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(-22,46,-20,50,-17,49,-21,48,-16,50,-11,47,-19,50,-31,49,-36,51,-33,52,-26,48,-38,55,-27,56,-21,43,-17,44,-14,50,-16,49,-16,47,-15,46,-7,50,-9,49,2,53,-6,54,0,56,7,56,4,58,-5,53,2,51,0,52,3,53,10,56,4,54,5,54,7,56,1,59,-8,62,-3,62,-16,73,-22,76,-32,80,-30,77,-32,81,-38,80,-41,80,-46,81,-58,80,-55,77,-48,71,-58,71,-58,64,-68,64,-75,47,-77,41,-75,35,-71,34,-63,33,-61,23,-53,16,-41,16,-35,8,-33,9),dim=c(2,61),dimnames=list(c('Econ','Price'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('Econ','Price'),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
Econ Price
1 -22 46
2 -20 50
3 -17 49
4 -21 48
5 -16 50
6 -11 47
7 -19 50
8 -31 49
9 -36 51
10 -33 52
11 -26 48
12 -38 55
13 -27 56
14 -21 43
15 -17 44
16 -14 50
17 -16 49
18 -16 47
19 -15 46
20 -7 50
21 -9 49
22 2 53
23 -6 54
24 0 56
25 7 56
26 4 58
27 -5 53
28 2 51
29 0 52
30 3 53
31 10 56
32 4 54
33 5 54
34 7 56
35 1 59
36 -8 62
37 -3 62
38 -16 73
39 -22 76
40 -32 80
41 -30 77
42 -32 81
43 -38 80
44 -41 80
45 -46 81
46 -58 80
47 -55 77
48 -48 71
49 -58 71
50 -58 64
51 -68 64
52 -75 47
53 -77 41
54 -75 35
55 -71 34
56 -63 33
57 -61 23
58 -53 16
59 -41 16
60 -35 8
61 -33 9
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Price
-33.2695 0.1343
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-49.237 -15.474 5.823 19.555 35.749
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -33.2695 10.2684 -3.240 0.00197 **
Price 0.1343 0.1846 0.727 0.46989
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 24.15 on 59 degrees of freedom
Multiple R-squared: 0.008887, Adjusted R-squared: -0.007911
F-statistic: 0.529 on 1 and 59 DF, p-value: 0.4699
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 7.578893e-04 1.515779e-03 0.9992421107
[2,] 2.078794e-03 4.157588e-03 0.9979212059
[3,] 3.275182e-04 6.550363e-04 0.9996724818
[4,] 8.547156e-04 1.709431e-03 0.9991452844
[5,] 1.084248e-03 2.168495e-03 0.9989157524
[6,] 3.375309e-04 6.750618e-04 0.9996624691
[7,] 1.167857e-04 2.335714e-04 0.9998832143
[8,] 2.938796e-05 5.877592e-05 0.9999706120
[9,] 1.706414e-05 3.412828e-05 0.9999829359
[10,] 6.350327e-06 1.270065e-05 0.9999936497
[11,] 1.537729e-06 3.075458e-06 0.9999984623
[12,] 1.077921e-06 2.155842e-06 0.9999989221
[13,] 3.986132e-07 7.972264e-07 0.9999996014
[14,] 1.107348e-07 2.214697e-07 0.9999998893
[15,] 2.916449e-08 5.832898e-08 0.9999999708
[16,] 7.855413e-08 1.571083e-07 0.9999999214
[17,] 6.706888e-08 1.341378e-07 0.9999999329
[18,] 1.334084e-06 2.668169e-06 0.9999986659
[19,] 1.588998e-06 3.177997e-06 0.9999984110
[20,] 3.191340e-06 6.382680e-06 0.9999968087
[21,] 1.007803e-05 2.015605e-05 0.9999899220
[22,] 1.149312e-05 2.298623e-05 0.9999885069
[23,] 7.516366e-06 1.503273e-05 0.9999924836
[24,] 1.155092e-05 2.310183e-05 0.9999884491
[25,] 1.313745e-05 2.627490e-05 0.9999868626
[26,] 1.979561e-05 3.959121e-05 0.9999802044
