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.
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Type 'contributors()' for more information and
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Type 'demo()' for some demos, 'help()' for on-line help, or
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Type 'q()' to quit R.
> x <- array(list(296.95,17.20,296.84,17.20,287.54,17.20,287.81,17.20,283.99,20.63,275.79,20.63,269.52,20.63,278.35,20.63,283.43,19.32,289.46,19.32,282.30,19.32,293.55,19.32,304.78,12.99,300.99,12.99,315.29,12.99,316.21,12.99,331.79,18.13,329.38,18.13,317.27,18.13,317.98,18.13,340.28,28.37,339.21,28.37,336.71,28.37,340.11,28.37,347.72,24.35,328.68,24.35,303.05,24.35,299.83,24.35,320.04,24.99,317.94,24.99,303.31,24.99,308.85,24.99,319.19,28.84,314.52,28.84,312.39,28.84,315.77,28.84,320.23,37.88,309.45,37.88,296.54,37.88,297.28,37.88,301.39,54.04,306.68,54.04,305.91,54.04,314.76,54.04,323.34,64.93,341.58,64.93,330.12,64.93,318.16,64.93,317.84,71.81,325.39,71.81,327.56,71.81,329.77,71.81,333.29,99.75,346.10,99.75,358.00,99.75,344.82,99.75,313.30,61.25,301.26,61.25,306.38,61.25,319.31,61.25),dim=c(2,60),dimnames=list(c('Gemiddelde_prijs_vliegticket_in$','Gemiddelde_olieprijs_in$'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Gemiddelde_prijs_vliegticket_in$','Gemiddelde_olieprijs_in$'),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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Gemiddelde_prijs_vliegticket_in$ Gemiddelde_olieprijs_in$
1 296.95 17.20
2 296.84 17.20
3 287.54 17.20
4 287.81 17.20
5 283.99 20.63
6 275.79 20.63
7 269.52 20.63
8 278.35 20.63
9 283.43 19.32
10 289.46 19.32
11 282.30 19.32
12 293.55 19.32
13 304.78 12.99
14 300.99 12.99
15 315.29 12.99
16 316.21 12.99
17 331.79 18.13
18 329.38 18.13
19 317.27 18.13
20 317.98 18.13
21 340.28 28.37
22 339.21 28.37
23 336.71 28.37
24 340.11 28.37
25 347.72 24.35
26 328.68 24.35
27 303.05 24.35
28 299.83 24.35
29 320.04 24.99
30 317.94 24.99
31 303.31 24.99
32 308.85 24.99
33 319.19 28.84
34 314.52 28.84
35 312.39 28.84
36 315.77 28.84
37 320.23 37.88
38 309.45 37.88
39 296.54 37.88
40 297.28 37.88
41 301.39 54.04
42 306.68 54.04
43 305.91 54.04
44 314.76 54.04
45 323.34 64.93
46 341.58 64.93
47 330.12 64.93
48 318.16 64.93
49 317.84 71.81
50 325.39 71.81
51 327.56 71.81
52 329.77 71.81
53 333.29 99.75
54 346.10 99.75
55 358.00 99.75
56 344.82 99.75
57 313.30 61.25
58 301.26 61.25
59 306.38 61.25
60 319.31 61.25
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `Gemiddelde_olieprijs_in$`
297.3331 0.4086
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-36.243 -12.927 -1.468 10.921 40.437
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 297.33307 4.11862 72.192 < 2e-16 ***
`Gemiddelde_olieprijs_in$` 0.40861 0.08934 4.573 2.57e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 17.05 on 58 degrees of freedom
Multiple R-squared: 0.265, Adjusted R-squared: 0.2524
F-statistic: 20.92 on 1 and 58 DF, p-value: 2.571e-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,] 0.0384401133 0.0768802266 9.615599e-01
[2,] 0.0202692489 0.0405384978 9.797308e-01
[3,] 0.0211184470 0.0422368940 9.788816e-01
[4,] 0.0091061523 0.0182123045 9.908938e-01
[5,] 0.0036418727 0.0072837455 9.963581e-01
[6,] 0.0025832205 0.0051664411 9.974168e-01
[7,] 0.0012622968 0.0025245936 9.987377e-01
