R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(613,0,611,0,594,0,595,0,591,0,589,0,584,0,573,0,567,0,569,0,621,0,629,0,628,0,612,0,595,0,597,0,593,0,590,0,580,0,574,0,573,0,573,0,620,0,626,0,620,0,588,0,566,0,557,0,561,0,549,0,532,0,526,0,511,0,499,0,555,0,565,0,542,0,527,0,510,0,514,0,517,0,508,0,493,0,490,0,469,0,478,0,528,0,534,0,518,1,506,1,502,1,516,1,528,1,533,1,536,1,537,1,524,1,536,1,587,1,597,1,581,1),dim=c(2,61),dimnames=list(c('WklBe','X'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('WklBe','X'),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 = '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
WklBe X M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 613 0 1 0 0 0 0 0 0 0 0 0 0 1
2 611 0 0 1 0 0 0 0 0 0 0 0 0 2
3 594 0 0 0 1 0 0 0 0 0 0 0 0 3
4 595 0 0 0 0 1 0 0 0 0 0 0 0 4
5 591 0 0 0 0 0 1 0 0 0 0 0 0 5
6 589 0 0 0 0 0 0 1 0 0 0 0 0 6
7 584 0 0 0 0 0 0 0 1 0 0 0 0 7
8 573 0 0 0 0 0 0 0 0 1 0 0 0 8
9 567 0 0 0 0 0 0 0 0 0 1 0 0 9
10 569 0 0 0 0 0 0 0 0 0 0 1 0 10
11 621 0 0 0 0 0 0 0 0 0 0 0 1 11
12 629 0 0 0 0 0 0 0 0 0 0 0 0 12
13 628 0 1 0 0 0 0 0 0 0 0 0 0 13
14 612 0 0 1 0 0 0 0 0 0 0 0 0 14
15 595 0 0 0 1 0 0 0 0 0 0 0 0 15
16 597 0 0 0 0 1 0 0 0 0 0 0 0 16
17 593 0 0 0 0 0 1 0 0 0 0 0 0 17
18 590 0 0 0 0 0 0 1 0 0 0 0 0 18
19 580 0 0 0 0 0 0 0 1 0 0 0 0 19
20 574 0 0 0 0 0 0 0 0 1 0 0 0 20
21 573 0 0 0 0 0 0 0 0 0 1 0 0 21
22 573 0 0 0 0 0 0 0 0 0 0 1 0 22
23 620 0 0 0 0 0 0 0 0 0 0 0 1 23
24 626 0 0 0 0 0 0 0 0 0 0 0 0 24
25 620 0 1 0 0 0 0 0 0 0 0 0 0 25
26 588 0 0 1 0 0 0 0 0 0 0 0 0 26
27 566 0 0 0 1 0 0 0 0 0 0 0 0 27
28 557 0 0 0 0 1 0 0 0 0 0 0 0 28
29 561 0 0 0 0 0 1 0 0 0 0 0 0 29
30 549 0 0 0 0 0 0 1 0 0 0 0 0 30
31 532 0 0 0 0 0 0 0 1 0 0 0 0 31
32 526 0 0 0 0 0 0 0 0 1 0 0 0 32
33 511 0 0 0 0 0 0 0 0 0 1 0 0 33
34 499 0 0 0 0 0 0 0 0 0 0 1 0 34
35 555 0 0 0 0 0 0 0 0 0 0 0 1 35
36 565 0 0 0 0 0 0 0 0 0 0 0 0 36
37 542 0 1 0 0 0 0 0 0 0 0 0 0 37
38 527 0 0 1 0 0 0 0 0 0 0 0 0 38
39 510 0 0 0 1 0 0 0 0 0 0 0 0 39
40 514 0 0 0 0 1 0 0 0 0 0 0 0 40
41 517 0 0 0 0 0 1 0 0 0 0 0 0 41
42 508 0 0 0 0 0 0 1 0 0 0 0 0 42
43 493 0 0 0 0 0 0 0 1 0 0 0 0 43
44 490 0 0 0 0 0 0 0 0 1 0 0 0 44
45 469 0 0 0 0 0 0 0 0 0 1 0 0 45
46 478 0 0 0 0 0 0 0 0 0 0 1 0 46
47 528 0 0 0 0 0 0 0 0 0 0 0 1 47
48 534 0 0 0 0 0 0 0 0 0 0 0 0 48
49 518 1 1 0 0 0 0 0 0 0 0 0 0 49
50 506 1 0 1 0 0 0 0 0 0 0 0 0 50
51 502 1 0 0 1 0 0 0 0 0 0 0 0 51
52 516 1 0 0 0 1 0 0 0 0 0 0 0 52
53 528 1 0 0 0 0 1 0 0 0 0 0 0 53
54 533 1 0 0 0 0 0 1 0 0 0 0 0 54
55 536 1 0 0 0 0 0 0 1 0 0 0 0 55
56 537 1 0 0 0 0 0 0 0 1 0 0 0 56
57 524 1 0 0 0 0 0 0 0 0 1 0 0 57
58 536 1 0 0 0 0 0 0 0 0 0 1 0 58
59 587 1 0 0 0 0 0 0 0 0 0 0 1 59
60 597 1 0 0 0 0 0 0 0 0 0 0 0 60
61 581 1 1 0 0 0 0 0 0 0 0 0 0 61
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
668.809 48.565 -25.276 -45.934 -58.881 -54.027
M5 M6 M7 M8 M9 M10
-49.374 -51.120 -57.467 -60.014 -68.760 -64.107
M11 t
-10.453 -2.453
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-53.882 -12.846 -4.246 16.361 38.558
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 668.8091 12.1744 54.936 < 2e-16 ***
X 48.5649 10.0179 4.848 1.40e-05 ***
M1 -25.2756 13.5362 -1.867 0.068109 .
