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(9.3,104.1,8.7,90.2,8.2,99.2,8.3,116.5,8.5,98.4,8.6,90.6,8.5,130.5,8.2,107.4,8.1,106,7.9,196.5,8.6,107.8,8.7,90.5,8.7,123.8,8.5,114.7,8.4,115.3,8.5,197,8.7,88.4,8.7,93.8,8.6,111.3,8.5,105.9,8.3,123.6,8,171,8.2,97,8.1,99.2,8.1,126.6,8,103.4,7.9,121.3,7.9,129.6,8,110.8,8,98.9,7.9,122.8,8,120.9,7.7,133.1,7.2,203.1,7.5,110.2,7.3,119.5,7,135.1,7,113.9,7,137.4,7.2,157.1,7.3,126.4,7.1,112.2,6.8,128.8,6.4,136.8,6.1,156.5,6.5,215.2,7.7,146.7,7.9,130.8,7.5,133.1,6.9,153.4,6.6,159.9,6.9,174.6,7.7,145,8,112.9,8,137.8,7.7,150.6,7.3,162.1,7.4,226.4,8.1,112.3,8.3,126.3),dim=c(2,60),dimnames=list(c('X','Y'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('X','Y'),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 = '2'
> #'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
Y X
1 104.1 9.3
2 90.2 8.7
3 99.2 8.2
4 116.5 8.3
5 98.4 8.5
6 90.6 8.6
7 130.5 8.5
8 107.4 8.2
9 106.0 8.1
10 196.5 7.9
11 107.8 8.6
12 90.5 8.7
13 123.8 8.7
14 114.7 8.5
15 115.3 8.4
16 197.0 8.5
17 88.4 8.7
18 93.8 8.7
19 111.3 8.6
20 105.9 8.5
21 123.6 8.3
22 171.0 8.0
23 97.0 8.2
24 99.2 8.1
25 126.6 8.1
26 103.4 8.0
27 121.3 7.9
28 129.6 7.9
29 110.8 8.0
30 98.9 8.0
31 122.8 7.9
32 120.9 8.0
33 133.1 7.7
34 203.1 7.2
35 110.2 7.5
36 119.5 7.3
37 135.1 7.0
38 113.9 7.0
39 137.4 7.0
40 157.1 7.2
41 126.4 7.3
42 112.2 7.1
43 128.8 6.8
44 136.8 6.4
45 156.5 6.1
46 215.2 6.5
47 146.7 7.7
48 130.8 7.9
49 133.1 7.5
50 153.4 6.9
51 159.9 6.6
52 174.6 6.9
53 145.0 7.7
54 112.9 8.0
55 137.8 8.0
56 150.6 7.7
57 162.1 7.3
58 226.4 7.4
59 112.3 8.1
60 126.3 8.3
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
324.71 -24.88
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-36.629 -17.301 -4.867 10.987 85.824
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 324.707 40.249 8.067 4.72e-11 ***
X -24.882 5.111 -4.868 9.04e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 26.9 on 58 degrees of freedom
Multiple R-squared: 0.2901, Adjusted R-squared: 0.2778
F-statistic: 23.7 on 1 and 58 DF, p-value: 9.04e-06
> 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,] 0.07614576 0.15229152 0.9238542
[2,] 0.03824587 0.07649173 0.9617541
[3,] 0.09987605 0.19975211 0.9001239
[4,] 0.04761780 0.09523559 0.9523822
[5,] 0.02151127 0.04302254 0.9784887
[6,] 0.64548408 0.70903184 0.3545159
[7,] 0.54131570 0.91736860 0.4586843
[8,] 0.46253479 0.92506957 0.5374652
[9,] 0.41591585 0.83183169 0.5840842
[10,] 0.32447740 0.64895481 0.6755226
[11,] 0.24374954 0.48749907 0.7562505
[12,] 0.86291016 0.27417967 0.1370898
[13,] 0.83533707 0.32932586 0.1646629
[14,] 0.79116471 0.41767058 0.2088353
[15,] 0.72680552 0.54638897 0.2731945
[16,] 0.66117295 0.67765409 0.3388270
[17,] 0.58561699 0.82876603 0.4143830
[18,] 0.65882311 0.68235378 0.3411769
[19,] 0.66586352 0.66827296 0.3341365
[20,] 0.67142025 0.65715949 0.3285797
[21,] 0.59966888 0.80066224 0.4003311
[22,] 0.59015218 0.81969565 0.4098478
[23,] 0.52375613 0.95248774 0.4762439
[24,] 0.44742796 0.89485592 0.5525720