[8,] 0.0021389622 0.0042779244 9.978610e-01
[9,] 0.0010348558 0.0020697116 9.989651e-01
[10,] 0.0005857694 0.0011715387 9.994142e-01
[11,] 0.0005967824 0.0011935649 9.994032e-01
[12,] 0.0004421807 0.0008843614 9.995578e-01
[13,] 0.2371157689 0.4742315377 7.628842e-01
[14,] 0.5842957330 0.8314085340 4.157043e-01
[15,] 0.6315952363 0.7368095273 3.684048e-01
[16,] 0.6626712321 0.6746575358 3.373288e-01
[17,] 0.9663443702 0.0673112596 3.365563e-02
[18,] 0.9864600605 0.0270798791 1.353994e-02
[19,] 0.9912167299 0.0175665402 8.783270e-03
[20,] 0.9959336073 0.0081327855 4.066393e-03
[21,] 0.9998083094 0.0003833812 1.916906e-04
[22,] 0.9999061230 0.0001877541 9.387705e-05
[23,] 0.9998322671 0.0003354657 1.677329e-04
[24,] 0.9997373270 0.0005253460 2.626730e-04
[25,] 0.9997039586 0.0005920828 2.960414e-04
[26,] 0.9996541010 0.0006917979 3.458990e-04
[27,] 0.9993832130 0.0012335740 6.167870e-04
[28,] 0.9989403796 0.0021192408 1.059620e-03
[29,] 0.9989740534 0.0020518931 1.025947e-03
[30,] 0.9988176082 0.0023647836 1.182392e-03
[31,] 0.9986476829 0.0027046343 1.352317e-03
[32,] 0.9991695069 0.0016609861 8.304931e-04
[33,] 0.9996922774 0.0006154452 3.077226e-04
[34,] 0.9997160141 0.0005679718 2.839859e-04
[35,] 0.9995904617 0.0008190766 4.095383e-04
[36,] 0.9993046156 0.0013907689 6.953844e-04
[37,] 0.9991713142 0.0016573717 8.286858e-04
[38,] 0.9984255360 0.0031489281 1.574464e-03
[39,] 0.9971854784 0.0056290433 2.814522e-03
[40,] 0.9942725069 0.0114549862 5.727493e-03
[41,] 0.9890323125 0.0219353749 1.096769e-02
[42,] 0.9979045613 0.0041908774 2.095439e-03
[43,] 0.9983355255 0.0033289491 1.664475e-03
[44,] 0.9959838635 0.0080322729 4.016136e-03
[45,] 0.9913989274 0.0172021452 8.601073e-03
[46,] 0.9813393516 0.0373212968 1.866065e-02
[47,] 0.9656476934 0.0687046132 3.435231e-02
[48,] 0.9506058197 0.0987883607 4.939418e-02
[49,] 0.9640860229 0.0718279542 3.591398e-02
[50,] 0.9213791655 0.1572416690 7.862083e-02
[51,] 0.8911094361 0.2177811278 1.088906e-01
> postscript(file="/var/www/html/rcomp/tmp/1qpiz1292001339.ps",horizontal=F,onefile=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/2qpiz1292001339.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/31zij1292001339.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/41zij1292001339.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/51zij1292001339.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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
-7.4111494 -7.5211494 -16.8211494 -16.5511494 -21.7726793 -29.9726793
7 8 9 10 11 12
-36.2426793 -27.4126793 -21.7974011 -15.7674011 -22.9274011 -11.6774011
13 14 15 16 17 18
2.1390956 -1.6509044 12.6490956 13.5690956 27.0488439 24.6388439
19 20 21 22 23 24
12.5288439 13.2388439 31.3546849 30.2846849 27.7846849 31.1846849
25 26 27 28 29 30
40.4372942 21.3972942 -4.2327058 -7.4527058 12.4957842 10.3957842
31 32 33 34 35 36
-4.2342158 1.3057842 10.0726385 5.4026385 3.2726385 6.6526385
37 38 39 40 41 42
7.4188106 -3.3611894 -16.2711894 -15.5311894 -18.0243154 -12.7343154
43 44 45 46 47 48
-13.5043154 -4.6543154 -0.5240705 17.7159295 6.2559295 -5.7040705
49 50 51 52 53 54
-8.8353023 -1.2853023 0.8846977 3.0946977 -4.8018457 8.0081543
55 56 57 58 59 60
19.9081543 6.7281543 -9.0603883 -21.1003883 -15.9803883 -3.0503883
