R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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(695,0,638,0,762,0,635,0,721,0,854,0,418,0,367,0,824,0,687,0,601,0,676,0,740,0,691,0,683,0,594,0,729,0,731,0,386,0,331,0,707,0,715,0,657,0,653,0,642,0,643,0,718,0,654,0,632,0,731,0,392,1,344,1,792,1,852,1,649,1,629,1,685,1,617,1,715,1,715,1,629,1,916,1,531,1,357,1,917,1,828,1,708,1,858,1,775,1,785,1,1006,1,789,1,734,1,906,1,532,1,387,1,991,1,841,1,892,1,782,1,813,1,793,1,978,1,775,1,797,1,946,1,594,1,438,1,1022,1,868,1),dim=c(2,70),dimnames=list(c('Y','X'),1:70))
> y <- array(NA,dim=c(2,70),dimnames=list(c('Y','X'),1:70))
> 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
> 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
Y X
1 695 0
2 638 0
3 762 0
4 635 0
5 721 0
6 854 0
7 418 0
8 367 0
9 824 0
10 687 0
11 601 0
12 676 0
13 740 0
14 691 0
15 683 0
16 594 0
17 729 0
18 731 0
19 386 0
20 331 0
21 707 0
22 715 0
23 657 0
24 653 0
25 642 0
26 643 0
27 718 0
28 654 0
29 632 0
30 731 0
31 392 1
32 344 1
33 792 1
34 852 1
35 649 1
36 629 1
37 685 1
38 617 1
39 715 1
40 715 1
41 629 1
42 916 1
43 531 1
44 357 1
45 917 1
46 828 1
47 708 1
48 858 1
49 775 1
50 785 1
51 1006 1
52 789 1
53 734 1
54 906 1
55 532 1
56 387 1
57 991 1
58 841 1
59 892 1
60 782 1
61 813 1
62 793 1
63 978 1
64 775 1
65 797 1
66 946 1
67 594 1
68 438 1
69 1022 1
70 868 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
650.50 88.95
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-395.45 -53.21 36.02 86.54 282.55
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 650.50 29.36 22.16 <2e-16 ***
X 88.95 38.84 2.29 0.0251 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 160.8 on 68 degrees of freedom
Multiple R-squared: 0.07161, Adjusted R-squared: 0.05795
F-statistic: 5.245 on 1 and 68 DF, p-value: 0.02512
> 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,] 0.06674612 0.13349225 0.9332539
[2,] 0.13248196 0.26496392 0.8675180
[3,] 0.46372878 0.92745755 0.5362712
[4,] 0.70182113 0.59635774 0.2981789
[5,] 0.70358970 0.59282060 0.2964103
[6,] 0.60393264 0.79213471 0.3960674
[7,] 0.50964346 0.98071308 0.4903565
[8,] 0.40891272 0.81782544 0.5910873
[9,] 0.33932656 0.67865312 0.6606734
[10,] 0.25852758 0.51705515 0.7414724
[11,] 0.18952532 0.37905063 0.8104747
[12,] 0.14305335 0.28610670 0.8569466
[13,] 0.10678369 0.21356738 0.8932163
[14,] 0.07849898 0.15699797 0.9215010
[15,] 0.17256122 0.34512243 0.8274388
[16,] 0.37231320 0.74462640 0.6276868
[17,] 0.30950241 0.61900483 0.6904976
[18,] 0.25440799 0.50881598 0.7455920
[19,] 0.19632923 0.39265845 0.8036708
[20,] 0.14750164 0.29500327 0.8524984
[21,] 0.10808762 0.21617524 0.8919124
[22,] 0.07722639 0.15445277 0.9227736
[23,] 0.05713030 0.11426060 0.9428697
[24,] 0.03877902 0.07755803 0.9612210
[25,] 0.02622136 0.05244272 0.9737786
[26,] 0.01855771 0.03711543 0.9814423
[27,] 0.02247986 0.04495972 0.9775201
[28,] 0.03846710 0.07693420 0.9615329
[29,] 0.09795226 0.19590453 0.9020477
[30,] 0.14852171 0.29704342 0.8514783
[31,] 0.11958112 0.23916224 0.8804189
[32,] 0.09634739 0.19269479 0.9036526
[33,] 0.07483396 0.14966791 0.9251660
[34,] 0.06043472 0.12086944 0.9395653
[35,] 0.04601987 0.09203974 0.9539801
[36,] 0.03400439 0.06800878 0.9659956
[37,] 0.02639405 0.05278810 0.9736060
[38,] 0.03827992 0.07655984 0.9617201
[39,] 0.04522107 0.09044215 0.9547789
[40,] 0.18938894 0.37877789 0.8106111
[41,] 0.22461114 0.44922229 0.7753889
[42,] 0.19856793 0.39713586 0.8014321
[43,] 0.16011479 0.32022958 0.8398852
[44,] 0.14399918 0.28799835 0.8560008
[45,] 0.11053683 0.22107366 0.8894632
[46,] 0.08291198 0.16582396 0.9170880
[47,] 0.13077425 0.26154849 0.8692258
