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(29.837,0,29.571,0,30.167,0,30.524,0,30.996,0,31.033,0,31.198,0,30.937,0,31.649,0,33.115,0,34.106,0,33.926,0,33.382,0,32.851,0,32.948,0,36.112,0,36.113,0,35.210,0,35.193,0,34.383,0,35.349,0,37.058,0,38.076,0,36.630,0,36.045,0,35.638,0,35.114,0,35.465,0,35.254,0,35.299,0,35.916,0,36.683,0,37.288,0,38.536,0,38.977,0,36.407,0,34.955,0,34.951,0,32.680,0,34.791,0,34.178,0,35.213,0,34.871,0,35.299,0,35.443,0,37.108,0,36.419,0,34.471,0,33.868,0,34.385,0,33.643,0,34.627,0,32.919,0,35.500,0,36.110,0,37.086,1,37.711,1,40.427,1,39.884,1,38.512,1,38.767,1),dim=c(2,61),dimnames=list(c('saldo_zichtrek','crisis'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('saldo_zichtrek','crisis'),1:61))
> 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
saldo_zichtrek crisis
1 29.837 0
2 29.571 0
3 30.167 0
4 30.524 0
5 30.996 0
6 31.033 0
7 31.198 0
8 30.937 0
9 31.649 0
10 33.115 0
11 34.106 0
12 33.926 0
13 33.382 0
14 32.851 0
15 32.948 0
16 36.112 0
17 36.113 0
18 35.210 0
19 35.193 0
20 34.383 0
21 35.349 0
22 37.058 0
23 38.076 0
24 36.630 0
25 36.045 0
26 35.638 0
27 35.114 0
28 35.465 0
29 35.254 0
30 35.299 0
31 35.916 0
32 36.683 0
33 37.288 0
34 38.536 0
35 38.977 0
36 36.407 0
37 34.955 0
38 34.951 0
39 32.680 0
40 34.791 0
41 34.178 0
42 35.213 0
43 34.871 0
44 35.299 0
45 35.443 0
46 37.108 0
47 36.419 0
48 34.471 0
49 33.868 0
50 34.385 0
51 33.643 0
52 34.627 0
53 32.919 0
54 35.500 0
55 36.110 0
56 37.086 1
57 37.711 1
58 40.427 1
59 39.884 1
60 38.512 1
61 38.767 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) crisis
34.517 4.214
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-4.9457 -1.1347 0.4343 1.3993 4.4603
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 34.5167 0.2878 119.943 < 2e-16 ***
crisis 4.2145 0.9176 4.593 2.34e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.134 on 59 degrees of freedom
Multiple R-squared: 0.2634, Adjusted R-squared: 0.2509
F-statistic: 21.1 on 1 and 59 DF, p-value: 2.344e-05
> 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,] 0.06268292 1.253658e-01 9.373171e-01
[2,] 0.04254760 8.509521e-02 9.574524e-01
[3,] 0.03357111 6.714222e-02 9.664289e-01
[4,] 0.02141920 4.283840e-02 9.785808e-01
[5,] 0.03144674 6.289349e-02 9.685533e-01
[6,] 0.19592931 3.918586e-01 8.040707e-01
[7,] 0.54822754 9.035449e-01 4.517725e-01
[8,] 0.70579985 5.884003e-01 2.942002e-01
[9,] 0.74966147 5.006771e-01 2.503385e-01
[10,] 0.76600703 4.679859e-01 2.339930e-01
[11,] 0.78813235 4.237353e-01 2.118677e-01
[12,] 0.95230326 9.539348e-02 4.769674e-02
[13,] 0.98486863 3.026273e-02 1.513137e-02
[14,] 0.98842429 2.315142e-02 1.157571e-02
[15,] 0.98979121 2.041758e-02 1.020879e-02
[16,] 0.98827765 2.344469e-02 1.172235e-02
[17,] 0.98863466 2.273067e-02 1.136534e-02
[18,] 0.99562199 8.756019e-03 4.378010e-03
[19,] 0.99934115 1.317700e-03 6.588500e-04
[20,] 0.99948844 1.023118e-03 5.115591e-04
[21,] 0.99937897 1.242061e-03 6.210306e-04
[22,] 0.99908199 1.836013e-03 9.180065e-04
