R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(156.3,0,151.5,0,159.1,0,166.9,0,160.5,0,162.8,0,178.9,0,148.5,0,184.1,0,197,0,186.8,0,139.2,0,162.7,0,187.5,0,235.8,0,219.4,0,212.4,1,220.2,1,197.5,1,185.6,1,232.4,1,223.8,1,219.4,1,191.4,1,210.4,1,212.6,1,274.4,1,256,1,227.6,1,261.7,1,237,1,234.9,1,310.6,1,274.2,1,288.1,1,242.5,1,271.7,1,282.2,1,317.4,1,280.3,1,322.6,1,328.2,1,280.7,1,288.8,1,347.9,1,360.1,1,348,1,275.7,1,332.6,1,340.8,1,390.5,1,351.2,1,377.4,1,413.5,1,366.9,1,364.8,1,388,1,429.8,1,423.6,1,326.4,1),dim=c(2,60),dimnames=list(c('Poland','Dummy'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Poland','Dummy'),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 = '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
Poland Dummy M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 156.3 0 1 0 0 0 0 0 0 0 0 0 0
2 151.5 0 0 1 0 0 0 0 0 0 0 0 0
3 159.1 0 0 0 1 0 0 0 0 0 0 0 0
4 166.9 0 0 0 0 1 0 0 0 0 0 0 0
5 160.5 0 0 0 0 0 1 0 0 0 0 0 0
6 162.8 0 0 0 0 0 0 1 0 0 0 0 0
7 178.9 0 0 0 0 0 0 0 1 0 0 0 0
8 148.5 0 0 0 0 0 0 0 0 1 0 0 0
9 184.1 0 0 0 0 0 0 0 0 0 1 0 0
10 197.0 0 0 0 0 0 0 0 0 0 0 1 0
11 186.8 0 0 0 0 0 0 0 0 0 0 0 1
12 139.2 0 0 0 0 0 0 0 0 0 0 0 0
13 162.7 0 1 0 0 0 0 0 0 0 0 0 0
14 187.5 0 0 1 0 0 0 0 0 0 0 0 0
15 235.8 0 0 0 1 0 0 0 0 0 0 0 0
16 219.4 0 0 0 0 1 0 0 0 0 0 0 0
17 212.4 1 0 0 0 0 1 0 0 0 0 0 0
18 220.2 1 0 0 0 0 0 1 0 0 0 0 0
19 197.5 1 0 0 0 0 0 0 1 0 0 0 0
20 185.6 1 0 0 0 0 0 0 0 1 0 0 0
21 232.4 1 0 0 0 0 0 0 0 0 1 0 0
22 223.8 1 0 0 0 0 0 0 0 0 0 1 0
23 219.4 1 0 0 0 0 0 0 0 0 0 0 1
24 191.4 1 0 0 0 0 0 0 0 0 0 0 0
25 210.4 1 1 0 0 0 0 0 0 0 0 0 0
26 212.6 1 0 1 0 0 0 0 0 0 0 0 0
27 274.4 1 0 0 1 0 0 0 0 0 0 0 0
28 256.0 1 0 0 0 1 0 0 0 0 0 0 0
29 227.6 1 0 0 0 0 1 0 0 0 0 0 0
30 261.7 1 0 0 0 0 0 1 0 0 0 0 0
31 237.0 1 0 0 0 0 0 0 1 0 0 0 0
32 234.9 1 0 0 0 0 0 0 0 1 0 0 0
33 310.6 1 0 0 0 0 0 0 0 0 1 0 0
34 274.2 1 0 0 0 0 0 0 0 0 0 1 0
35 288.1 1 0 0 0 0 0 0 0 0 0 0 1
36 242.5 1 0 0 0 0 0 0 0 0 0 0 0
37 271.7 1 1 0 0 0 0 0 0 0 0 0 0
38 282.2 1 0 1 0 0 0 0 0 0 0 0 0
39 317.4 1 0 0 1 0 0 0 0 0 0 0 0
40 280.3 1 0 0 0 1 0 0 0 0 0 0 0
41 322.6 1 0 0 0 0 1 0 0 0 0 0 0
42 328.2 1 0 0 0 0 0 1 0 0 0 0 0
43 280.7 1 0 0 0 0 0 0 1 0 0 0 0
44 288.8 1 0 0 0 0 0 0 0 1 0 0 0
45 347.9 1 0 0 0 0 0 0 0 0 1 0 0
46 360.1 1 0 0 0 0 0 0 0 0 0 1 0
47 348.0 1 0 0 0 0 0 0 0 0 0 0 1
48 275.7 1 0 0 0 0 0 0 0 0 0 0 0
49 332.6 1 1 0 0 0 0 0 0 0 0 0 0
50 340.8 1 0 1 0 0 0 0 0 0 0 0 0
51 390.5 1 0 0 1 0 0 0 0 0 0 0 0
52 351.2 1 0 0 0 1 0 0 0 0 0 0 0
53 377.4 1 0 0 0 0 1 0 0 0 0 0 0
54 413.5 1 0 0 0 0 0 1 0 0 0 0 0
55 366.9 1 0 0 0 0 0 0 1 0 0 0 0
56 364.8 1 0 0 0 0 0 0 0 1 0 0 0
57 388.0 1 0 0 0 0 0 0 0 0 1 0 0
58 429.8 1 0 0 0 0 0 0 0 0 0 1 0
59 423.6 1 0 0 0 0 0 0 0 0 0 0 1
60 326.4 1 0 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummy M1 M2 M3 M4
139.42 119.52 15.60 23.78 64.30 43.62
M5 M6 M7 M8 M9 M10
25.06 42.24 17.16 9.48 57.56 61.94
M11
58.14
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-97.684 -40.770 -3.416 33.142 112.316
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 139.42 31.25 4.461 5.06e-05 ***
Dummy 119.52 18.42 6.490 4.86e-08 ***
M1 15.60 39.15 0.399 0.692