> postscript(file="/var/www/html/rcomp/tmp/6cqzn1292001339.ps",horizontal=F,onefile=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 -7.4111494 NA
1 -7.5211494 -7.4111494
2 -16.8211494 -7.5211494
3 -16.5511494 -16.8211494
4 -21.7726793 -16.5511494
5 -29.9726793 -21.7726793
6 -36.2426793 -29.9726793
7 -27.4126793 -36.2426793
8 -21.7974011 -27.4126793
9 -15.7674011 -21.7974011
10 -22.9274011 -15.7674011
11 -11.6774011 -22.9274011
12 2.1390956 -11.6774011
13 -1.6509044 2.1390956
14 12.6490956 -1.6509044
15 13.5690956 12.6490956
16 27.0488439 13.5690956
17 24.6388439 27.0488439
18 12.5288439 24.6388439
19 13.2388439 12.5288439
20 31.3546849 13.2388439
21 30.2846849 31.3546849
22 27.7846849 30.2846849
23 31.1846849 27.7846849
24 40.4372942 31.1846849
25 21.3972942 40.4372942
26 -4.2327058 21.3972942
27 -7.4527058 -4.2327058
28 12.4957842 -7.4527058
29 10.3957842 12.4957842
30 -4.2342158 10.3957842
31 1.3057842 -4.2342158
32 10.0726385 1.3057842
33 5.4026385 10.0726385
34 3.2726385 5.4026385
35 6.6526385 3.2726385
36 7.4188106 6.6526385
37 -3.3611894 7.4188106
38 -16.2711894 -3.3611894
39 -15.5311894 -16.2711894
40 -18.0243154 -15.5311894
41 -12.7343154 -18.0243154
42 -13.5043154 -12.7343154
43 -4.6543154 -13.5043154
44 -0.5240705 -4.6543154
45 17.7159295 -0.5240705
46 6.2559295 17.7159295
47 -5.7040705 6.2559295
48 -8.8353023 -5.7040705
49 -1.2853023 -8.8353023
50 0.8846977 -1.2853023
51 3.0946977 0.8846977
52 -4.8018457 3.0946977
53 8.0081543 -4.8018457
54 19.9081543 8.0081543
55 6.7281543 19.9081543
56 -9.0603883 6.7281543
57 -21.1003883 -9.0603883
58 -15.9803883 -21.1003883
59 -3.0503883 -15.9803883
60 NA -3.0503883
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -7.5211494 -7.4111494
[2,] -16.8211494 -7.5211494
[3,] -16.5511494 -16.8211494
[4,] -21.7726793 -16.5511494
[5,] -29.9726793 -21.7726793
[6,] -36.2426793 -29.9726793
[7,] -27.4126793 -36.2426793
[8,] -21.7974011 -27.4126793
[9,] -15.7674011 -21.7974011
[10,] -22.9274011 -15.7674011
[11,] -11.6774011 -22.9274011
[12,] 2.1390956 -11.6774011
[13,] -1.6509044 2.1390956
[14,] 12.6490956 -1.6509044
[15,] 13.5690956 12.6490956
[16,] 27.0488439 13.5690956
[17,] 24.6388439 27.0488439
[18,] 12.5288439 24.6388439
[19,] 13.2388439 12.5288439
[20,] 31.3546849 13.2388439
[21,] 30.2846849 31.3546849
[22,] 27.7846849 30.2846849
[23,] 31.1846849 27.7846849
[24,] 40.4372942 31.1846849
[25,] 21.3972942 40.4372942
[26,] -4.2327058 21.3972942
[27,] -7.4527058 -4.2327058
[28,] 12.4957842 -7.4527058
[29,] 10.3957842 12.4957842
[30,] -4.2342158 10.3957842
[31,] 1.3057842 -4.2342158
[32,] 10.0726385 1.3057842
[33,] 5.4026385 10.0726385
[34,] 3.2726385 5.4026385
[35,] 6.6526385 3.2726385
[36,] 7.4188106 6.6526385
[37,] -3.3611894 7.4188106
[38,] -16.2711894 -3.3611894
[39,] -15.5311894 -16.2711894
[40,] -18.0243154 -15.5311894
[41,] -12.7343154 -18.0243154
[42,] -13.5043154 -12.7343154
[43,] -4.6543154 -13.5043154
[44,] -0.5240705 -4.6543154
[45,] 17.7159295 -0.5240705
[46,] 6.2559295 17.7159295
[47,] -5.7040705 6.2559295
[48,] -8.8353023 -5.7040705
[49,] -1.2853023 -8.8353023
[50,] 0.8846977 -1.2853023
[51,] 3.0946977 0.8846977
[52,] -4.8018457 3.0946977
[53,] 8.0081543 -4.8018457
[54,] 19.9081543 8.0081543
[55,] 6.7281543 19.9081543
[56,] -9.0603883 6.7281543
[57,] -21.1003883 -9.0603883
[58,] -15.9803883 -21.1003883
[59,] -3.0503883 -15.9803883
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -7.5211494 -7.4111494