[23,] 0.99848833 3.023339e-03 1.511670e-03
[24,] 0.99764864 4.702718e-03 2.351359e-03
[25,] 0.99624128 7.517448e-03 3.758724e-03
[26,] 0.99408822 1.182356e-02 5.911778e-03
[27,] 0.99180825 1.638350e-02 8.191752e-03
[28,] 0.99145043 1.709914e-02 8.549572e-03
[29,] 0.99366828 1.266344e-02 6.331719e-03
[30,] 0.99877361 2.452781e-03 1.226391e-03
[31,] 0.99995833 8.334090e-05 4.167045e-05
[32,] 0.99995640 8.719317e-05 4.359658e-05
[33,] 0.99989789 2.042128e-04 1.021064e-04
[34,] 0.99976854 4.629282e-04 2.314641e-04
[35,] 0.99986817 2.636694e-04 1.318347e-04
[36,] 0.99969404 6.119111e-04 3.059555e-04
[37,] 0.99941321 1.173572e-03 5.867859e-04
[38,] 0.99874592 2.508159e-03 1.254079e-03
[39,] 0.99735302 5.293965e-03 2.646983e-03
[40,] 0.99479858 1.040284e-02 5.201421e-03
[41,] 0.99045595 1.908810e-02 9.544049e-03
[42,] 0.99501773 9.964542e-03 4.982271e-03
[43,] 0.99615164 7.696718e-03 3.848359e-03
[44,] 0.99150164 1.699673e-02 8.498363e-03
[45,] 0.98381410 3.237181e-02 1.618590e-02
[46,] 0.96744925 6.510150e-02 3.255075e-02
[47,] 0.94979858 1.004028e-01 5.020142e-02
[48,] 0.90658244 1.868351e-01 9.341756e-02
[49,] 0.94812711 1.037458e-01 5.187289e-02
[50,] 0.89729437 2.054113e-01 1.027056e-01
[51,] 0.80304828 3.939034e-01 1.969517e-01
[52,] 0.80497968 3.900406e-01 1.950203e-01
> postscript(file="/var/www/html/rcomp/tmp/1m50l1258735481.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2y9zv1258735481.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ee5l1258735481.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4bqcg1258735481.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5sfo91258735481.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 = 61
Frequency = 1
1 2 3 4 5 6
-4.67967273 -4.94567273 -4.34967273 -3.99267273 -3.52067273 -3.48367273
7 8 9 10 11 12
-3.31867273 -3.57967273 -2.86767273 -1.40167273 -0.41067273 -0.59067273
13 14 15 16 17 18
-1.13467273 -1.66567273 -1.56867273 1.59532727 1.59632727 0.69332727
19 20 21 22 23 24
0.67632727 -0.13367273 0.83232727 2.54132727 3.55932727 2.11332727
25 26 27 28 29 30
1.52832727 1.12132727 0.59732727 0.94832727 0.73732727 0.78232727
31 32 33 34 35 36
1.39932727 2.16632727 2.77132727 4.01932727 4.46032727 1.89032727
37 38 39 40 41 42
0.43832727 0.43432727 -1.83667273 0.27432727 -0.33867273 0.69632727
43 44 45 46 47 48
0.35432727 0.78232727 0.92632727 2.59132727 1.90232727 -0.04567273
49 50 51 52 53 54
-0.64867273 -0.13167273 -0.87367273 0.11032727 -1.59767273 0.98332727
55 56 57 58 59 60
1.59332727 -1.64516667 -1.02016667 1.69583333 1.15283333 -0.21916667
61
0.03583333
> postscript(file="/var/www/html/rcomp/tmp/6x6y31258735481.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 = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 -4.67967273 NA
1 -4.94567273 -4.67967273
2 -4.34967273 -4.94567273
3 -3.99267273 -4.34967273
4 -3.52067273 -3.99267273
5 -3.48367273 -3.52067273
6 -3.31867273 -3.48367273
7 -3.57967273 -3.31867273
8 -2.86767273 -3.57967273
9 -1.40167273 -2.86767273
10 -0.41067273 -1.40167273
11 -0.59067273 -0.41067273
12 -1.13467273 -0.59067273