[25,] 0.39962286 0.79924571 0.6003771
[26,] 0.40438372 0.80876745 0.5956163
[27,] 0.33720306 0.67440613 0.6627969
[28,] 0.27503497 0.55006993 0.7249650
[29,] 0.21547253 0.43094506 0.7845275
[30,] 0.40520867 0.81041735 0.5947913
[31,] 0.43629782 0.87259564 0.5637022
[32,] 0.42999991 0.85999983 0.5700001
[33,] 0.37925649 0.75851297 0.6207435
[34,] 0.43428689 0.86857378 0.5657131
[35,] 0.37445809 0.74891618 0.6255419
[36,] 0.31382758 0.62765516 0.6861724
[37,] 0.27528103 0.55056206 0.7247190
[38,] 0.33804334 0.67608668 0.6619567
[39,] 0.35217298 0.70434596 0.6478270
[40,] 0.41573844 0.83147688 0.5842616
[41,] 0.51104885 0.97790231 0.4889512
[42,] 0.61569015 0.76861970 0.3843099
[43,] 0.52955041 0.94089917 0.4704496
[44,] 0.43569848 0.87139696 0.5643015
[45,] 0.37287500 0.74575000 0.6271250
[46,] 0.32254190 0.64508379 0.6774581
[47,] 0.40529132 0.81058264 0.5947087
[48,] 0.45220883 0.90441767 0.5477912
[49,] 0.34982697 0.69965393 0.6501730
[50,] 0.29563504 0.59127007 0.7043650
[51,] 0.17644814 0.35289627 0.8235519
> postscript(file="/var/www/html/rcomp/tmp/1z63z1258743441.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2i0mk1258743441.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/30o7f1258743441.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4g8bv1258743441.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5d5wo1258743441.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 60
Frequency = 1
1 2 3 4 5 6
10.80069885 -18.02879896 -21.47004713 -1.68179750 -14.80529823 -20.11704859
7 8 9 10 11 12
17.29470177 -13.27004713 -17.15829677 68.36520397 -2.91704859 -17.72879896
13 14 15 16 17 18
15.57120104 1.49470177 -0.39354786 83.79470177 -19.82879896 -14.42879896
19 20 21 22 23 24
0.58295141 -7.30529823 5.41820250 45.35345360 -23.67004713 -23.95829677
25 26 27 28 29 30
3.44170323 -22.24654640 -6.83479603 1.46520397 -14.84654640 -26.74654640
31 32 33 34 35 36
-5.33479603 -4.74654640 -0.01129530 57.54745653 -27.88779457 -23.56429384
37 38 39 40 41 42
-15.42904274 -36.62904274 -13.12904274 11.54745653 -16.66429384 -35.84079311
43 44 45 46 47 48
-26.70554201 -28.65854055 -16.42328945 52.22970908 13.58870470 2.66520397
49 50 51 52 53 54
-4.98779457 0.38270762 -0.58204128 21.58270762 11.88870470 -12.74654640
55 56 57 58 59 60
12.15345360 17.48870470 19.03570616 85.82395579 -10.85829677 8.11820250
> postscript(file="/var/www/html/rcomp/tmp/6ol3a1258743441.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 10.80069885 NA
1 -18.02879896 10.80069885
2 -21.47004713 -18.02879896
3 -1.68179750 -21.47004713
4 -14.80529823 -1.68179750
5 -20.11704859 -14.80529823
6 17.29470177 -20.11704859
7 -13.27004713 17.29470177
8 -17.15829677 -13.27004713
9 68.36520397 -17.15829677
10 -2.91704859 68.36520397
11 -17.72879896 -2.91704859
12 15.57120104 -17.72879896
13 1.49470177 15.57120104
14 -0.39354786 1.49470177
15 83.79470177 -0.39354786
16 -19.82879896 83.79470177
17 -14.42879896 -19.82879896
18 0.58295141 -14.42879896
19 -7.30529823 0.58295141
20 5.41820250 -7.30529823
