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
'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(104.08,99.2,103.86,93.6,107.47,104.2,111.1,95.3,117.33,102.7,119.04,103.1,123.68,100,125.9,107.2,124.54,107,119.39,119,118.8,110.4,114.81,101.7,117.9,102.4,120.53,98.8,125.15,105.6,126.49,104.4,131.85,106.3,127.4,107.2,131.08,108.5,122.37,106.9,124.34,114.2,119.61,125.9,119.97,110.6,116.46,110.5,117.03,106.7,120.96,104.7,124.71,107.4,127.08,109.8,131.91,103.4,137.69,114.8,142.46,114.3,144.32,109.6,138.06,118.3,124.45,127.3,126.71,112.3,121.83,114.9,122.51,108.2,125.48,105.4,127.77,122.1,128.03,113.5,132.84,110,133.41,125.3,139.99,114.3,138.53,115.6,136.12,127.1,124.75,123,122.88,122.2,121.46,126.4,118.4,112.7,122.45,105.8,128.94,120.9,133.25,116.3,137.94,115.7,140.04,127.9,130.74,108.3,131.55,121.1,129.47,128.6,125.45,123.1,127.87,127.7,124.68,126.6),dim=c(2,60),dimnames=list(c('Y','X'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Y','X'),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
Y X
1 104.08 99.2
2 103.86 93.6
3 107.47 104.2
4 111.10 95.3
5 117.33 102.7
6 119.04 103.1
7 123.68 100.0
8 125.90 107.2
9 124.54 107.0
10 119.39 119.0
11 118.80 110.4
12 114.81 101.7
13 117.90 102.4
14 120.53 98.8
15 125.15 105.6
16 126.49 104.4
17 131.85 106.3
18 127.40 107.2
19 131.08 108.5
20 122.37 106.9
21 124.34 114.2
22 119.61 125.9
23 119.97 110.6
24 116.46 110.5
25 117.03 106.7
26 120.96 104.7
27 124.71 107.4
28 127.08 109.8
29 131.91 103.4
30 137.69 114.8
31 142.46 114.3
32 144.32 109.6
33 138.06 118.3
34 124.45 127.3
35 126.71 112.3
36 121.83 114.9
37 122.51 108.2
38 125.48 105.4
39 127.77 122.1
40 128.03 113.5
41 132.84 110.0
42 133.41 125.3
43 139.99 114.3
44 138.53 115.6
45 136.12 127.1
46 124.75 123.0
47 122.88 122.2
48 121.46 126.4
49 118.40 112.7
50 122.45 105.8
51 128.94 120.9
52 133.25 116.3
53 137.94 115.7
54 140.04 127.9
55 130.74 108.3
56 131.55 121.1
57 129.47 128.6
58 125.45 123.1
59 127.87 127.7
60 124.68 126.6
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
75.6033 0.4452
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-15.6849 -5.6953 -0.3691 4.1579 19.9253
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 75.6033 12.4507 6.072 1.04e-07 ***
X 0.4452 0.1105 4.027 0.000166 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7.72 on 58 degrees of freedom
Multiple R-squared: 0.2185, Adjusted R-squared: 0.205
F-statistic: 16.22 on 1 and 58 DF, p-value: 0.0001662
> 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,] 0.4640749 0.92814973 0.53592513
[2,] 0.4680689 0.93613779 0.53193111
[3,] 0.6827044 0.63459124 0.31729562
[4,] 0.6216707 0.75665863 0.37832932
[5,] 0.5157055 0.96858896 0.48429448
[6,] 0.6307705 0.73845908 0.36922954
[7,] 0.5484528 0.90309435 0.45154717
[8,] 0.4820679 0.96413581 0.51793209
[9,] 0.4191280 0.83825598 0.58087201
[10,] 0.4173728 0.83474561 0.58262719
[11,] 0.4080358 0.81607153 0.59196423
[12,] 0.4268593 0.85371867 0.57314066
