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.
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'citation()' on how to cite R or R packages in publications.
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> x <- array(list(1.43,0,1.43,0,1.43,0,1.43,0,1.43,0,1.43,0,1.44,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.48,0,1.57,0,1.58,0,1.58,0,1.58,0,1.58,0,1.59,1,1.6,1,1.6,1,1.61,1,1.61,1,1.61,1,1.62,1,1.63,1,1.63,1,1.64,1,1.64,1,1.64,1,1.64,1,1.64,1,1.65,1,1.65,1,1.65,1,1.65,1),dim=c(2,60),dimnames=list(c('Broodprijzen','X'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Broodprijzen','X'),1:60))
> 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 = '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
Broodprijzen X
1 1.43 0
2 1.43 0
3 1.43 0
4 1.43 0
5 1.43 0
6 1.43 0
7 1.44 0
8 1.48 0
9 1.48 0
10 1.48 0
11 1.48 0
12 1.48 0
13 1.48 0
14 1.48 0
15 1.48 0
16 1.48 0
17 1.48 0
18 1.48 0
19 1.48 0
20 1.48 0
21 1.48 0
22 1.48 0
23 1.48 0
24 1.48 0
25 1.48 0
26 1.48 0
27 1.48 0
28 1.48 0
29 1.48 0
30 1.48 0
31 1.48 0
32 1.48 0
33 1.48 0
34 1.48 0
35 1.48 0
36 1.48 0
37 1.48 0
38 1.57 0
39 1.58 0
40 1.58 0
41 1.58 0
42 1.58 0
43 1.59 1
44 1.60 1
45 1.60 1
46 1.61 1
47 1.61 1
48 1.61 1
49 1.62 1
50 1.63 1
51 1.63 1
52 1.64 1
53 1.64 1
54 1.64 1
55 1.64 1
56 1.64 1
57 1.65 1
58 1.65 1
59 1.65 1
60 1.65 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
1.4836 0.1442
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.053571 -0.003571 -0.003571 0.002222 0.096429
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.483571 0.005394 275.04 <2e-16 ***
X 0.144206 0.009848 14.64 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.03496 on 58 degrees of freedom
Multiple R-squared: 0.7871, Adjusted R-squared: 0.7834
F-statistic: 214.4 on 1 and 58 DF, p-value: < 2.2e-16
> 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,] 7.146303e-43 1.429261e-42 1.000000e+00
[2,] 8.270240e-57 1.654048e-56 1.000000e+00
[3,] 1.383718e-04 2.767437e-04 9.998616e-01
[4,] 1.086805e-01 2.173609e-01 8.913195e-01
[5,] 2.101528e-01 4.203057e-01 7.898472e-01
[6,] 2.591574e-01 5.183148e-01 7.408426e-01
[7,] 2.735293e-01 5.470586e-01 7.264707e-01
[8,] 2.670164e-01 5.340328e-01 7.329836e-01
[9,] 2.481758e-01 4.963517e-01 7.518242e-01
[10,] 2.225121e-01 4.450241e-01 7.774879e-01
[11,] 1.937535e-01 3.875070e-01 8.062465e-01
[12,] 1.644924e-01 3.289848e-01 8.355076e-01
[13,] 1.365089e-01 2.730178e-01 8.634911e-01
[14,] 1.109550e-01 2.219101e-01 8.890450e-01
[15,] 8.848226e-02 1.769645e-01 9.115177e-01
[16,] 6.934940e-02 1.386988e-01 9.306506e-01
[17,] 5.352226e-02 1.070445e-01 9.464777e-01
[18,] 4.076569e-02 8.153137e-02 9.592343e-01
[19,] 3.072459e-02 6.144918e-02 9.692754e-01
[20,] 2.299037e-02 4.598075e-02 9.770096e-01
[21,] 1.715087e-02 3.430174e-02 9.828491e-01
[22,] 1.282415e-02 2.564830e-02 9.871759e-01
[23,] 9.678327e-03 1.935665e-02 9.903217e-01
[24,] 7.440839e-03 1.488168e-02 9.925592e-01
[25,] 5.901259e-03 1.180252e-02 9.940987e-01
[26,] 4.912894e-03 9.825788e-03 9.950871e-01
[27,] 4.401532e-03 8.803064e-03 9.955985e-01