[48,] 0.09639112 0.19278224 0.9036089
[49,] 0.06817456 0.13634913 0.9318254
[50,] 0.06230330 0.12460659 0.9376967
[51,] 0.08570910 0.17141820 0.9142909
[52,] 0.36287895 0.72575790 0.6371210
[53,] 0.41052526 0.82105052 0.5894747
[54,] 0.33245141 0.66490282 0.6675486
[55,] 0.28109290 0.56218580 0.7189071
[56,] 0.20323653 0.40647305 0.7967635
[57,] 0.13858876 0.27717753 0.8614112
[58,] 0.08667676 0.17335352 0.9133232
[59,] 0.09172013 0.18344027 0.9082799
[60,] 0.04899805 0.09799610 0.9510019
[61,] 0.02255899 0.04511798 0.9774410
> postscript(file="/var/www/rcomp/tmp/1ratr1292926424.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/2ratr1292926424.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/rcomp/tmp/3ratr1292926424.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4jjac1292926424.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5jjac1292926424.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 = 70
Frequency = 1
1 2 3 4 5 6 7 8 9 10
44.50 -12.50 111.50 -15.50 70.50 203.50 -232.50 -283.50 173.50 36.50
11 12 13 14 15 16 17 18 19 20
-49.50 25.50 89.50 40.50 32.50 -56.50 78.50 80.50 -264.50 -319.50
21 22 23 24 25 26 27 28 29 30
56.50 64.50 6.50 2.50 -8.50 -7.50 67.50 3.50 -18.50 80.50
31 32 33 34 35 36 37 38 39 40
-347.45 -395.45 52.55 112.55 -90.45 -110.45 -54.45 -122.45 -24.45 -24.45
41 42 43 44 45 46 47 48 49 50
-110.45 176.55 -208.45 -382.45 177.55 88.55 -31.45 118.55 35.55 45.55
51 52 53 54 55 56 57 58 59 60
266.55 49.55 -5.45 166.55 -207.45 -352.45 251.55 101.55 152.55 42.55
61 62 63 64 65 66 67 68 69 70
73.55 53.55 238.55 35.55 57.55 206.55 -145.45 -301.45 282.55 128.55
> postscript(file="/var/www/rcomp/tmp/6jjac1292926424.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 = 70
Frequency = 1
lag(myerror, k = 1) myerror
0 44.50 NA
1 -12.50 44.50
2 111.50 -12.50
3 -15.50 111.50
4 70.50 -15.50
5 203.50 70.50
6 -232.50 203.50
7 -283.50 -232.50
8 173.50 -283.50
9 36.50 173.50
10 -49.50 36.50
11 25.50 -49.50
12 89.50 25.50
13 40.50 89.50
14 32.50 40.50
15 -56.50 32.50
16 78.50 -56.50
17 80.50 78.50
18 -264.50 80.50
19 -319.50 -264.50
20 56.50 -319.50
21 64.50 56.50
22 6.50 64.50
23 2.50 6.50
24 -8.50 2.50
25 -7.50 -8.50
26 67.50 -7.50
27 3.50 67.50
28 -18.50 3.50
29 80.50 -18.50
30 -347.45 80.50
31 -395.45 -347.45
32 52.55 -395.45
33 112.55 52.55
34 -90.45 112.55
35 -110.45 -90.45
36 -54.45 -110.45
37 -122.45 -54.45
38 -24.45 -122.45
39 -24.45 -24.45
40 -110.45 -24.45
41 176.55 -110.45
42 -208.45 176.55
43 -382.45 -208.45
44 177.55 -382.45
45 88.55 177.55
46 -31.45 88.55
47 118.55 -31.45
48 35.55 118.55
49 45.55 35.55
50 266.55 45.55
51 49.55 266.55
52 -5.45 49.55
53 166.55 -5.45
54 -207.45 166.55
55 -352.45 -207.45
56 251.55 -352.45
57 101.55 251.55
58 152.55 101.55
59 42.55 152.55
60 73.55 42.55
61 53.55 73.55
62 238.55 53.55
63 35.55 238.55
64 57.55 35.55
65 206.55 57.55
66 -145.45 206.55
67 -301.45 -145.45
68 282.55 -301.45
69 128.55 282.55
70 NA 128.55
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -12.50 44.50
[2,] 111.50 -12.50
[3,] -15.50 111.50
[4,] 70.50 -15.50
[5,] 203.50 70.50
[6,] -232.50 203.50
[7,] -283.50 -232.50
[8,] 173.50 -283.50
[9,] 36.50 173.50
[10,] -49.50 36.50
[11,] 25.50 -49.50
[12,] 89.50 25.50
[13,] 40.50 89.50
[14,] 32.50 40.50
[15,] -56.50 32.50
[16,] 78.50 -56.50
[17,] 80.50 78.50
[18,] -264.50 80.50
[19,] -319.50 -264.50
[20,] 56.50 -319.50
[21,] 64.50 56.50
[22,] 6.50 64.50
[23,] 2.50 6.50
[24,] -8.50 2.50
[25,] -7.50 -8.50
[26,] 67.50 -7.50
[27,] 3.50 67.50
[28,] -18.50 3.50
[29,] 80.50 -18.50
[30,] -347.45 80.50
[31,] -395.45 -347.45
[32,] 52.55 -395.45
[33,] 112.55 52.55
[34,] -90.45 112.55