M2 23.78 39.15 0.607 0.546
M3 64.30 39.15 1.642 0.107
M4 43.62 39.15 1.114 0.271
M5 25.06 38.98 0.643 0.523
M6 42.24 38.98 1.084 0.284
M7 17.16 38.98 0.440 0.662
M8 9.48 38.98 0.243 0.809
M9 57.56 38.98 1.477 0.146
M10 61.94 38.98 1.589 0.119
M11 58.14 38.98 1.492 0.142
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 61.63 on 47 degrees of freedom
Multiple R-squared: 0.5202, Adjusted R-squared: 0.3977
F-statistic: 4.246 on 12 and 47 DF, p-value: 0.0001607
> 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,] 1.753958e-01 3.507917e-01 0.8246042
[2,] 7.922710e-02 1.584542e-01 0.9207729
[3,] 3.497805e-02 6.995610e-02 0.9650220
[4,] 1.771986e-02 3.543972e-02 0.9822801
[5,] 7.661904e-03 1.532381e-02 0.9923381
[6,] 3.419315e-03 6.838630e-03 0.9965807
[7,] 1.818469e-03 3.636938e-03 0.9981815
[8,] 1.025178e-03 2.050355e-03 0.9989748
[9,] 4.736851e-04 9.473701e-04 0.9995263
[10,] 2.155348e-04 4.310696e-04 0.9997845
[11,] 1.008590e-04 2.017181e-04 0.9998991
[12,] 8.341774e-05 1.668355e-04 0.9999166
[13,] 3.673259e-05 7.346518e-05 0.9999633
[14,] 3.389208e-05 6.778417e-05 0.9999661
[15,] 8.789126e-05 1.757825e-04 0.9999121
[16,] 7.465990e-05 1.493198e-04 0.9999253
[17,] 1.379036e-04 2.758071e-04 0.9998621
[18,] 6.685753e-04 1.337151e-03 0.9993314
[19,] 1.905884e-03 3.811767e-03 0.9980941
[20,] 6.156049e-03 1.231210e-02 0.9938440
[21,] 7.543037e-03 1.508607e-02 0.9924570
[22,] 9.930346e-03 1.986069e-02 0.9900697
[23,] 1.223813e-02 2.447625e-02 0.9877619
[24,] 1.610651e-02 3.221303e-02 0.9838935
[25,] 1.539358e-02 3.078716e-02 0.9846064
[26,] 3.588501e-02 7.177002e-02 0.9641150
[27,] 8.009852e-02 1.601970e-01 0.9199015
[28,] 1.202268e-01 2.404536e-01 0.8797732
[29,] 1.686560e-01 3.373119e-01 0.8313440
> postscript(file="/var/www/html/freestat/rcomp/tmp/1zn531228378080.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2mwri1228378080.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/freestat/rcomp/tmp/3ou6f1228378080.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4gzng1228378080.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5qcgg1228378080.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
1.2717857 -11.7082143 -44.6282143 -16.1482143 -3.9842857 -18.8642857
7 8 9 10 11 12
22.3157143 -0.4042857 -12.8842857 -4.3642857 -10.7642857 -0.2242857
13 14 15 16 17 18
7.6717857 24.2917857 32.0717857 36.3517857 -71.6039286 -80.9839286
19 20 21 22 23 24
-78.6039286 -82.8239286 -84.1039286 -97.0839286 -97.6839286 -67.5439286
25 26 27 28 29 30
-64.1478571 -70.1278571 -48.8478571 -46.5678571 -56.4039286 -39.4839286
31 32 33 34 35 36
-39.1039286 -33.5239286 -5.9039286 -46.6839286 -28.9839286 -16.4439286
37 38 39 40 41 42
-2.8478571 -0.5278571 -5.8478571 -22.2678571 38.5960714 27.0160714
43 44 45 46 47 48
4.5960714 20.3760714 31.3960714 39.2160714 30.9160714 16.7560714
49 50 51 52 53 54
58.0521429 58.0721429 67.2521429 48.6321429 93.3960714 112.3160714
55 56 57 58 59 60
90.7960714 96.3760714 71.4960714 108.9160714 106.5160714 67.4560714
> postscript(file="/var/www/html/freestat/rcomp/tmp/635d61228378080.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 1.2717857 NA
1 -11.7082143 1.2717857
2 -44.6282143 -11.7082143