[28,] 4.402201e-03 8.804403e-03 9.955978e-01
[29,] 5.198860e-03 1.039772e-02 9.948011e-01
[30,] 7.928638e-03 1.585728e-02 9.920714e-01
[31,] 1.810554e-02 3.621109e-02 9.818945e-01
[32,] 7.829636e-02 1.565927e-01 9.217036e-01
[33,] 6.578713e-01 6.842574e-01 3.421287e-01
[34,] 9.365441e-01 1.269119e-01 6.345593e-02
[35,] 9.857714e-01 2.845721e-02 1.422860e-02
[36,] 9.943473e-01 1.130546e-02 5.652730e-03
[37,] 9.966005e-01 6.799056e-03 3.399528e-03
[38,] 9.972472e-01 5.505627e-03 2.752814e-03
[39,] 9.986045e-01 2.791032e-03 1.395516e-03
[40,] 9.989652e-01 2.069699e-03 1.034850e-03
[41,] 9.994802e-01 1.039623e-03 5.198117e-04
[42,] 9.995527e-01 8.945910e-04 4.472955e-04
[43,] 9.997440e-01 5.120261e-04 2.560131e-04
[44,] 9.999494e-01 1.011764e-04 5.058818e-05
[45,] 9.999829e-01 3.413664e-05 1.706832e-05
[46,] 9.999762e-01 4.756485e-05 2.378243e-05
[47,] 9.999844e-01 3.115184e-05 1.557592e-05
[48,] 9.999250e-01 1.500652e-04 7.503258e-05
[49,] 9.996662e-01 6.675794e-04 3.337897e-04
[50,] 9.986811e-01 2.637858e-03 1.318929e-03
[51,] 9.958795e-01 8.240954e-03 4.120477e-03
> postscript(file="/var/www/html/rcomp/tmp/17rlk1258738755.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2u4am1258738755.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/37hws1258738755.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/40pfw1258738755.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5mxga1258738755.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 = 60
Frequency = 1
1 2 3 4 5 6
-0.053571429 -0.053571429 -0.053571429 -0.053571429 -0.053571429 -0.053571429
7 8 9 10 11 12
-0.043571429 -0.003571429 -0.003571429 -0.003571429 -0.003571429 -0.003571429
13 14 15 16 17 18
-0.003571429 -0.003571429 -0.003571429 -0.003571429 -0.003571429 -0.003571429
19 20 21 22 23 24
-0.003571429 -0.003571429 -0.003571429 -0.003571429 -0.003571429 -0.003571429
25 26 27 28 29 30
-0.003571429 -0.003571429 -0.003571429 -0.003571429 -0.003571429 -0.003571429
31 32 33 34 35 36
-0.003571429 -0.003571429 -0.003571429 -0.003571429 -0.003571429 -0.003571429
37 38 39 40 41 42
-0.003571429 0.086428571 0.096428571 0.096428571 0.096428571 0.096428571
43 44 45 46 47 48
-0.037777778 -0.027777778 -0.027777778 -0.017777778 -0.017777778 -0.017777778
49 50 51 52 53 54
-0.007777778 0.002222222 0.002222222 0.012222222 0.012222222 0.012222222
55 56 57 58 59 60
0.012222222 0.012222222 0.022222222 0.022222222 0.022222222 0.022222222
> postscript(file="/var/www/html/rcomp/tmp/6xqg91258738755.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.053571429 NA
1 -0.053571429 -0.053571429
2 -0.053571429 -0.053571429
3 -0.053571429 -0.053571429
4 -0.053571429 -0.053571429
5 -0.053571429 -0.053571429
6 -0.043571429 -0.053571429
7 -0.003571429 -0.043571429
8 -0.003571429 -0.003571429
9 -0.003571429 -0.003571429
10 -0.003571429 -0.003571429
11 -0.003571429 -0.003571429
12 -0.003571429 -0.003571429
13 -0.003571429 -0.003571429
14 -0.003571429 -0.003571429
15 -0.003571429 -0.003571429
16 -0.003571429 -0.003571429
17 -0.003571429 -0.003571429
18 -0.003571429 -0.003571429
19 -0.003571429 -0.003571429
20 -0.003571429 -0.003571429