[13,] 0.5362360 0.92752809 0.46376404
[14,] 0.4979327 0.99586544 0.50206728
[15,] 0.4996999 0.99939970 0.50030015
[16,] 0.4285623 0.85712464 0.57143768
[17,] 0.3643969 0.72879385 0.63560307
[18,] 0.4817722 0.96354443 0.51822779
[19,] 0.4414392 0.88287846 0.55856077
[20,] 0.4710236 0.94204727 0.52897636
[21,] 0.4873149 0.97462986 0.51268507
[22,] 0.4635351 0.92707014 0.53646493
[23,] 0.4268257 0.85365137 0.57317432
[24,] 0.3881082 0.77621639 0.61189180
[25,] 0.4489693 0.89793858 0.55103071
[26,] 0.5392989 0.92140215 0.46070108
[27,] 0.7484049 0.50319015 0.25159507
[28,] 0.9396323 0.12073546 0.06036773
[29,] 0.9489064 0.10218726 0.05109363
[30,] 0.9504271 0.09914576 0.04957288
[31,] 0.9274554 0.14508918 0.07254459
[32,] 0.9215482 0.15690357 0.07845178
[33,] 0.9064600 0.18708008 0.09354004
[34,] 0.8791797 0.24164061 0.12082031
[35,] 0.8377814 0.32443726 0.16221863
[36,] 0.7854032 0.42919361 0.21459681
[37,] 0.7499038 0.50019243 0.25009622
[38,] 0.6896027 0.62079469 0.31039734
[39,] 0.7847716 0.43045673 0.21522836
[40,] 0.8459928 0.30801444 0.15400722
[41,] 0.8345355 0.33092892 0.16546446
[42,] 0.7953793 0.40924145 0.20462072
[43,] 0.7764843 0.44703131 0.22351566
[44,] 0.8159761 0.36804771 0.18402385
[45,] 0.8812725 0.23745509 0.11872755
[46,] 0.9064235 0.18715304 0.09357652
[47,] 0.8500439 0.29991229 0.14995615
[48,] 0.7666163 0.46676747 0.23338374
[49,] 0.7765018 0.44699643 0.22349821
[50,] 0.9746749 0.05065028 0.02532514
[51,] 0.9223476 0.15530488 0.07765244
> postscript(file="/var/www/html/rcomp/tmp/1gxwu1258761893.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/20e2r1258761893.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3kn7d1258761893.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4dvgv1258761893.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5fpyf1258761893.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
-15.6848500 -13.4118572 -14.5207365 -6.9286586 -3.9929705 -2.4610415
7 8 9 10 11 12
3.5590082 2.5737316 1.3027671 -9.1893605 -5.9508357 -6.0677932
13 14 15 16 17 18
-3.2894174 0.9432209 2.5360153 4.4102281 8.9243912 4.0737316
19 20 21 22 23 24
7.1750011 -0.8227152 -2.1025094 -12.0410838 -4.8698712 -8.3353534
25 26 27 28 29 30
-6.0736797 -1.2533251 1.2946962 2.5962707 10.2754054 10.9803842
31 32 33 34 35 36
15.9729728 19.9253061 9.7922637 -7.8243320 1.1133274 -4.9241335
37 38 39 40 41 42
-1.2614457 2.9550508 -2.1894101 1.8991147 8.2672352 2.0260226
43 44 45 46 47 48
13.5029728 11.4642423 3.9347035 -5.6100696 -7.1239278 -10.4136724
49 50 51 52 53 54
-7.3747435 -0.2530202 -0.4851973 5.8726182 10.8297246 7.4985616
55 56 57 58 59 60
6.9240366 2.0357672 -3.3830625 -4.9545874 -4.5824029 -7.2827079
> postscript(file="/var/www/html/rcomp/tmp/6hf3b1258761893.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 -15.6848500 NA
1 -13.4118572 -15.6848500
2 -14.5207365 -13.4118572
3 -6.9286586 -14.5207365
4 -3.9929705 -6.9286586
5 -2.4610415 -3.9929705
6 3.5590082 -2.4610415