[35,] -110.45 -90.45
[36,] -54.45 -110.45
[37,] -122.45 -54.45
[38,] -24.45 -122.45
[39,] -24.45 -24.45
[40,] -110.45 -24.45
[41,] 176.55 -110.45
[42,] -208.45 176.55
[43,] -382.45 -208.45
[44,] 177.55 -382.45
[45,] 88.55 177.55
[46,] -31.45 88.55
[47,] 118.55 -31.45
[48,] 35.55 118.55
[49,] 45.55 35.55
[50,] 266.55 45.55
[51,] 49.55 266.55
[52,] -5.45 49.55
[53,] 166.55 -5.45
[54,] -207.45 166.55
[55,] -352.45 -207.45
[56,] 251.55 -352.45
[57,] 101.55 251.55
[58,] 152.55 101.55
[59,] 42.55 152.55
[60,] 73.55 42.55
[61,] 53.55 73.55
[62,] 238.55 53.55
[63,] 35.55 238.55
[64,] 57.55 35.55
[65,] 206.55 57.55
[66,] -145.45 206.55
[67,] -301.45 -145.45
[68,] 282.55 -301.45
[69,] 128.55 282.55
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -12.50 44.50
2 111.50 -12.50
3 -15.50 111.50
4 70.50 -15.50
5 203.50 70.50
6 -232.50 203.50
7 -283.50 -232.50
8 173.50 -283.50
9 36.50 173.50
10 -49.50 36.50
11 25.50 -49.50
12 89.50 25.50
13 40.50 89.50
14 32.50 40.50
15 -56.50 32.50
16 78.50 -56.50
17 80.50 78.50
18 -264.50 80.50
19 -319.50 -264.50
20 56.50 -319.50
21 64.50 56.50
22 6.50 64.50
23 2.50 6.50
24 -8.50 2.50
25 -7.50 -8.50
26 67.50 -7.50
27 3.50 67.50
28 -18.50 3.50
29 80.50 -18.50
30 -347.45 80.50
31 -395.45 -347.45
32 52.55 -395.45
33 112.55 52.55
34 -90.45 112.55
35 -110.45 -90.45
36 -54.45 -110.45
37 -122.45 -54.45
38 -24.45 -122.45
39 -24.45 -24.45
40 -110.45 -24.45
41 176.55 -110.45
42 -208.45 176.55
43 -382.45 -208.45
44 177.55 -382.45
45 88.55 177.55
46 -31.45 88.55
47 118.55 -31.45
48 35.55 118.55
49 45.55 35.55
50 266.55 45.55
51 49.55 266.55
52 -5.45 49.55
53 166.55 -5.45
54 -207.45 166.55
55 -352.45 -207.45
56 251.55 -352.45
57 101.55 251.55
58 152.55 101.55
59 42.55 152.55
60 73.55 42.55
61 53.55 73.55
62 238.55 53.55
63 35.55 238.55
64 57.55 35.55
65 206.55 57.55
66 -145.45 206.55
67 -301.45 -145.45
68 282.55 -301.45
69 128.55 282.55
> 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/rcomp/tmp/7csrx1292926424.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8n1801292926424.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9n1801292926424.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10n1801292926424.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/111toq1292926424.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/rcomp/tmp/12u3ou1292926424.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/rcomp/tmp/130l251292926424.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/rcomp/tmp/14bvk81292926424.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/rcomp/tmp/15xd0e1292926424.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/rcomp/tmp/16snyn1292926424.tab")
+ }
>
> try(system("convert tmp/1ratr1292926424.ps tmp/1ratr1292926424.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ratr1292926424.ps tmp/2ratr1292926424.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ratr1292926424.ps tmp/3ratr1292926424.png",intern=TRUE))
character(0)
> try(system("convert tmp/4jjac1292926424.ps tmp/4jjac1292926424.png",intern=TRUE))
character(0)
> try(system("convert tmp/5jjac1292926424.ps tmp/5jjac1292926424.png",intern=TRUE))
character(0)
> try(system("convert tmp/6jjac1292926424.ps tmp/6jjac1292926424.png",intern=TRUE))
character(0)
> try(system("convert tmp/7csrx1292926424.ps tmp/7csrx1292926424.png",intern=TRUE))
character(0)
> try(system("convert tmp/8n1801292926424.ps tmp/8n1801292926424.png",intern=TRUE))
character(0)
> try(system("convert tmp/9n1801292926424.ps tmp/9n1801292926424.png",intern=TRUE))
character(0)
> try(system("convert tmp/10n1801292926424.ps tmp/10n1801292926424.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.27 0.82 4.11