[27,] 5.351625e-05 1.070325e-04 0.9999464838
[28,] 9.978893e-05 1.995779e-04 0.9999002111
[29,] 2.512888e-04 5.025776e-04 0.9997487112
[30,] 8.761657e-04 1.752331e-03 0.9991238343
[31,] 2.277326e-03 4.554652e-03 0.9977226741
[32,] 5.599406e-03 1.119881e-02 0.9944005937
[33,] 2.159340e-02 4.318680e-02 0.9784065996
[34,] 7.473498e-02 1.494700e-01 0.9252650204
[35,] 1.518774e-01 3.037548e-01 0.8481226100
[36,] 2.170581e-01 4.341163e-01 0.7829418748
[37,] 2.806380e-01 5.612760e-01 0.7193619895
[38,] 3.549991e-01 7.099981e-01 0.6450009394
[39,] 4.178661e-01 8.357323e-01 0.5821338646
[40,] 4.853382e-01 9.706763e-01 0.5146618452
[41,] 5.440574e-01 9.118853e-01 0.4559426274
[42,] 5.605596e-01 8.788808e-01 0.4394404240
[43,] 5.813570e-01 8.372859e-01 0.4186429665
[44,] 7.103314e-01 5.793372e-01 0.2896686189
[45,] 8.072869e-01 3.854262e-01 0.1927131196
[46,] 9.357921e-01 1.284159e-01 0.0642079277
[47,] 9.984227e-01 3.154591e-03 0.0015772954
[48,] 9.994900e-01 1.020063e-03 0.0005100313
[49,] 9.990415e-01 1.917017e-03 0.0009585083
[50,] 9.976344e-01 4.731169e-03 0.0023655846
[51,] 9.918435e-01 1.631294e-02 0.0081564680
[52,] 9.871466e-01 2.570684e-02 0.0128534218
> postscript(file="/var/www/html/rcomp/tmp/1rgxq1258813962.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2zduk1258813962.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3qg521258813962.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ki4m1258813962.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/58rev1258813962.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
5.0920006 6.5548254 9.6891192 5.8234130 10.5548254 15.9577068
7 8 9 10 11 12
7.5548254 -4.3108808 -9.5794684 -6.7137622 0.8234130 -12.1166435
13 14 15 16 17 18
-1.2509373 6.4948819 10.3605882 12.5548254 10.6891192 10.9577068
19 20 21 22 23 24
12.0920006 19.5548254 17.6891192 28.1519441 20.0176503 25.7490627
25 26 27 28 29 30
32.7490627 29.4804751 21.1519441 28.4205316 26.2862378 29.1519441
31 32 33 34 35 36
35.7490627 30.0176503 31.0176503 32.7490627 26.3461813 16.9433000
37 38 39 40 41 42
21.9433000 7.4660683 1.0631869 -9.4739882 -7.0711069 -9.6082820
43 44 45 46 47 48
-15.4739882 -18.4739882 -23.6082820 -35.4739882 -32.0711069 -24.2653441
49 50 51 52 53 54
-34.2653441 -33.3252876 -43.3252876 -48.0422932 -49.2365305 -46.4307678
55 56 57 58 59 60
-42.2964740 -34.1621802 -30.8192423 -21.8791858 -9.8791858 -2.8048355
61
-0.9391293
> postscript(file="/var/www/html/rcomp/tmp/698oy1258813962.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 5.0920006 NA
1 6.5548254 5.0920006
2 9.6891192 6.5548254
3 5.8234130 9.6891192
4 10.5548254 5.8234130
5 15.9577068 10.5548254
6 7.5548254 15.9577068
7 -4.3108808 7.5548254
8 -9.5794684 -4.3108808
9 -6.7137622 -9.5794684
10 0.8234130 -6.7137622
11 -12.1166435 0.8234130
12 -1.2509373 -12.1166435
13 6.4948819 -1.2509373
14 10.3605882 6.4948819
15 12.5548254 10.3605882