7 2.5737316 3.5590082
8 1.3027671 2.5737316
9 -9.1893605 1.3027671
10 -5.9508357 -9.1893605
11 -6.0677932 -5.9508357
12 -3.2894174 -6.0677932
13 0.9432209 -3.2894174
14 2.5360153 0.9432209
15 4.4102281 2.5360153
16 8.9243912 4.4102281
17 4.0737316 8.9243912
18 7.1750011 4.0737316
19 -0.8227152 7.1750011
20 -2.1025094 -0.8227152
21 -12.0410838 -2.1025094
22 -4.8698712 -12.0410838
23 -8.3353534 -4.8698712
24 -6.0736797 -8.3353534
25 -1.2533251 -6.0736797
26 1.2946962 -1.2533251
27 2.5962707 1.2946962
28 10.2754054 2.5962707
29 10.9803842 10.2754054
30 15.9729728 10.9803842
31 19.9253061 15.9729728
32 9.7922637 19.9253061
33 -7.8243320 9.7922637
34 1.1133274 -7.8243320
35 -4.9241335 1.1133274
36 -1.2614457 -4.9241335
37 2.9550508 -1.2614457
38 -2.1894101 2.9550508
39 1.8991147 -2.1894101
40 8.2672352 1.8991147
41 2.0260226 8.2672352
42 13.5029728 2.0260226
43 11.4642423 13.5029728
44 3.9347035 11.4642423
45 -5.6100696 3.9347035
46 -7.1239278 -5.6100696
47 -10.4136724 -7.1239278
48 -7.3747435 -10.4136724
49 -0.2530202 -7.3747435
50 -0.4851973 -0.2530202
51 5.8726182 -0.4851973
52 10.8297246 5.8726182
53 7.4985616 10.8297246
54 6.9240366 7.4985616
55 2.0357672 6.9240366
56 -3.3830625 2.0357672
57 -4.9545874 -3.3830625
58 -4.5824029 -4.9545874
59 -7.2827079 -4.5824029
60 NA -7.2827079
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -13.4118572 -15.6848500
[2,] -14.5207365 -13.4118572
[3,] -6.9286586 -14.5207365
[4,] -3.9929705 -6.9286586
[5,] -2.4610415 -3.9929705
[6,] 3.5590082 -2.4610415
[7,] 2.5737316 3.5590082
[8,] 1.3027671 2.5737316
[9,] -9.1893605 1.3027671
[10,] -5.9508357 -9.1893605
[11,] -6.0677932 -5.9508357
[12,] -3.2894174 -6.0677932
[13,] 0.9432209 -3.2894174
[14,] 2.5360153 0.9432209
[15,] 4.4102281 2.5360153
[16,] 8.9243912 4.4102281
[17,] 4.0737316 8.9243912
[18,] 7.1750011 4.0737316
[19,] -0.8227152 7.1750011
[20,] -2.1025094 -0.8227152
[21,] -12.0410838 -2.1025094
[22,] -4.8698712 -12.0410838
[23,] -8.3353534 -4.8698712
[24,] -6.0736797 -8.3353534
[25,] -1.2533251 -6.0736797
[26,] 1.2946962 -1.2533251
[27,] 2.5962707 1.2946962
[28,] 10.2754054 2.5962707
[29,] 10.9803842 10.2754054
[30,] 15.9729728 10.9803842
[31,] 19.9253061 15.9729728
[32,] 9.7922637 19.9253061
[33,] -7.8243320 9.7922637
[34,] 1.1133274 -7.8243320
[35,] -4.9241335 1.1133274
[36,] -1.2614457 -4.9241335
[37,] 2.9550508 -1.2614457
[38,] -2.1894101 2.9550508
[39,] 1.8991147 -2.1894101
[40,] 8.2672352 1.8991147
[41,] 2.0260226 8.2672352
[42,] 13.5029728 2.0260226
[43,] 11.4642423 13.5029728
[44,] 3.9347035 11.4642423
[45,] -5.6100696 3.9347035
[46,] -7.1239278 -5.6100696
[47,] -10.4136724 -7.1239278
[48,] -7.3747435 -10.4136724
[49,] -0.2530202 -7.3747435
[50,] -0.4851973 -0.2530202
[51,] 5.8726182 -0.4851973
[52,] 10.8297246 5.8726182
[53,] 7.4985616 10.8297246
[54,] 6.9240366 7.4985616
[55,] 2.0357672 6.9240366
[56,] -3.3830625 2.0357672
[57,] -4.9545874 -3.3830625
[58,] -4.5824029 -4.9545874
