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

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')