	0	0	5	13	30
8	0	1	3	5	22
13	0	1	2	7	24
13	0	1	3	10	25
18	0	1	4	15	26
12	0	0	2	9	27
16	0	0	6	9	27
21	1	0	8	15	35
20	1	0	8	14	36
18	0	0	5	11	32
22	1	1	10	18	35
23	1	1	9	20	35
23	1	1	8	20	36
21	1	1	9	16	37
16	1	1	8	15	33
14	1	0	5	14	25
18	1	1	7	13	35
22	1	1	9	18	37
20	1	0	8	14	36
18	1	1	4	12	35
12	1	1	7	9	29
17	1	1	8	19	35
15	1	0	7	13	31
18	1	1	7	12	30
18	1	0	9	14	37
15	1	1	6	6	36
16	1	0	7	14	35
15	1	0	4	11	32
16	1	1	6	11	34
19	1	0	10	14	37
19	1	1	9	12	36
23	1	1	10	19	39
20	1	0	8	13	37
18	0	0	4	14	31
21	1	1	8	17	40
19	1	0	5	12	38
18	0	1	8	16	35
19	0	1	9	15	38
17	1	0	8	15	32
21	1	1	4	15	41
19	1	0	8	16	28
24	1	1	10	15	40
12	1	0	6	12	25
15	1	0	7	13	28
18	1	1	10	14	37
19	1	1	9	17	37
22	1	1	8	14	40
19	0	0	3	14	26
16	1	0	8	14	30
19	1	0	7	15	32
18	1	0	7	11	31
18	1	0	8	11	28
19	1	1	8	16	34
21	1	0	7	12	39
19	0	1	7	12	33
22	1	0	9	19	43
23	0	1	9	18	37
17	1	0	9	16	31
18	0	1	4	16	31
19	1	0	6	13	34
15	1	1	6	11	32
14	0	0	6	10	27
18	1	0	8	14	34
17	0	0	3	14	28
19	0	0	8	14	32
16	0	1	8	16	39
14	0	1	6	10	28
20	1	0	10	16	39
16	0	0	2	7	32
18	0	1	9	16	36
16	0	1	6	15	31
21	0	0	6	17	39
16	0	0	5	11	23
14	0	0	4	11	25
16	1	0	7	10	32
19	0	1	5	13	32
19	0	1	8	14	36
19	0	0	6	13	39
18	0	1	9	13	31
16	1	0	6	12	32
14	0	1	4	10	28
19	0	0	7	15	34
11	0	1	2	6	28
18	1	1	8	15	38
18	1	1	9	15	35
16	1	0	6	11	32
20	0	1	5	14	26
18	0	1	7	14	32
20	1	1	8	16	28
16	1	0	4	12	31
18	0	1	9	15	33
19	1	0	9	20	38
19	0	1	9	12	38
15	0	0	7	9	36
17	1	1	5	13	31
21	0	0	7	15	36
24	1	1	9	19	43
16	1	1	8	11	37
13	0	1	6	11	28
21	0	1	9	17	35
16	1	1	8	15	34
17	1	1	7	14	40
17	1	0	7	15	31
18	0	0	7	11	41
18	1	0	8	12	35
23	1	1	10	15	38
20	0	0	6	16	37
20	0	0	6	16	31

par6 <- '12'
par5 <- ''
par4 <- ''
par3 <- 'TRUE'
par2 <- 'Do not include Seasonal Dummies'
par1 <- '1'
library(lattice)
library(lmtest)
library(car)
library(MASS)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
mywarning <- ''
par6 <- as.numeric(par6)
if(is.na(par6)) {
par6 <- 12
mywarning = 'Warning: you did not specify the seasonality. The seasonal period was set to s = 12.'
}
par1 <- as.numeric(par1)
if(is.na(par1)) {
par1 <- 1
mywarning = 'Warning: you did not specify the column number of the endogenous series! The first column was selected by default.'
