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(4143,0,4429,0,5219,0,4929,0,5761,0,5592,0,4163,0,4962,0,5208,0,4755,0,4491,0,5732,0,5731,0,5040,0,6102,0,4904,0,5369,0,5578,0,4619,0,4731,0,5011,0,5299,0,4146,0,4625,0,4736,0,4219,0,5116,0,4205,1,4121,1,5103,1,4300,1,4578,1,3809,1,5526,1,4248,1,3830,1,4428,1,4834,1,4406,1,4565,1,4104,1,4798,1,3935,1,3792,1,4387,1,4006,1,4078,1,4724,1),dim=c(2,48),dimnames=list(c('y','x
'),1:48))
> y <- array(NA,dim=c(2,48),dimnames=list(c('y','x
'),1:48))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Include Monthly 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
y x\r M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 4143 0 1 0 0 0 0 0 0 0 0 0 0 1
2 4429 0 0 1 0 0 0 0 0 0 0 0 0 2
3 5219 0 0 0 1 0 0 0 0 0 0 0 0 3
4 4929 0 0 0 0 1 0 0 0 0 0 0 0 4
5 5761 0 0 0 0 0 1 0 0 0 0 0 0 5
6 5592 0 0 0 0 0 0 1 0 0 0 0 0 6
7 4163 0 0 0 0 0 0 0 1 0 0 0 0 7
8 4962 0 0 0 0 0 0 0 0 1 0 0 0 8
9 5208 0 0 0 0 0 0 0 0 0 1 0 0 9
10 4755 0 0 0 0 0 0 0 0 0 0 1 0 10
11 4491 0 0 0 0 0 0 0 0 0 0 0 1 11
12 5732 0 0 0 0 0 0 0 0 0 0 0 0 12
13 5731 0 1 0 0 0 0 0 0 0 0 0 0 13
14 5040 0 0 1 0 0 0 0 0 0 0 0 0 14
15 6102 0 0 0 1 0 0 0 0 0 0 0 0 15
16 4904 0 0 0 0 1 0 0 0 0 0 0 0 16
17 5369 0 0 0 0 0 1 0 0 0 0 0 0 17
18 5578 0 0 0 0 0 0 1 0 0 0 0 0 18
19 4619 0 0 0 0 0 0 0 1 0 0 0 0 19
20 4731 0 0 0 0 0 0 0 0 1 0 0 0 20
21 5011 0 0 0 0 0 0 0 0 0 1 0 0 21
22 5299 0 0 0 0 0 0 0 0 0 0 1 0 22
23 4146 0 0 0 0 0 0 0 0 0 0 0 1 23
24 4625 0 0 0 0 0 0 0 0 0 0 0 0 24
25 4736 0 1 0 0 0 0 0 0 0 0 0 0 25
26 4219 0 0 1 0 0 0 0 0 0 0 0 0 26
27 5116 0 0 0 1 0 0 0 0 0 0 0 0 27
28 4205 1 0 0 0 1 0 0 0 0 0 0 0 28
29 4121 1 0 0 0 0 1 0 0 0 0 0 0 29
30 5103 1 0 0 0 0 0 1 0 0 0 0 0 30
31 4300 1 0 0 0 0 0 0 1 0 0 0 0 31
32 4578 1 0 0 0 0 0 0 0 1 0 0 0 32
33 3809 1 0 0 0 0 0 0 0 0 1 0 0 33
34 5526 1 0 0 0 0 0 0 0 0 0 1 0 34
35 4248 1 0 0 0 0 0 0 0 0 0 0 1 35
36 3830 1 0 0 0 0 0 0 0 0 0 0 0 36
37 4428 1 1 0 0 0 0 0 0 0 0 0 0 37
38 4834 1 0 1 0 0 0 0 0 0 0 0 0 38
39 4406 1 0 0 1 0 0 0 0 0 0 0 0 39
40 4565 1 0 0 0 1 0 0 0 0 0 0 0 40
41 4104 1 0 0 0 0 1 0 0 0 0 0 0 41
42 4798 1 0 0 0 0 0 1 0 0 0 0 0 42
43 3935 1 0 0 0 0 0 0 1 0 0 0 0 43
44 3792 1 0 0 0 0 0 0 0 1 0 0 0 44
45 4387 1 0 0 0 0 0 0 0 0 1 0 0 45
46 4006 1 0 0 0 0 0 0 0 0 0 1 0 46
47 4078 1 0 0 0 0 0 0 0 0 0 0 1 47
48 4724 1 0 0 0 0 0 0 0 0 0 0 0 48
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `x\r` M1 M2 M3 M4
5134.772 -467.044 -148.628 -271.844 314.189 -123.267
M5 M6 M7 M8 M9 M10
70.517 505.300 -502.417 -235.133 -141.350 157.183
M11 t
-492.783 -5.783
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-837.4 -365.0 2.5 259.0 897.7
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5134.772 307.393 16.704 <2e-16 ***
`x\r` -467.044 282.083 -1.656 0.107
M1 -148.628 340.191 -0.437 0.665
M2 -271.844 338.818 -0.802 0.428
M3 314.189 337.746 0.930 0.359
M4 -123.267 344.278 -0.358 0.723
M5 70.517 342.014 0.206 0.838
M6 505.300 340.039 1.486 0.146
M7 -502.417 338.359 -1.485 0.147
M8 -235.133 336.978 -0.698 0.490
M9 -141.350 335.900 -0.421 0.677
M10 157.183 335.128 0.469 0.642
M11 -492.783 334.664 -1.472 0.150
t -5.783 10.179 -0.568 0.574
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 473.1 on 34 degrees of freedom
Multiple R-squared: 0.5309, Adjusted R-squared: 0.3515
F-statistic: 2.96 on 13 and 34 DF, p-value: 0.00555
> 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,] 0.88387506 0.2322499 0.1161249