16 10.6891192 12.5548254
17 10.9577068 10.6891192
18 12.0920006 10.9577068
19 19.5548254 12.0920006
20 17.6891192 19.5548254
21 28.1519441 17.6891192
22 20.0176503 28.1519441
23 25.7490627 20.0176503
24 32.7490627 25.7490627
25 29.4804751 32.7490627
26 21.1519441 29.4804751
27 28.4205316 21.1519441
28 26.2862378 28.4205316
29 29.1519441 26.2862378
30 35.7490627 29.1519441
31 30.0176503 35.7490627
32 31.0176503 30.0176503
33 32.7490627 31.0176503
34 26.3461813 32.7490627
35 16.9433000 26.3461813
36 21.9433000 16.9433000
37 7.4660683 21.9433000
38 1.0631869 7.4660683
39 -9.4739882 1.0631869
40 -7.0711069 -9.4739882
41 -9.6082820 -7.0711069
42 -15.4739882 -9.6082820
43 -18.4739882 -15.4739882
44 -23.6082820 -18.4739882
45 -35.4739882 -23.6082820
46 -32.0711069 -35.4739882
47 -24.2653441 -32.0711069
48 -34.2653441 -24.2653441
49 -33.3252876 -34.2653441
50 -43.3252876 -33.3252876
51 -48.0422932 -43.3252876
52 -49.2365305 -48.0422932
53 -46.4307678 -49.2365305
54 -42.2964740 -46.4307678
55 -34.1621802 -42.2964740
56 -30.8192423 -34.1621802
57 -21.8791858 -30.8192423
58 -9.8791858 -21.8791858
59 -2.8048355 -9.8791858
60 -0.9391293 -2.8048355
61 NA -0.9391293
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 6.5548254 5.092001
[2,] 9.6891192 6.554825
[3,] 5.8234130 9.689119
[4,] 10.5548254 5.823413
[5,] 15.9577068 10.554825
[6,] 7.5548254 15.957707
[7,] -4.3108808 7.554825
[8,] -9.5794684 -4.310881
[9,] -6.7137622 -9.579468
[10,] 0.8234130 -6.713762
[11,] -12.1166435 0.823413
[12,] -1.2509373 -12.116644
[13,] 6.4948819 -1.250937
[14,] 10.3605882 6.494882
[15,] 12.5548254 10.360588
[16,] 10.6891192 12.554825
[17,] 10.9577068 10.689119
[18,] 12.0920006 10.957707
[19,] 19.5548254 12.092001
[20,] 17.6891192 19.554825
[21,] 28.1519441 17.689119
[22,] 20.0176503 28.151944
[23,] 25.7490627 20.017650
[24,] 32.7490627 25.749063
[25,] 29.4804751 32.749063
[26,] 21.1519441 29.480475
[27,] 28.4205316 21.151944
[28,] 26.2862378 28.420532
[29,] 29.1519441 26.286238
[30,] 35.7490627 29.151944
[31,] 30.0176503 35.749063
[32,] 31.0176503 30.017650
[33,] 32.7490627 31.017650
[34,] 26.3461813 32.749063
[35,] 16.9433000 26.346181
[36,] 21.9433000 16.943300
[37,] 7.4660683 21.943300
[38,] 1.0631869 7.466068
[39,] -9.4739882 1.063187
[40,] -7.0711069 -9.473988
[41,] -9.6082820 -7.071107
[42,] -15.4739882 -9.608282
[43,] -18.4739882 -15.473988
[44,] -23.6082820 -18.473988
[45,] -35.4739882 -23.608282
[46,] -32.0711069 -35.473988
[47,] -24.2653441 -32.071107
[48,] -34.2653441 -24.265344
[49,] -33.3252876 -34.265344
[50,] -43.3252876 -33.325288
[51,] -48.0422932 -43.325288
[52,] -49.2365305 -48.042293
[53,] -46.4307678 -49.236530
[54,] -42.2964740 -46.430768
[55,] -34.1621802 -42.296474
[56,] -30.8192423 -34.162180
[57,] -21.8791858 -30.819242
[58,] -9.8791858 -21.879186
[59,] -2.8048355 -9.879186
[60,] -0.9391293 -2.804835
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 6.5548254 5.092001