21 45.35345360 5.41820250
22 -23.67004713 45.35345360
23 -23.95829677 -23.67004713
24 3.44170323 -23.95829677
25 -22.24654640 3.44170323
26 -6.83479603 -22.24654640
27 1.46520397 -6.83479603
28 -14.84654640 1.46520397
29 -26.74654640 -14.84654640
30 -5.33479603 -26.74654640
31 -4.74654640 -5.33479603
32 -0.01129530 -4.74654640
33 57.54745653 -0.01129530
34 -27.88779457 57.54745653
35 -23.56429384 -27.88779457
36 -15.42904274 -23.56429384
37 -36.62904274 -15.42904274
38 -13.12904274 -36.62904274
39 11.54745653 -13.12904274
40 -16.66429384 11.54745653
41 -35.84079311 -16.66429384
42 -26.70554201 -35.84079311
43 -28.65854055 -26.70554201
44 -16.42328945 -28.65854055
45 52.22970908 -16.42328945
46 13.58870470 52.22970908
47 2.66520397 13.58870470
48 -4.98779457 2.66520397
49 0.38270762 -4.98779457
50 -0.58204128 0.38270762
51 21.58270762 -0.58204128
52 11.88870470 21.58270762
53 -12.74654640 11.88870470
54 12.15345360 -12.74654640
55 17.48870470 12.15345360
56 19.03570616 17.48870470
57 85.82395579 19.03570616
58 -10.85829677 85.82395579
59 8.11820250 -10.85829677
60 NA 8.11820250
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -18.02879896 10.80069885
[2,] -21.47004713 -18.02879896
[3,] -1.68179750 -21.47004713
[4,] -14.80529823 -1.68179750
[5,] -20.11704859 -14.80529823
[6,] 17.29470177 -20.11704859
[7,] -13.27004713 17.29470177
[8,] -17.15829677 -13.27004713
[9,] 68.36520397 -17.15829677
[10,] -2.91704859 68.36520397
[11,] -17.72879896 -2.91704859
[12,] 15.57120104 -17.72879896
[13,] 1.49470177 15.57120104
[14,] -0.39354786 1.49470177
[15,] 83.79470177 -0.39354786
[16,] -19.82879896 83.79470177
[17,] -14.42879896 -19.82879896
[18,] 0.58295141 -14.42879896
[19,] -7.30529823 0.58295141
[20,] 5.41820250 -7.30529823
[21,] 45.35345360 5.41820250
[22,] -23.67004713 45.35345360
[23,] -23.95829677 -23.67004713
[24,] 3.44170323 -23.95829677
[25,] -22.24654640 3.44170323
[26,] -6.83479603 -22.24654640
[27,] 1.46520397 -6.83479603
[28,] -14.84654640 1.46520397
[29,] -26.74654640 -14.84654640
[30,] -5.33479603 -26.74654640
[31,] -4.74654640 -5.33479603
[32,] -0.01129530 -4.74654640
[33,] 57.54745653 -0.01129530
[34,] -27.88779457 57.54745653
[35,] -23.56429384 -27.88779457
[36,] -15.42904274 -23.56429384
[37,] -36.62904274 -15.42904274
[38,] -13.12904274 -36.62904274
[39,] 11.54745653 -13.12904274
[40,] -16.66429384 11.54745653
[41,] -35.84079311 -16.66429384
[42,] -26.70554201 -35.84079311
[43,] -28.65854055 -26.70554201
[44,] -16.42328945 -28.65854055
[45,] 52.22970908 -16.42328945
[46,] 13.58870470 52.22970908
[47,] 2.66520397 13.58870470
[48,] -4.98779457 2.66520397
[49,] 0.38270762 -4.98779457
[50,] -0.58204128 0.38270762
[51,] 21.58270762 -0.58204128
[52,] 11.88870470 21.58270762
[53,] -12.74654640 11.88870470
[54,] 12.15345360 -12.74654640
[55,] 17.48870470 12.15345360
[56,] 19.03570616 17.48870470
[57,] 85.82395579 19.03570616
[58,] -10.85829677 85.82395579
[59,] 8.11820250 -10.85829677
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -18.02879896 10.80069885
2 -21.47004713 -18.02879896