[2,] 0.82056847 0.3588631 0.1794315
[3,] 0.70240313 0.5951937 0.2975969
[4,] 0.64449290 0.7110142 0.3555071
[5,] 0.60673601 0.7865280 0.3932640
[6,] 0.49594679 0.9918936 0.5040532
[7,] 0.43952463 0.8790493 0.5604754
[8,] 0.53861227 0.9227755 0.4613877
[9,] 0.43348211 0.8669642 0.5665179
[10,] 0.46313827 0.9262765 0.5368617
[11,] 0.36528439 0.7305688 0.6347156
[12,] 0.27775977 0.5555195 0.7222402
[13,] 0.19489245 0.3897849 0.8051076
[14,] 0.11937646 0.2387529 0.8806235
[15,] 0.07072583 0.1414517 0.9292742
> postscript(file="/var/www/html/rcomp/tmp/1x2cv1258729920.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2nkht1258729920.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3wg2k1258729920.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/40z271258729920.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5ur4b1258729920.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 = 48
Frequency = 1
1 2 3 4 5 6 7
-837.36111 -422.36111 -212.61111 -59.37222 584.62778 -13.37222 -428.87222
8 9 10 11 12 13 14
108.62778 266.62778 -479.12222 -87.37222 666.62778 820.03889 258.03889
15 16 17 18 19 20 21
739.78889 -14.97222 262.02778 42.02778 96.52778 -52.97222 139.02778
22 23 24 25 26 27 28
134.27778 -362.97222 -370.97222 -105.56111 -493.56111 -176.81111 -177.52778
29 30 31 32 33 34 35
-449.52778 103.47222 313.97222 330.47222 -526.52778 897.72222 275.47222
36 37 38 39 40 41 42
-629.52778 122.88333 657.88333 -350.36667 251.87222 -397.12778 -132.12778
43 44 45 46 47 48
18.37222 -386.12778 120.87222 -552.87778 174.87222 333.87222
> postscript(file="/var/www/html/rcomp/tmp/6wezz1258729920.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 = 48
Frequency = 1
lag(myerror, k = 1) myerror
0 -837.36111 NA
1 -422.36111 -837.36111
2 -212.61111 -422.36111
3 -59.37222 -212.61111
4 584.62778 -59.37222
5 -13.37222 584.62778
6 -428.87222 -13.37222
7 108.62778 -428.87222
8 266.62778 108.62778
9 -479.12222 266.62778
10 -87.37222 -479.12222
11 666.62778 -87.37222
12 820.03889 666.62778
13 258.03889 820.03889
14 739.78889 258.03889
15 -14.97222 739.78889
16 262.02778 -14.97222
17 42.02778 262.02778
18 96.52778 42.02778
19 -52.97222 96.52778
20 139.02778 -52.97222
21 134.27778 139.02778
22 -362.97222 134.27778
23 -370.97222 -362.97222
24 -105.56111 -370.97222
25 -493.56111 -105.56111
26 -176.81111 -493.56111
27 -177.52778 -176.81111
28 -449.52778 -177.52778
29 103.47222 -449.52778
30 313.97222 103.47222
31 330.47222 313.97222
32 -526.52778 330.47222
33 897.72222 -526.52778
34 275.47222 897.72222
35 -629.52778 275.47222
36 122.88333 -629.52778
37 657.88333 122.88333
38 -350.36667 657.88333
39 251.87222 -350.36667
40 -397.12778 251.87222
41 -132.12778 -397.12778
42 18.37222 -132.12778
43 -386.12778 18.37222
44 120.87222 -386.12778
45 -552.87778 120.87222
46 174.87222 -552.87778
47 333.87222 174.87222
48 NA 333.87222
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -422.36111 -837.36111
[2,] -212.61111 -422.36111
[3,] -59.37222 -212.61111
[4,] 584.62778 -59.37222
[5,] -13.37222 584.62778
[6,] -428.87222 -13.37222
[7,] 108.62778 -428.87222
[8,] 266.62778 108.62778
[9,] -479.12222 266.62778
[10,] -87.37222 -479.12222
[11,] 666.62778 -87.37222
[12,] 820.03889 666.62778
[13,] 258.03889 820.03889
[14,] 739.78889 258.03889
[15,] -14.97222 739.78889
[16,] 262.02778 -14.97222
[17,] 42.02778 262.02778
[18,] 96.52778 42.02778