}
if (par4=='') par4 <- 0
par4 <- as.numeric(par4)
if (!is.numeric(par4)) par4 <- 0
if (par5=='') par5 <- 0
par5 <- as.numeric(par5)
if (!is.numeric(par5)) par5 <- 0
x <- na.omit(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'){
(n <- n -1)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par3 == 'Seasonal Differences (s)'){
(n <- n - par6)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-Bs)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+par6,j] - x[i,j]
}
}
x <- x2
}
if (par3 == 'First and Seasonal Differences (s)'){
(n <- n -1)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-B)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
(n <- n - par6)
x2 <- array(0, dim=c(n,k), dimnames=list(1:n, paste('(1-Bs)',colnames(x),sep='')))
for (i in 1:n) {
for (j in 1:k) {
x2[i,j] <- x[i+par6,j] - x[i,j]
}
}
x <- x2
}
if(par4 > 0) {
x2 <- array(0, dim=c(n-par4,par4), dimnames=list(1:(n-par4), paste(colnames(x)[par1],'(t-',1:par4,')',sep='')))
for (i in 1:(n-par4)) {
for (j in 1:par4) {
x2[i,j] <- x[i+par4-j,par1]
}
}
x <- cbind(x[(par4+1):n,], x2)
n <- n - par4
}
if(par5 > 0) {
x2 <- array(0, dim=c(n-par5*par6,par5), dimnames=list(1:(n-par5*par6), paste(colnames(x)[par1],'(t-',1:par5,'s)',sep='')))
for (i in 1:(n-par5*par6)) {
for (j in 1:par5) {
x2[i,j] <- x[i+par5*par6-j*par6,par1]
}
}
x <- cbind(x[(par5*par6+1):n,], x2)
n <- n - par5*par6
}
if (par2 == 'Include Seasonal Dummies'){
x2 <- array(0, dim=c(n,par6-1), dimnames=list(1:n, paste('M', seq(1:(par6-1)), sep ='')))
for (i in 1:(par6-1)){
x2[seq(i,n,par6),i] <- 1
}
x <- cbind(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[n,]))
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
print(x)
(k <- length(x[n,]))
head(x)
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$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
sresid <- studres(mylm)
hist(sresid, freq=FALSE, main='Distribution of Studentized Residuals')
xfit<-seq(min(sresid),max(sresid),length=40)
yfit<-dnorm(xfit)
lines(xfit, yfit)
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqPlot(mylm, main='QQ Plot')
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
print(z)
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$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.row.start(a)
a<-table.element(a, mywarning)
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,'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$coefficients)[i],header=TRUE)
a<-table.element(a,formatC(signif(mysum$coefficients[i,1],5),format='g',flag='+'))
a<-table.element(a,formatC(signif(mysum$coefficients[i,2],5),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$coefficients[i,3],4),format='e',flag='+'))
a<-table.element(a,formatC(signif(mysum$coefficients[i,4],4),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$coefficients[i,4]/2,4),format='g',flag=' '))
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,formatC(signif(sqrt(mysum$r.squared),6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a,formatC(signif(mysum$r.squared,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a,formatC(signif(mysum$adj.r.squared,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a,formatC(signif(mysum$fstatistic[1],6),format='g',flag=' '))
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,formatC(signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a,formatC(signif(mysum$sigma,6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a,formatC(signif(sum(myerror*myerror),6),format='g',flag=' '))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
myr <- as.numeric(mysum$resid)
myr
a <-table.start()
a <- table.row.start(a)
a <- table.element(a,'Menu of Residual Diagnostics',2,TRUE)
a <- table.row.end(a)
a <- table.row.start(a)
a <- table.element(a,'Description',1,TRUE)
a <- table.element(a,'Link',1,TRUE)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Histogram',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_histogram.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Central Tendency',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_centraltendency.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'QQ Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_fitdistrnorm.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Kernel Density Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_density.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Skewness/Kurtosis Test',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_skewness_kurtosis.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Skewness-Kurtosis Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_skewness_kurtosis_plot.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Harrell-Davis Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_harrell_davis.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Bootstrap Plot -- Central Tendency',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_bootstrapplot1.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Blocked Bootstrap Plot -- Central Tendency',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_bootstrapplot.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'(Partial) Autocorrelation Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_autocorrelation.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Spectral Analysis',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_spectrum.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Tukey lambda PPCC Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_tukeylambda.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <-table.element(a,'Box-Cox Normality Plot',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_boxcoxnorm.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a <- table.row.start(a)
a <- table.element(a,'Summary Statistics',1,header=TRUE)
a <- table.element(a,hyperlink( paste('https://supernova.wessa.net/rwasp_summary1.wasp?convertgetintopost=1&data=',paste(as.character(mysum$resid),sep='',collapse=' '),sep='') ,'Compute','Click here to examine the Residuals.'),1)
a <- table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable7.tab')
if(n < 200) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,formatC(signif(x[i],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(x[i]-mysum$resid[i],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(mysum$resid[i],6),format='g',flag=' '))
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,formatC(signif(gqarr[mypoint-kp3+1,1],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,2],6),format='g',flag=' '))
a<-table.element(a,formatC(signif(gqarr[mypoint-kp3+1,3],6),format='g',flag=' '))
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,formatC(signif(numsignificant1/numgqtests,6),format='g',flag=' '))
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')
}
}
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Ramsey RESET F-Test for powers (2 and 3) of fitted values',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
reset_test_fitted <- resettest(mylm,power=2:3,type='fitted')
a<-table.element(a,paste('
',RC.texteval('reset_test_fitted'),'
',sep=''))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Ramsey RESET F-Test for powers (2 and 3) of regressors',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
reset_test_regressors <- resettest(mylm,power=2:3,type='regressor')
a<-table.element(a,paste('
',RC.texteval('reset_test_regressors'),'
',sep=''))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Ramsey RESET F-Test for powers (2 and 3) of principal components',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
reset_test_principal_components <- resettest(mylm,power=2:3,type='princomp')
a<-table.element(a,paste('
',RC.texteval('reset_test_principal_components'),'
',sep=''))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable8.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Variance Inflation Factors (Multicollinearity)',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
vif <- vif(mylm)
a<-table.element(a,paste('
',RC.texteval('vif'),'
',sep=''))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable9.tab')