2 9.6891192 6.554825
3 5.8234130 9.689119
4 10.5548254 5.823413
5 15.9577068 10.554825
6 7.5548254 15.957707
7 -4.3108808 7.554825
8 -9.5794684 -4.310881
9 -6.7137622 -9.579468
10 0.8234130 -6.713762
11 -12.1166435 0.823413
12 -1.2509373 -12.116644
13 6.4948819 -1.250937
14 10.3605882 6.494882
15 12.5548254 10.360588
16 10.6891192 12.554825
17 10.9577068 10.689119
18 12.0920006 10.957707
19 19.5548254 12.092001
20 17.6891192 19.554825
21 28.1519441 17.689119
22 20.0176503 28.151944
23 25.7490627 20.017650
24 32.7490627 25.749063
25 29.4804751 32.749063
26 21.1519441 29.480475
27 28.4205316 21.151944
28 26.2862378 28.420532
29 29.1519441 26.286238
30 35.7490627 29.151944
31 30.0176503 35.749063
32 31.0176503 30.017650
33 32.7490627 31.017650
34 26.3461813 32.749063
35 16.9433000 26.346181
36 21.9433000 16.943300
37 7.4660683 21.943300
38 1.0631869 7.466068
39 -9.4739882 1.063187
40 -7.0711069 -9.473988
41 -9.6082820 -7.071107
42 -15.4739882 -9.608282
43 -18.4739882 -15.473988
44 -23.6082820 -18.473988
45 -35.4739882 -23.608282
46 -32.0711069 -35.473988
47 -24.2653441 -32.071107
48 -34.2653441 -24.265344
49 -33.3252876 -34.265344
50 -43.3252876 -33.325288
51 -48.0422932 -43.325288
52 -49.2365305 -48.042293
53 -46.4307678 -49.236530
54 -42.2964740 -46.430768
55 -34.1621802 -42.296474
56 -30.8192423 -34.162180
57 -21.8791858 -30.819242
58 -9.8791858 -21.879186
59 -2.8048355 -9.879186
60 -0.9391293 -2.804835
> 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/7wcer1258813962.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8yz8d1258813962.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9rx8w1258813962.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10i4eg1258813962.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11umyl1258813962.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/12g3pt1258813962.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/13uzbs1258813963.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/14sma21258813963.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/1555ev1258813963.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/16e75m1258813963.tab")
+ }
>
> system("convert tmp/1rgxq1258813962.ps tmp/1rgxq1258813962.png")
> system("convert tmp/2zduk1258813962.ps tmp/2zduk1258813962.png")
> system("convert tmp/3qg521258813962.ps tmp/3qg521258813962.png")
> system("convert tmp/4ki4m1258813962.ps tmp/4ki4m1258813962.png")
> system("convert tmp/58rev1258813962.ps tmp/58rev1258813962.png")
> system("convert tmp/698oy1258813962.ps tmp/698oy1258813962.png")
> system("convert tmp/7wcer1258813962.ps tmp/7wcer1258813962.png")
> system("convert tmp/8yz8d1258813962.ps tmp/8yz8d1258813962.png")
> system("convert tmp/9rx8w1258813962.ps tmp/9rx8w1258813962.png")
> system("convert tmp/10i4eg1258813962.ps tmp/10i4eg1258813962.png")
>
>
> proc.time()
user system elapsed
2.455 1.554 2.918