[19,] -52.97222 96.52778
[20,] 139.02778 -52.97222
[21,] 134.27778 139.02778
[22,] -362.97222 134.27778
[23,] -370.97222 -362.97222
[24,] -105.56111 -370.97222
[25,] -493.56111 -105.56111
[26,] -176.81111 -493.56111
[27,] -177.52778 -176.81111
[28,] -449.52778 -177.52778
[29,] 103.47222 -449.52778
[30,] 313.97222 103.47222
[31,] 330.47222 313.97222
[32,] -526.52778 330.47222
[33,] 897.72222 -526.52778
[34,] 275.47222 897.72222
[35,] -629.52778 275.47222
[36,] 122.88333 -629.52778
[37,] 657.88333 122.88333
[38,] -350.36667 657.88333
[39,] 251.87222 -350.36667
[40,] -397.12778 251.87222
[41,] -132.12778 -397.12778
[42,] 18.37222 -132.12778
[43,] -386.12778 18.37222
[44,] 120.87222 -386.12778
[45,] -552.87778 120.87222
[46,] 174.87222 -552.87778
[47,] 333.87222 174.87222
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -422.36111 -837.36111
2 -212.61111 -422.36111
3 -59.37222 -212.61111
4 584.62778 -59.37222
5 -13.37222 584.62778
6 -428.87222 -13.37222
7 108.62778 -428.87222
8 266.62778 108.62778
9 -479.12222 266.62778
10 -87.37222 -479.12222
11 666.62778 -87.37222
12 820.03889 666.62778
13 258.03889 820.03889
14 739.78889 258.03889
15 -14.97222 739.78889
16 262.02778 -14.97222
17 42.02778 262.02778
18 96.52778 42.02778
19 -52.97222 96.52778
20 139.02778 -52.97222
21 134.27778 139.02778
22 -362.97222 134.27778
23 -370.97222 -362.97222
24 -105.56111 -370.97222
25 -493.56111 -105.56111
26 -176.81111 -493.56111
27 -177.52778 -176.81111
28 -449.52778 -177.52778
29 103.47222 -449.52778
30 313.97222 103.47222
31 330.47222 313.97222
32 -526.52778 330.47222
33 897.72222 -526.52778
34 275.47222 897.72222
35 -629.52778 275.47222
36 122.88333 -629.52778
37 657.88333 122.88333
38 -350.36667 657.88333
39 251.87222 -350.36667
40 -397.12778 251.87222
41 -132.12778 -397.12778
42 18.37222 -132.12778
43 -386.12778 18.37222
44 120.87222 -386.12778
45 -552.87778 120.87222
46 174.87222 -552.87778
47 333.87222 174.87222
> 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/7pnvw1258729920.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/83mz91258729920.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/99lst1258729920.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/109knp1258729920.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11pnro1258729920.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/12af031258729920.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/137i6s1258729921.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/14gh0e1258729921.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/1546091258729921.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/1671zu1258729921.tab")
+ }
>
> system("convert tmp/1x2cv1258729920.ps tmp/1x2cv1258729920.png")
> system("convert tmp/2nkht1258729920.ps tmp/2nkht1258729920.png")
> system("convert tmp/3wg2k1258729920.ps tmp/3wg2k1258729920.png")
> system("convert tmp/40z271258729920.ps tmp/40z271258729920.png")
> system("convert tmp/5ur4b1258729920.ps tmp/5ur4b1258729920.png")
> system("convert tmp/6wezz1258729920.ps tmp/6wezz1258729920.png")
> system("convert tmp/7pnvw1258729920.ps tmp/7pnvw1258729920.png")
> system("convert tmp/83mz91258729920.ps tmp/83mz91258729920.png")
> system("convert tmp/99lst1258729920.ps tmp/99lst1258729920.png")
> system("convert tmp/109knp1258729920.ps tmp/109knp1258729920.png")
>
>
> proc.time()
user system elapsed
2.273 1.524 2.700