[59,] -7.2827079 -4.5824029
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -13.4118572 -15.6848500
2 -14.5207365 -13.4118572
3 -6.9286586 -14.5207365
4 -3.9929705 -6.9286586
5 -2.4610415 -3.9929705
6 3.5590082 -2.4610415
7 2.5737316 3.5590082
8 1.3027671 2.5737316
9 -9.1893605 1.3027671
10 -5.9508357 -9.1893605
11 -6.0677932 -5.9508357
12 -3.2894174 -6.0677932
13 0.9432209 -3.2894174
14 2.5360153 0.9432209
15 4.4102281 2.5360153
16 8.9243912 4.4102281
17 4.0737316 8.9243912
18 7.1750011 4.0737316
19 -0.8227152 7.1750011
20 -2.1025094 -0.8227152
21 -12.0410838 -2.1025094
22 -4.8698712 -12.0410838
23 -8.3353534 -4.8698712
24 -6.0736797 -8.3353534
25 -1.2533251 -6.0736797
26 1.2946962 -1.2533251
27 2.5962707 1.2946962
28 10.2754054 2.5962707
29 10.9803842 10.2754054
30 15.9729728 10.9803842
31 19.9253061 15.9729728
32 9.7922637 19.9253061
33 -7.8243320 9.7922637
34 1.1133274 -7.8243320
35 -4.9241335 1.1133274
36 -1.2614457 -4.9241335
37 2.9550508 -1.2614457
38 -2.1894101 2.9550508
39 1.8991147 -2.1894101
40 8.2672352 1.8991147
41 2.0260226 8.2672352
42 13.5029728 2.0260226
43 11.4642423 13.5029728
44 3.9347035 11.4642423
45 -5.6100696 3.9347035
46 -7.1239278 -5.6100696
47 -10.4136724 -7.1239278
48 -7.3747435 -10.4136724
49 -0.2530202 -7.3747435
50 -0.4851973 -0.2530202
51 5.8726182 -0.4851973
52 10.8297246 5.8726182
53 7.4985616 10.8297246
54 6.9240366 7.4985616
55 2.0357672 6.9240366
56 -3.3830625 2.0357672
57 -4.9545874 -3.3830625
58 -4.5824029 -4.9545874
59 -7.2827079 -4.5824029
> 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/7qbat1258761893.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8vwuo1258761893.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9yr0l1258761893.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10dga81258761893.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11pw381258761893.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/12f19t1258761893.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/13hrwv1258761893.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/14uzwy1258761893.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/15ojf81258761893.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/16z6q71258761893.tab")
+ }
>
> system("convert tmp/1gxwu1258761893.ps tmp/1gxwu1258761893.png")
> system("convert tmp/20e2r1258761893.ps tmp/20e2r1258761893.png")
> system("convert tmp/3kn7d1258761893.ps tmp/3kn7d1258761893.png")
> system("convert tmp/4dvgv1258761893.ps tmp/4dvgv1258761893.png")
> system("convert tmp/5fpyf1258761893.ps tmp/5fpyf1258761893.png")
> system("convert tmp/6hf3b1258761893.ps tmp/6hf3b1258761893.png")
> system("convert tmp/7qbat1258761893.ps tmp/7qbat1258761893.png")
> system("convert tmp/8vwuo1258761893.ps tmp/8vwuo1258761893.png")
> system("convert tmp/9yr0l1258761893.ps tmp/9yr0l1258761893.png")
> system("convert tmp/10dga81258761893.ps tmp/10dga81258761893.png")
>
>
> proc.time()
user system elapsed
2.498 1.588 3.376