M2 -45.9339 14.1240 -3.252 0.002123 **
M3 -58.8805 14.0867 -4.180 0.000126 ***
M4 -54.0271 14.0532 -3.844 0.000362 ***
M5 -49.3737 14.0237 -3.521 0.000968 ***
M6 -51.1203 13.9980 -3.652 0.000653 ***
M7 -57.4670 13.9762 -4.112 0.000156 ***
M8 -60.0136 13.9583 -4.299 8.57e-05 ***
M9 -68.7602 13.9444 -4.931 1.06e-05 ***
M10 -64.1068 13.9345 -4.601 3.20e-05 ***
M11 -10.4534 13.9285 -0.751 0.456694
t -2.4534 0.2354 -10.424 8.23e-14 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 22.02 on 47 degrees of freedom
Multiple R-squared: 0.7852, Adjusted R-squared: 0.7258
F-statistic: 13.22 on 13 and 47 DF, p-value: 1.379e-11
> 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,] 1.370692e-02 2.741383e-02 0.986293083
[2,] 2.614185e-03 5.228370e-03 0.997385815
[3,] 8.104167e-04 1.620833e-03 0.999189583
[4,] 1.361078e-04 2.722156e-04 0.999863892
[5,] 2.524445e-05 5.048889e-05 0.999974756
[6,] 3.778763e-06 7.557525e-06 0.999996221
[7,] 6.650126e-07 1.330025e-06 0.999999335
[8,] 1.496297e-07 2.992594e-07 0.999999850
[9,] 4.334714e-08 8.669427e-08 0.999999957
[10,] 2.307586e-05 4.615173e-05 0.999976924
[11,] 3.451638e-04 6.903275e-04 0.999654836
[12,] 3.281708e-03 6.563417e-03 0.996718292
[13,] 5.070320e-03 1.014064e-02 0.994929680
[14,] 1.073713e-02 2.147427e-02 0.989262866
[15,] 2.473579e-02 4.947157e-02 0.975264213
[16,] 3.244326e-02 6.488653e-02 0.967556737
[17,] 6.358571e-02 1.271714e-01 0.936414294
[18,] 1.138166e-01 2.276332e-01 0.886183414
[19,] 1.344188e-01 2.688377e-01 0.865581155
[20,] 1.805569e-01 3.611138e-01 0.819443120
[21,] 3.209856e-01 6.419713e-01 0.679014353
[22,] 5.372507e-01 9.254986e-01 0.462749276
[23,] 7.194491e-01 5.611019e-01 0.280550926
[24,] 8.596762e-01 2.806477e-01 0.140323845
[25,] 9.609943e-01 7.801145e-02 0.039005727
[26,] 9.943784e-01 1.124330e-02 0.005621649
[27,] 9.947806e-01 1.043887e-02 0.005219436
[28,] 9.971651e-01 5.669875e-03 0.002834938
> postscript(file="/var/www/html/rcomp/tmp/10ljo1258726535.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2ex9c1258726535.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/38jhg1258726535.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4scxz1258726535.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5cqn51258726535.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
-28.0800866 -6.9683983 -8.5683983 -9.9683983 -16.1683983 -13.9683983
7 8 9 10 11 12
-10.1683983 -16.1683983 -10.9683983 -11.1683983 -10.3683983 -10.3683983
13 14 15 16 17 18
16.3606061 23.4722944 21.8722944 21.4722944 15.2722944 16.4722944
19 20 21 22 23 24
15.2722944 14.2722944 24.4722944 22.2722944 18.0722944 16.0722944
25 26 27 28 29 30
37.8012987 28.9129870 22.3129870 10.9129870 12.7129870 4.9129870
31 32 33 34 35 36
-3.2870130 -4.2870130 -8.0870130 -22.2870130 -17.4870130 -15.4870130
37 38 39 40 41 42
-10.7580087 -2.6463203 -4.2463203 -2.6463203 -1.8463203 -6.6463203
43 44 45 46 47 48
-12.8463203 -10.8463203 -20.6463203 -13.8463203 -15.0463203 -17.0463203
49 50 51 52 53 54
-53.8822511 -42.7705628 -31.3705628 -19.7705628 -9.9705628 -0.7705628
55 56 57 58 59 60
11.0294372 17.0294372 15.2294372 25.0294372 24.8294372 26.8294372
61
38.5584416