3 -16.1482143 -44.6282143
4 -3.9842857 -16.1482143
5 -18.8642857 -3.9842857
6 22.3157143 -18.8642857
7 -0.4042857 22.3157143
8 -12.8842857 -0.4042857
9 -4.3642857 -12.8842857
10 -10.7642857 -4.3642857
11 -0.2242857 -10.7642857
12 7.6717857 -0.2242857
13 24.2917857 7.6717857
14 32.0717857 24.2917857
15 36.3517857 32.0717857
16 -71.6039286 36.3517857
17 -80.9839286 -71.6039286
18 -78.6039286 -80.9839286
19 -82.8239286 -78.6039286
20 -84.1039286 -82.8239286
21 -97.0839286 -84.1039286
22 -97.6839286 -97.0839286
23 -67.5439286 -97.6839286
24 -64.1478571 -67.5439286
25 -70.1278571 -64.1478571
26 -48.8478571 -70.1278571
27 -46.5678571 -48.8478571
28 -56.4039286 -46.5678571
29 -39.4839286 -56.4039286
30 -39.1039286 -39.4839286
31 -33.5239286 -39.1039286
32 -5.9039286 -33.5239286
33 -46.6839286 -5.9039286
34 -28.9839286 -46.6839286
35 -16.4439286 -28.9839286
36 -2.8478571 -16.4439286
37 -0.5278571 -2.8478571
38 -5.8478571 -0.5278571
39 -22.2678571 -5.8478571
40 38.5960714 -22.2678571
41 27.0160714 38.5960714
42 4.5960714 27.0160714
43 20.3760714 4.5960714
44 31.3960714 20.3760714
45 39.2160714 31.3960714
46 30.9160714 39.2160714
47 16.7560714 30.9160714
48 58.0521429 16.7560714
49 58.0721429 58.0521429
50 67.2521429 58.0721429
51 48.6321429 67.2521429
52 93.3960714 48.6321429
53 112.3160714 93.3960714
54 90.7960714 112.3160714
55 96.3760714 90.7960714
56 71.4960714 96.3760714
57 108.9160714 71.4960714
58 106.5160714 108.9160714
59 67.4560714 106.5160714
60 NA 67.4560714
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -11.7082143 1.2717857
[2,] -44.6282143 -11.7082143
[3,] -16.1482143 -44.6282143
[4,] -3.9842857 -16.1482143
[5,] -18.8642857 -3.9842857
[6,] 22.3157143 -18.8642857
[7,] -0.4042857 22.3157143
[8,] -12.8842857 -0.4042857
[9,] -4.3642857 -12.8842857
[10,] -10.7642857 -4.3642857
[11,] -0.2242857 -10.7642857
[12,] 7.6717857 -0.2242857
[13,] 24.2917857 7.6717857
[14,] 32.0717857 24.2917857
[15,] 36.3517857 32.0717857
[16,] -71.6039286 36.3517857
[17,] -80.9839286 -71.6039286
[18,] -78.6039286 -80.9839286
[19,] -82.8239286 -78.6039286
[20,] -84.1039286 -82.8239286
[21,] -97.0839286 -84.1039286
[22,] -97.6839286 -97.0839286
[23,] -67.5439286 -97.6839286
[24,] -64.1478571 -67.5439286
[25,] -70.1278571 -64.1478571
[26,] -48.8478571 -70.1278571
[27,] -46.5678571 -48.8478571
[28,] -56.4039286 -46.5678571
[29,] -39.4839286 -56.4039286
[30,] -39.1039286 -39.4839286
[31,] -33.5239286 -39.1039286
[32,] -5.9039286 -33.5239286
[33,] -46.6839286 -5.9039286
[34,] -28.9839286 -46.6839286
[35,] -16.4439286 -28.9839286
[36,] -2.8478571 -16.4439286
[37,] -0.5278571 -2.8478571
[38,] -5.8478571 -0.5278571
[39,] -22.2678571 -5.8478571
[40,] 38.5960714 -22.2678571
[41,] 27.0160714 38.5960714
[42,] 4.5960714 27.0160714
[43,] 20.3760714 4.5960714
[44,] 31.3960714 20.3760714
[45,] 39.2160714 31.3960714
[46,] 30.9160714 39.2160714
[47,] 16.7560714 30.9160714
[48,] 58.0521429 16.7560714
[49,] 58.0721429 58.0521429
[50,] 67.2521429 58.0721429
[51,] 48.6321429 67.2521429
[52,] 93.3960714 48.6321429
[53,] 112.3160714 93.3960714
[54,] 90.7960714 112.3160714
[55,] 96.3760714 90.7960714
[56,] 71.4960714 96.3760714
[57,] 108.9160714 71.4960714