3 -1.68179750 -21.47004713
4 -14.80529823 -1.68179750
5 -20.11704859 -14.80529823
6 17.29470177 -20.11704859
7 -13.27004713 17.29470177
8 -17.15829677 -13.27004713
9 68.36520397 -17.15829677
10 -2.91704859 68.36520397
11 -17.72879896 -2.91704859
12 15.57120104 -17.72879896
13 1.49470177 15.57120104
14 -0.39354786 1.49470177
15 83.79470177 -0.39354786
16 -19.82879896 83.79470177
17 -14.42879896 -19.82879896
18 0.58295141 -14.42879896
19 -7.30529823 0.58295141
20 5.41820250 -7.30529823
21 45.35345360 5.41820250
22 -23.67004713 45.35345360
23 -23.95829677 -23.67004713
24 3.44170323 -23.95829677
25 -22.24654640 3.44170323
26 -6.83479603 -22.24654640
27 1.46520397 -6.83479603
28 -14.84654640 1.46520397
29 -26.74654640 -14.84654640
30 -5.33479603 -26.74654640
31 -4.74654640 -5.33479603
32 -0.01129530 -4.74654640
33 57.54745653 -0.01129530
34 -27.88779457 57.54745653
35 -23.56429384 -27.88779457
36 -15.42904274 -23.56429384
37 -36.62904274 -15.42904274
38 -13.12904274 -36.62904274
39 11.54745653 -13.12904274
40 -16.66429384 11.54745653
41 -35.84079311 -16.66429384
42 -26.70554201 -35.84079311
43 -28.65854055 -26.70554201
44 -16.42328945 -28.65854055
45 52.22970908 -16.42328945
46 13.58870470 52.22970908
47 2.66520397 13.58870470
48 -4.98779457 2.66520397
49 0.38270762 -4.98779457
50 -0.58204128 0.38270762
51 21.58270762 -0.58204128
52 11.88870470 21.58270762
53 -12.74654640 11.88870470
54 12.15345360 -12.74654640
55 17.48870470 12.15345360
56 19.03570616 17.48870470
57 85.82395579 19.03570616
58 -10.85829677 85.82395579
59 8.11820250 -10.85829677
> 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/7emjo1258743441.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8hfn81258743441.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9rn5w1258743441.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10o9gi1258743441.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/116p981258743441.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/12xq8a1258743441.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/13ry3y1258743441.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/14m9a01258743441.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/15vymy1258743441.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/16npgb1258743441.tab")
+ }
>
> system("convert tmp/1z63z1258743441.ps tmp/1z63z1258743441.png")
> system("convert tmp/2i0mk1258743441.ps tmp/2i0mk1258743441.png")
> system("convert tmp/30o7f1258743441.ps tmp/30o7f1258743441.png")
> system("convert tmp/4g8bv1258743441.ps tmp/4g8bv1258743441.png")
> system("convert tmp/5d5wo1258743441.ps tmp/5d5wo1258743441.png")
> system("convert tmp/6ol3a1258743441.ps tmp/6ol3a1258743441.png")
> system("convert tmp/7emjo1258743441.ps tmp/7emjo1258743441.png")
> system("convert tmp/8hfn81258743441.ps tmp/8hfn81258743441.png")
> system("convert tmp/9rn5w1258743441.ps tmp/9rn5w1258743441.png")
> system("convert tmp/10o9gi1258743441.ps tmp/10o9gi1258743441.png")
>
>
> proc.time()
user system elapsed
2.510 1.581 5.633