> postscript(file="/var/www/html/rcomp/tmp/6whla1258726535.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 -28.0800866 NA
1 -6.9683983 -28.0800866
2 -8.5683983 -6.9683983
3 -9.9683983 -8.5683983
4 -16.1683983 -9.9683983
5 -13.9683983 -16.1683983
6 -10.1683983 -13.9683983
7 -16.1683983 -10.1683983
8 -10.9683983 -16.1683983
9 -11.1683983 -10.9683983
10 -10.3683983 -11.1683983
11 -10.3683983 -10.3683983
12 16.3606061 -10.3683983
13 23.4722944 16.3606061
14 21.8722944 23.4722944
15 21.4722944 21.8722944
16 15.2722944 21.4722944
17 16.4722944 15.2722944
18 15.2722944 16.4722944
19 14.2722944 15.2722944
20 24.4722944 14.2722944
21 22.2722944 24.4722944
22 18.0722944 22.2722944
23 16.0722944 18.0722944
24 37.8012987 16.0722944
25 28.9129870 37.8012987
26 22.3129870 28.9129870
27 10.9129870 22.3129870
28 12.7129870 10.9129870
29 4.9129870 12.7129870
30 -3.2870130 4.9129870
31 -4.2870130 -3.2870130
32 -8.0870130 -4.2870130
33 -22.2870130 -8.0870130
34 -17.4870130 -22.2870130
35 -15.4870130 -17.4870130
36 -10.7580087 -15.4870130
37 -2.6463203 -10.7580087
38 -4.2463203 -2.6463203
39 -2.6463203 -4.2463203
40 -1.8463203 -2.6463203
41 -6.6463203 -1.8463203
42 -12.8463203 -6.6463203
43 -10.8463203 -12.8463203
44 -20.6463203 -10.8463203
45 -13.8463203 -20.6463203
46 -15.0463203 -13.8463203
47 -17.0463203 -15.0463203
48 -53.8822511 -17.0463203
49 -42.7705628 -53.8822511
50 -31.3705628 -42.7705628
51 -19.7705628 -31.3705628
52 -9.9705628 -19.7705628
53 -0.7705628 -9.9705628
54 11.0294372 -0.7705628
55 17.0294372 11.0294372
56 15.2294372 17.0294372
57 25.0294372 15.2294372
58 24.8294372 25.0294372
59 26.8294372 24.8294372
60 38.5584416 26.8294372
61 NA 38.5584416
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -6.9683983 -28.0800866
[2,] -8.5683983 -6.9683983
[3,] -9.9683983 -8.5683983
[4,] -16.1683983 -9.9683983
[5,] -13.9683983 -16.1683983
[6,] -10.1683983 -13.9683983
[7,] -16.1683983 -10.1683983
[8,] -10.9683983 -16.1683983
[9,] -11.1683983 -10.9683983
[10,] -10.3683983 -11.1683983
[11,] -10.3683983 -10.3683983
[12,] 16.3606061 -10.3683983
[13,] 23.4722944 16.3606061
[14,] 21.8722944 23.4722944
[15,] 21.4722944 21.8722944
[16,] 15.2722944 21.4722944
[17,] 16.4722944 15.2722944
[18,] 15.2722944 16.4722944
[19,] 14.2722944 15.2722944
[20,] 24.4722944 14.2722944
[21,] 22.2722944 24.4722944
[22,] 18.0722944 22.2722944
[23,] 16.0722944 18.0722944
[24,] 37.8012987 16.0722944
[25,] 28.9129870 37.8012987
[26,] 22.3129870 28.9129870
[27,] 10.9129870 22.3129870
[28,] 12.7129870 10.9129870
[29,] 4.9129870 12.7129870
[30,] -3.2870130 4.9129870
[31,] -4.2870130 -3.2870130
[32,] -8.0870130 -4.2870130
[33,] -22.2870130 -8.0870130
[34,] -17.4870130 -22.2870130
[35,] -15.4870130 -17.4870130
[36,] -10.7580087 -15.4870130
[37,] -2.6463203 -10.7580087
[38,] -4.2463203 -2.6463203
[39,] -2.6463203 -4.2463203
[40,] -1.8463203 -2.6463203
[41,] -6.6463203 -1.8463203
[42,] -12.8463203 -6.6463203
[43,] -10.8463203 -12.8463203
[44,] -20.6463203 -10.8463203
[45,] -13.8463203 -20.6463203
[46,] -15.0463203 -13.8463203
[47,] -17.0463203 -15.0463203
[48,] -53.8822511 -17.0463203
[49,] -42.7705628 -53.8822511
[50,] -31.3705628 -42.7705628
[51,] -19.7705628 -31.3705628
[52,] -9.9705628 -19.7705628
[53,] -0.7705628 -9.9705628
[54,] 11.0294372 -0.7705628