13 -1.66567273 -1.13467273
14 -1.56867273 -1.66567273
15 1.59532727 -1.56867273
16 1.59632727 1.59532727
17 0.69332727 1.59632727
18 0.67632727 0.69332727
19 -0.13367273 0.67632727
20 0.83232727 -0.13367273
21 2.54132727 0.83232727
22 3.55932727 2.54132727
23 2.11332727 3.55932727
24 1.52832727 2.11332727
25 1.12132727 1.52832727
26 0.59732727 1.12132727
27 0.94832727 0.59732727
28 0.73732727 0.94832727
29 0.78232727 0.73732727
30 1.39932727 0.78232727
31 2.16632727 1.39932727
32 2.77132727 2.16632727
33 4.01932727 2.77132727
34 4.46032727 4.01932727
35 1.89032727 4.46032727
36 0.43832727 1.89032727
37 0.43432727 0.43832727
38 -1.83667273 0.43432727
39 0.27432727 -1.83667273
40 -0.33867273 0.27432727
41 0.69632727 -0.33867273
42 0.35432727 0.69632727
43 0.78232727 0.35432727
44 0.92632727 0.78232727
45 2.59132727 0.92632727
46 1.90232727 2.59132727
47 -0.04567273 1.90232727
48 -0.64867273 -0.04567273
49 -0.13167273 -0.64867273
50 -0.87367273 -0.13167273
51 0.11032727 -0.87367273
52 -1.59767273 0.11032727
53 0.98332727 -1.59767273
54 1.59332727 0.98332727
55 -1.64516667 1.59332727
56 -1.02016667 -1.64516667
57 1.69583333 -1.02016667
58 1.15283333 1.69583333
59 -0.21916667 1.15283333
60 0.03583333 -0.21916667
61 NA 0.03583333
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -4.94567273 -4.67967273
[2,] -4.34967273 -4.94567273
[3,] -3.99267273 -4.34967273
[4,] -3.52067273 -3.99267273
[5,] -3.48367273 -3.52067273
[6,] -3.31867273 -3.48367273
[7,] -3.57967273 -3.31867273
[8,] -2.86767273 -3.57967273
[9,] -1.40167273 -2.86767273
[10,] -0.41067273 -1.40167273
[11,] -0.59067273 -0.41067273
[12,] -1.13467273 -0.59067273
[13,] -1.66567273 -1.13467273
[14,] -1.56867273 -1.66567273
[15,] 1.59532727 -1.56867273
[16,] 1.59632727 1.59532727
[17,] 0.69332727 1.59632727
[18,] 0.67632727 0.69332727
[19,] -0.13367273 0.67632727
[20,] 0.83232727 -0.13367273
[21,] 2.54132727 0.83232727
[22,] 3.55932727 2.54132727
[23,] 2.11332727 3.55932727
[24,] 1.52832727 2.11332727
[25,] 1.12132727 1.52832727
[26,] 0.59732727 1.12132727
[27,] 0.94832727 0.59732727
[28,] 0.73732727 0.94832727
[29,] 0.78232727 0.73732727
[30,] 1.39932727 0.78232727
[31,] 2.16632727 1.39932727
[32,] 2.77132727 2.16632727
[33,] 4.01932727 2.77132727
[34,] 4.46032727 4.01932727
[35,] 1.89032727 4.46032727
[36,] 0.43832727 1.89032727
[37,] 0.43432727 0.43832727
[38,] -1.83667273 0.43432727
[39,] 0.27432727 -1.83667273
[40,] -0.33867273 0.27432727
[41,] 0.69632727 -0.33867273
[42,] 0.35432727 0.69632727
[43,] 0.78232727 0.35432727
[44,] 0.92632727 0.78232727
[45,] 2.59132727 0.92632727
[46,] 1.90232727 2.59132727
[47,] -0.04567273 1.90232727
[48,] -0.64867273 -0.04567273
[49,] -0.13167273 -0.64867273
[50,] -0.87367273 -0.13167273
[51,] 0.11032727 -0.87367273
[52,] -1.59767273 0.11032727
[53,] 0.98332727 -1.59767273
[54,] 1.59332727 0.98332727
[55,] -1.64516667 1.59332727
[56,] -1.02016667 -1.64516667
[57,] 1.69583333 -1.02016667
[58,] 1.15283333 1.69583333
[59,] -0.21916667 1.15283333
[60,] 0.03583333 -0.21916667