[58,] 106.5160714 108.9160714
[59,] 67.4560714 106.5160714
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -11.7082143 1.2717857
2 -44.6282143 -11.7082143
3 -16.1482143 -44.6282143
4 -3.9842857 -16.1482143
5 -18.8642857 -3.9842857
6 22.3157143 -18.8642857
7 -0.4042857 22.3157143
8 -12.8842857 -0.4042857
9 -4.3642857 -12.8842857
10 -10.7642857 -4.3642857
11 -0.2242857 -10.7642857
12 7.6717857 -0.2242857
13 24.2917857 7.6717857
14 32.0717857 24.2917857
15 36.3517857 32.0717857
16 -71.6039286 36.3517857
17 -80.9839286 -71.6039286
18 -78.6039286 -80.9839286
19 -82.8239286 -78.6039286
20 -84.1039286 -82.8239286
21 -97.0839286 -84.1039286
22 -97.6839286 -97.0839286
23 -67.5439286 -97.6839286
24 -64.1478571 -67.5439286
25 -70.1278571 -64.1478571
26 -48.8478571 -70.1278571
27 -46.5678571 -48.8478571
28 -56.4039286 -46.5678571
29 -39.4839286 -56.4039286
30 -39.1039286 -39.4839286
31 -33.5239286 -39.1039286
32 -5.9039286 -33.5239286
33 -46.6839286 -5.9039286
34 -28.9839286 -46.6839286
35 -16.4439286 -28.9839286
36 -2.8478571 -16.4439286
37 -0.5278571 -2.8478571
38 -5.8478571 -0.5278571
39 -22.2678571 -5.8478571
40 38.5960714 -22.2678571
41 27.0160714 38.5960714
42 4.5960714 27.0160714
43 20.3760714 4.5960714
44 31.3960714 20.3760714
45 39.2160714 31.3960714
46 30.9160714 39.2160714
47 16.7560714 30.9160714
48 58.0521429 16.7560714
49 58.0721429 58.0521429
50 67.2521429 58.0721429
51 48.6321429 67.2521429
52 93.3960714 48.6321429
53 112.3160714 93.3960714
54 90.7960714 112.3160714
55 96.3760714 90.7960714
56 71.4960714 96.3760714
57 108.9160714 71.4960714
58 106.5160714 108.9160714
59 67.4560714 106.5160714
> 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/freestat/rcomp/tmp/7owx01228378080.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8xqxf1228378080.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/962oj1228378080.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/1045za1228378080.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/11hd771228378080.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/freestat/rcomp/tmp/12hro51228378080.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/freestat/rcomp/tmp/138u9e1228378080.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/freestat/rcomp/tmp/1408kz1228378080.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/freestat/rcomp/tmp/1599lp1228378080.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/freestat/rcomp/tmp/16i9e11228378080.tab")
+ }
>
> system("convert tmp/1zn531228378080.ps tmp/1zn531228378080.png")
> system("convert tmp/2mwri1228378080.ps tmp/2mwri1228378080.png")
> system("convert tmp/3ou6f1228378080.ps tmp/3ou6f1228378080.png")
> system("convert tmp/4gzng1228378080.ps tmp/4gzng1228378080.png")
> system("convert tmp/5qcgg1228378080.ps tmp/5qcgg1228378080.png")
> system("convert tmp/635d61228378080.ps tmp/635d61228378080.png")
> system("convert tmp/7owx01228378080.ps tmp/7owx01228378080.png")
> system("convert tmp/8xqxf1228378080.ps tmp/8xqxf1228378080.png")
> system("convert tmp/962oj1228378080.ps tmp/962oj1228378080.png")
> system("convert tmp/1045za1228378080.ps tmp/1045za1228378080.png")
>
>
> proc.time()
user system elapsed
3.642 2.488 4.096