21 -0.003571429 -0.003571429
22 -0.003571429 -0.003571429
23 -0.003571429 -0.003571429
24 -0.003571429 -0.003571429
25 -0.003571429 -0.003571429
26 -0.003571429 -0.003571429
27 -0.003571429 -0.003571429
28 -0.003571429 -0.003571429
29 -0.003571429 -0.003571429
30 -0.003571429 -0.003571429
31 -0.003571429 -0.003571429
32 -0.003571429 -0.003571429
33 -0.003571429 -0.003571429
34 -0.003571429 -0.003571429
35 -0.003571429 -0.003571429
36 -0.003571429 -0.003571429
37 0.086428571 -0.003571429
38 0.096428571 0.086428571
39 0.096428571 0.096428571
40 0.096428571 0.096428571
41 0.096428571 0.096428571
42 -0.037777778 0.096428571
43 -0.027777778 -0.037777778
44 -0.027777778 -0.027777778
45 -0.017777778 -0.027777778
46 -0.017777778 -0.017777778
47 -0.017777778 -0.017777778
48 -0.007777778 -0.017777778
49 0.002222222 -0.007777778
50 0.002222222 0.002222222
51 0.012222222 0.002222222
52 0.012222222 0.012222222
53 0.012222222 0.012222222
54 0.012222222 0.012222222
55 0.012222222 0.012222222
56 0.022222222 0.012222222
57 0.022222222 0.022222222
58 0.022222222 0.022222222
59 0.022222222 0.022222222
60 NA 0.022222222
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.053571429 -0.053571429
[2,] -0.053571429 -0.053571429
[3,] -0.053571429 -0.053571429
[4,] -0.053571429 -0.053571429
[5,] -0.053571429 -0.053571429
[6,] -0.043571429 -0.053571429
[7,] -0.003571429 -0.043571429
[8,] -0.003571429 -0.003571429
[9,] -0.003571429 -0.003571429
[10,] -0.003571429 -0.003571429
[11,] -0.003571429 -0.003571429
[12,] -0.003571429 -0.003571429
[13,] -0.003571429 -0.003571429
[14,] -0.003571429 -0.003571429
[15,] -0.003571429 -0.003571429
[16,] -0.003571429 -0.003571429
[17,] -0.003571429 -0.003571429
[18,] -0.003571429 -0.003571429
[19,] -0.003571429 -0.003571429
[20,] -0.003571429 -0.003571429
[21,] -0.003571429 -0.003571429
[22,] -0.003571429 -0.003571429
[23,] -0.003571429 -0.003571429
[24,] -0.003571429 -0.003571429
[25,] -0.003571429 -0.003571429
[26,] -0.003571429 -0.003571429
[27,] -0.003571429 -0.003571429
[28,] -0.003571429 -0.003571429
[29,] -0.003571429 -0.003571429
[30,] -0.003571429 -0.003571429
[31,] -0.003571429 -0.003571429
[32,] -0.003571429 -0.003571429
[33,] -0.003571429 -0.003571429
[34,] -0.003571429 -0.003571429
[35,] -0.003571429 -0.003571429
[36,] -0.003571429 -0.003571429
[37,] 0.086428571 -0.003571429
[38,] 0.096428571 0.086428571
[39,] 0.096428571 0.096428571
[40,] 0.096428571 0.096428571
[41,] 0.096428571 0.096428571
[42,] -0.037777778 0.096428571
[43,] -0.027777778 -0.037777778
[44,] -0.027777778 -0.027777778
[45,] -0.017777778 -0.027777778
[46,] -0.017777778 -0.017777778
[47,] -0.017777778 -0.017777778
[48,] -0.007777778 -0.017777778
[49,] 0.002222222 -0.007777778
[50,] 0.002222222 0.002222222
[51,] 0.012222222 0.002222222
[52,] 0.012222222 0.012222222
[53,] 0.012222222 0.012222222
[54,] 0.012222222 0.012222222
[55,] 0.012222222 0.012222222
[56,] 0.022222222 0.012222222
[57,] 0.022222222 0.022222222
[58,] 0.022222222 0.022222222
[59,] 0.022222222 0.022222222
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.053571429 -0.053571429