2 -16.8211494 -7.5211494
3 -16.5511494 -16.8211494
4 -21.7726793 -16.5511494
5 -29.9726793 -21.7726793
6 -36.2426793 -29.9726793
7 -27.4126793 -36.2426793
8 -21.7974011 -27.4126793
9 -15.7674011 -21.7974011
10 -22.9274011 -15.7674011
11 -11.6774011 -22.9274011
12 2.1390956 -11.6774011
13 -1.6509044 2.1390956
14 12.6490956 -1.6509044
15 13.5690956 12.6490956
16 27.0488439 13.5690956
17 24.6388439 27.0488439
18 12.5288439 24.6388439
19 13.2388439 12.5288439
20 31.3546849 13.2388439
21 30.2846849 31.3546849
22 27.7846849 30.2846849
23 31.1846849 27.7846849
24 40.4372942 31.1846849
25 21.3972942 40.4372942
26 -4.2327058 21.3972942
27 -7.4527058 -4.2327058
28 12.4957842 -7.4527058
29 10.3957842 12.4957842
30 -4.2342158 10.3957842
31 1.3057842 -4.2342158
32 10.0726385 1.3057842
33 5.4026385 10.0726385
34 3.2726385 5.4026385
35 6.6526385 3.2726385
36 7.4188106 6.6526385
37 -3.3611894 7.4188106
38 -16.2711894 -3.3611894
39 -15.5311894 -16.2711894
40 -18.0243154 -15.5311894
41 -12.7343154 -18.0243154
42 -13.5043154 -12.7343154
43 -4.6543154 -13.5043154
44 -0.5240705 -4.6543154
45 17.7159295 -0.5240705
46 6.2559295 17.7159295
47 -5.7040705 6.2559295
48 -8.8353023 -5.7040705
49 -1.2853023 -8.8353023
50 0.8846977 -1.2853023
51 3.0946977 0.8846977
52 -4.8018457 3.0946977
53 8.0081543 -4.8018457
54 19.9081543 8.0081543
55 6.7281543 19.9081543
56 -9.0603883 6.7281543
57 -21.1003883 -9.0603883
58 -15.9803883 -21.1003883
59 -3.0503883 -15.9803883
> 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/7cqzn1292001339.ps",horizontal=F,onefile=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/8mhgp1292001339.ps",horizontal=F,onefile=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/9mhgp1292001339.ps",horizontal=F,onefile=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/10f9fa1292001339.ps",horizontal=F,onefile=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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/1119ey1292001339.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/1249u41292001339.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13ijav1292001339.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14lk911292001339.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/157kp71292001339.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/16lcnf1292001339.tab")
+ }
>
> try(system("convert tmp/1qpiz1292001339.ps tmp/1qpiz1292001339.png",intern=TRUE))
character(0)
> try(system("convert tmp/2qpiz1292001339.ps tmp/2qpiz1292001339.png",intern=TRUE))
character(0)
> try(system("convert tmp/31zij1292001339.ps tmp/31zij1292001339.png",intern=TRUE))
character(0)
> try(system("convert tmp/41zij1292001339.ps tmp/41zij1292001339.png",intern=TRUE))
character(0)
> try(system("convert tmp/51zij1292001339.ps tmp/51zij1292001339.png",intern=TRUE))
character(0)
> try(system("convert tmp/6cqzn1292001339.ps tmp/6cqzn1292001339.png",intern=TRUE))
character(0)
> try(system("convert tmp/7cqzn1292001339.ps tmp/7cqzn1292001339.png",intern=TRUE))
character(0)
> try(system("convert tmp/8mhgp1292001339.ps tmp/8mhgp1292001339.png",intern=TRUE))
character(0)
> try(system("convert tmp/9mhgp1292001339.ps tmp/9mhgp1292001339.png",intern=TRUE))
character(0)
> try(system("convert tmp/10f9fa1292001339.ps tmp/10f9fa1292001339.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.501 1.642 8.422