[55,] 17.0294372 11.0294372
[56,] 15.2294372 17.0294372
[57,] 25.0294372 15.2294372
[58,] 24.8294372 25.0294372
[59,] 26.8294372 24.8294372
[60,] 38.5584416 26.8294372
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -6.9683983 -28.0800866
2 -8.5683983 -6.9683983
3 -9.9683983 -8.5683983
4 -16.1683983 -9.9683983
5 -13.9683983 -16.1683983
6 -10.1683983 -13.9683983
7 -16.1683983 -10.1683983
8 -10.9683983 -16.1683983
9 -11.1683983 -10.9683983
10 -10.3683983 -11.1683983
11 -10.3683983 -10.3683983
12 16.3606061 -10.3683983
13 23.4722944 16.3606061
14 21.8722944 23.4722944
15 21.4722944 21.8722944
16 15.2722944 21.4722944
17 16.4722944 15.2722944
18 15.2722944 16.4722944
19 14.2722944 15.2722944
20 24.4722944 14.2722944
21 22.2722944 24.4722944
22 18.0722944 22.2722944
23 16.0722944 18.0722944
24 37.8012987 16.0722944
25 28.9129870 37.8012987
26 22.3129870 28.9129870
27 10.9129870 22.3129870
28 12.7129870 10.9129870
29 4.9129870 12.7129870
30 -3.2870130 4.9129870
31 -4.2870130 -3.2870130
32 -8.0870130 -4.2870130
33 -22.2870130 -8.0870130
34 -17.4870130 -22.2870130
35 -15.4870130 -17.4870130
36 -10.7580087 -15.4870130
37 -2.6463203 -10.7580087
38 -4.2463203 -2.6463203
39 -2.6463203 -4.2463203
40 -1.8463203 -2.6463203
41 -6.6463203 -1.8463203
42 -12.8463203 -6.6463203
43 -10.8463203 -12.8463203
44 -20.6463203 -10.8463203
45 -13.8463203 -20.6463203
46 -15.0463203 -13.8463203
47 -17.0463203 -15.0463203
48 -53.8822511 -17.0463203
49 -42.7705628 -53.8822511
50 -31.3705628 -42.7705628
51 -19.7705628 -31.3705628
52 -9.9705628 -19.7705628
53 -0.7705628 -9.9705628
54 11.0294372 -0.7705628
55 17.0294372 11.0294372
56 15.2294372 17.0294372
57 25.0294372 15.2294372
58 24.8294372 25.0294372
59 26.8294372 24.8294372
60 38.5584416 26.8294372
> 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/7yr2a1258726535.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8t0n51258726535.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9vyko1258726535.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10lkeb1258726535.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11bdqj1258726535.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/12axb81258726535.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/13bfj71258726535.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/148jgp1258726535.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/15h0u41258726536.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/16fdir1258726536.tab")
+ }
>
> system("convert tmp/10ljo1258726535.ps tmp/10ljo1258726535.png")
> system("convert tmp/2ex9c1258726535.ps tmp/2ex9c1258726535.png")
> system("convert tmp/38jhg1258726535.ps tmp/38jhg1258726535.png")
> system("convert tmp/4scxz1258726535.ps tmp/4scxz1258726535.png")
> system("convert tmp/5cqn51258726535.ps tmp/5cqn51258726535.png")
> system("convert tmp/6whla1258726535.ps tmp/6whla1258726535.png")
> system("convert tmp/7yr2a1258726535.ps tmp/7yr2a1258726535.png")
> system("convert tmp/8t0n51258726535.ps tmp/8t0n51258726535.png")
> system("convert tmp/9vyko1258726535.ps tmp/9vyko1258726535.png")
> system("convert tmp/10lkeb1258726535.ps tmp/10lkeb1258726535.png")
>
>
> proc.time()
user system elapsed
2.399 1.561 4.572