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -4.94567273 -4.67967273
2 -4.34967273 -4.94567273
3 -3.99267273 -4.34967273
4 -3.52067273 -3.99267273
5 -3.48367273 -3.52067273
6 -3.31867273 -3.48367273
7 -3.57967273 -3.31867273
8 -2.86767273 -3.57967273
9 -1.40167273 -2.86767273
10 -0.41067273 -1.40167273
11 -0.59067273 -0.41067273
12 -1.13467273 -0.59067273
13 -1.66567273 -1.13467273
14 -1.56867273 -1.66567273
15 1.59532727 -1.56867273
16 1.59632727 1.59532727
17 0.69332727 1.59632727
18 0.67632727 0.69332727
19 -0.13367273 0.67632727
20 0.83232727 -0.13367273
21 2.54132727 0.83232727
22 3.55932727 2.54132727
23 2.11332727 3.55932727
24 1.52832727 2.11332727
25 1.12132727 1.52832727
26 0.59732727 1.12132727
27 0.94832727 0.59732727
28 0.73732727 0.94832727
29 0.78232727 0.73732727
30 1.39932727 0.78232727
31 2.16632727 1.39932727
32 2.77132727 2.16632727
33 4.01932727 2.77132727
34 4.46032727 4.01932727
35 1.89032727 4.46032727
36 0.43832727 1.89032727
37 0.43432727 0.43832727
38 -1.83667273 0.43432727
39 0.27432727 -1.83667273
40 -0.33867273 0.27432727
41 0.69632727 -0.33867273
42 0.35432727 0.69632727
43 0.78232727 0.35432727
44 0.92632727 0.78232727
45 2.59132727 0.92632727
46 1.90232727 2.59132727
47 -0.04567273 1.90232727
48 -0.64867273 -0.04567273
49 -0.13167273 -0.64867273
50 -0.87367273 -0.13167273
51 0.11032727 -0.87367273
52 -1.59767273 0.11032727
53 0.98332727 -1.59767273
54 1.59332727 0.98332727
55 -1.64516667 1.59332727
56 -1.02016667 -1.64516667
57 1.69583333 -1.02016667
58 1.15283333 1.69583333
59 -0.21916667 1.15283333
60 0.03583333 -0.21916667
> 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/73o1h1258735481.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8glph1258735481.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9czr01258735482.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10mt691258735482.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/116r9w1258735482.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/12rnhh1258735482.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/13tm7m1258735482.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/14wrqn1258735482.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/15qvvw1258735482.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/165to61258735482.tab")
+ }
>
> system("convert tmp/1m50l1258735481.ps tmp/1m50l1258735481.png")
> system("convert tmp/2y9zv1258735481.ps tmp/2y9zv1258735481.png")
> system("convert tmp/3ee5l1258735481.ps tmp/3ee5l1258735481.png")
> system("convert tmp/4bqcg1258735481.ps tmp/4bqcg1258735481.png")
> system("convert tmp/5sfo91258735481.ps tmp/5sfo91258735481.png")
> system("convert tmp/6x6y31258735481.ps tmp/6x6y31258735481.png")
> system("convert tmp/73o1h1258735481.ps tmp/73o1h1258735481.png")
> system("convert tmp/8glph1258735481.ps tmp/8glph1258735481.png")
> system("convert tmp/9czr01258735482.ps tmp/9czr01258735482.png")
> system("convert tmp/10mt691258735482.ps tmp/10mt691258735482.png")
>
>
> proc.time()
user system elapsed
2.534 1.573 5.966