2 -0.053571429 -0.053571429
3 -0.053571429 -0.053571429
4 -0.053571429 -0.053571429
5 -0.053571429 -0.053571429
6 -0.043571429 -0.053571429
7 -0.003571429 -0.043571429
8 -0.003571429 -0.003571429
9 -0.003571429 -0.003571429
10 -0.003571429 -0.003571429
11 -0.003571429 -0.003571429
12 -0.003571429 -0.003571429
13 -0.003571429 -0.003571429
14 -0.003571429 -0.003571429
15 -0.003571429 -0.003571429
16 -0.003571429 -0.003571429
17 -0.003571429 -0.003571429
18 -0.003571429 -0.003571429
19 -0.003571429 -0.003571429
20 -0.003571429 -0.003571429
21 -0.003571429 -0.003571429
22 -0.003571429 -0.003571429
23 -0.003571429 -0.003571429
24 -0.003571429 -0.003571429
25 -0.003571429 -0.003571429
26 -0.003571429 -0.003571429
27 -0.003571429 -0.003571429
28 -0.003571429 -0.003571429
29 -0.003571429 -0.003571429
30 -0.003571429 -0.003571429
31 -0.003571429 -0.003571429
32 -0.003571429 -0.003571429
33 -0.003571429 -0.003571429
34 -0.003571429 -0.003571429
35 -0.003571429 -0.003571429
36 -0.003571429 -0.003571429
37 0.086428571 -0.003571429
38 0.096428571 0.086428571
39 0.096428571 0.096428571
40 0.096428571 0.096428571
41 0.096428571 0.096428571
42 -0.037777778 0.096428571
43 -0.027777778 -0.037777778
44 -0.027777778 -0.027777778
45 -0.017777778 -0.027777778
46 -0.017777778 -0.017777778
47 -0.017777778 -0.017777778
48 -0.007777778 -0.017777778
49 0.002222222 -0.007777778
50 0.002222222 0.002222222
51 0.012222222 0.002222222
52 0.012222222 0.012222222
53 0.012222222 0.012222222
54 0.012222222 0.012222222
55 0.012222222 0.012222222
56 0.022222222 0.012222222
57 0.022222222 0.022222222
58 0.022222222 0.022222222
59 0.022222222 0.022222222
> 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/73td91258738755.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8iuxx1258738755.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9jkc41258738755.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10nhol1258738755.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11r9031258738755.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/129wao1258738755.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/137alv1258738755.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/14577o1258738755.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/15xk5x1258738755.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/16tauz1258738755.tab")
+ }
>
> system("convert tmp/17rlk1258738755.ps tmp/17rlk1258738755.png")
> system("convert tmp/2u4am1258738755.ps tmp/2u4am1258738755.png")
> system("convert tmp/37hws1258738755.ps tmp/37hws1258738755.png")
> system("convert tmp/40pfw1258738755.ps tmp/40pfw1258738755.png")
> system("convert tmp/5mxga1258738755.ps tmp/5mxga1258738755.png")
> system("convert tmp/6xqg91258738755.ps tmp/6xqg91258738755.png")
> system("convert tmp/73td91258738755.ps tmp/73td91258738755.png")
> system("convert tmp/8iuxx1258738755.ps tmp/8iuxx1258738755.png")
> system("convert tmp/9jkc41258738755.ps tmp/9jkc41258738755.png")
> system("convert tmp/10nhol1258738755.ps tmp/10nhol1258738755.png")
>
>
> proc.time()
user system elapsed
2.413 1.520 2.995