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(110.5,55,110.8,48.7,104.2,70.3,88.9,94.8,89.8,58.5,90,62.4,93.9,56.7,91.3,65.1,87.8,114.4,99.7,50.7,73.5,44.5,79.2,72,96.9,61.2,95.2,68.4,95.6,78.7,89.7,64.1,92.8,64.6,88,71.9,101.1,71,92.7,76.4,95.8,117.3,103.8,66.1,81.8,57.3,87.1,75,105.9,63.8,108.1,62.2,102.6,75.4,93.7,58,103.5,62.1,100.6,99.2,113.3,70.7,102.4,73.3,102.1,111.2,106.9,68.9,87.3,57.6,93.1,72.9,109.1,75.9,120.3,79.4,104.9,96.9,92.6,75.2,109.8,60.3,111.4,88.9,117.9,90.5,121.6,79.9,117.8,116.3,124.2,95.2,106.8,81.5,102.7,89.1,116.8,76,113.6,100.5,96.1,83.9,85,75.1,83.2,69.5,84.9,95.1,83,90.1,79.6,78.4,83.2,113.8,83.8,73.6,82.8,56.5,71.4,97.7),dim=c(2,60),dimnames=list(c('prod','inv
'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('prod','inv
'),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
prod inv\r
1 110.5 55.0
2 110.8 48.7
3 104.2 70.3
4 88.9 94.8
5 89.8 58.5
6 90.0 62.4
7 93.9 56.7
8 91.3 65.1
9 87.8 114.4
10 99.7 50.7
11 73.5 44.5
12 79.2 72.0
13 96.9 61.2
14 95.2 68.4
15 95.6 78.7
16 89.7 64.1
17 92.8 64.6
18 88.0 71.9
19 101.1 71.0
20 92.7 76.4
21 95.8 117.3
22 103.8 66.1
23 81.8 57.3
24 87.1 75.0
25 105.9 63.8
26 108.1 62.2
27 102.6 75.4
28 93.7 58.0
29 103.5 62.1
30 100.6 99.2
31 113.3 70.7
32 102.4 73.3
33 102.1 111.2
34 106.9 68.9
35 87.3 57.6
36 93.1 72.9
37 109.1 75.9
38 120.3 79.4
39 104.9 96.9
40 92.6 75.2
41 109.8 60.3
42 111.4 88.9
43 117.9 90.5
44 121.6 79.9
45 117.8 116.3
46 124.2 95.2
47 106.8 81.5
48 102.7 89.1
49 116.8 76.0
50 113.6 100.5
51 96.1 83.9
52 85.0 75.1
53 83.2 69.5
54 84.9 95.1
55 83.0 90.1
56 79.6 78.4
57 83.2 113.8
58 83.8 73.6
59 82.8 56.5
60 71.4 97.7
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `inv\r`
91.16251 0.08567
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-28.133 -9.588 -1.971 9.412 24.882
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 91.16251 7.27638 12.529 <2e-16 ***
`inv\r` 0.08567 0.09292 0.922 0.360
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 12.58 on 58 degrees of freedom
Multiple R-squared: 0.01444, Adjusted R-squared: -0.002549
F-statistic: 0.85 on 1 and 58 DF, p-value: 0.3604
> 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,] 0.343950064 0.687900129 0.656049936
[2,] 0.325143402 0.650286804 0.674856598
[3,] 0.244557097 0.489114194 0.755442903
[4,] 0.171337981 0.342675963 0.828662019
[5,] 0.115145102 0.230290205 0.884854898
[6,] 0.065310848 0.130621696 0.934689152
[7,] 0.366411723 0.732823446 0.633588277
[8,] 0.409031415 0.818062830 0.590968585
[9,] 0.317980564 0.635961129 0.682019436
[10,] 0.237307447 0.474614894 0.762692553
[11,] 0.174070878 0.348141756 0.825929122
[12,] 0.128783509 0.257567018 0.871216491
[13,] 0.087504643 0.175009286 0.912495357
[14,] 0.064488641 0.128977282 0.935511359
[15,] 0.050171007 0.100342013 0.949828993
[16,] 0.032150683 0.064301365 0.967849317
[17,] 0.023223600 0.046447199 0.976776400
[18,] 0.019508863 0.039017725 0.980491137
[19,] 0.023965966 0.047931932 0.976034034
[20,] 0.018740854 0.037481708 0.981259146
[21,] 0.018338130 0.036676261 0.981661870
[22,] 0.020507280 0.041014559 0.979492720
[23,] 0.015408241 0.030816482 0.984591759
[24,] 0.009405848 0.018811697 0.990594152
[25,] 0.006938975 0.013877950 0.993061025
[26,] 0.004651254 0.009302508 0.995348746
[27,] 0.008491102 0.016982204 0.991508898
[28,] 0.005678869 0.011357738 0.994321131
[29,] 0.003689846 0.007379691 0.996310154
[30,] 0.003170735 0.006341469 0.996829265
[31,] 0.002352879 0.004705757 0.997647121
[32,] 0.001345371 0.002690743 0.998654629
[33,] 0.001315647 0.002631295 0.998684353
[34,] 0.005235150 0.010470300 0.994764850
[35,] 0.003315802 0.006631605 0.996684198
[36,] 0.001945389 0.003890779 0.998054611
[37,] 0.002355980 0.004711960 0.997644020
[38,] 0.002346212 0.004692424 0.997653788
[39,] 0.004679101 0.009358202 0.995320899
[40,] 0.020410345 0.040820690 0.979589655
[41,] 0.024601621 0.049203242 0.975398379
[42,] 0.118197811 0.236395621 0.881802189
[43,] 0.129573723 0.259147446 0.870426277
[44,] 0.119676131 0.239352263 0.880323869
[45,] 0.458143278 0.916286556 0.541856722
[46,] 0.954321334 0.091357333 0.045678666
[47,] 0.992128539 0.015742922 0.007871461
[48,] 0.983747628 0.032504743 0.016252372
[49,] 0.961958915 0.076082169 0.038041085
[50,] 0.936155728 0.127688544 0.063844272
[51,] 0.868478211 0.263043578 0.131521789
> postscript(file="/var/www/html/rcomp/tmp/1bkey1258626008.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/293j41258626008.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3nj4q1258626008.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ldfw1258626008.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5fh4a1258626008.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
14.6255623 15.4652924 7.0147893 -10.3841609 -6.3742877 -6.5084063
7 8 9 10 11 12
-2.1200791 -5.4397192 -13.1633211 4.1939495 -21.4748876 -18.1308521
13 14 15 16 17 18
0.4943994 -1.8224349 -2.3048508 -6.9540478 -3.8968835 -9.3222850
19 20 21 22 23 24
3.8548193 -5.0078065 -5.4117683 6.9746094 -14.2714820 -10.4878664
25 26 27 28 29 30
9.2716537 11.6087280 4.9778650 -2.4314520 7.0172951 0.9388847
31 32 33 34 35 36
16.0805207 4.9577750 1.4108275 9.8347293 -8.7971834 -4.3079564
37 38 39 40 41 42
11.4350293 22.3351792 5.4359291 -5.0050007 13.4715037 12.6213006
43 44 45 46 47 48
18.9842263 23.5923435 16.6739031 24.8815705 8.6552692 3.9041663
49 50 51 52 53 54
19.1264621 13.8275119 -2.2503422 -12.5964336 -13.9166735 -14.4098624
55 56 57 58 59 60
-15.8815052 -18.2791493 -17.7119183 -13.6679264 -13.2029448 -28.1326081
> postscript(file="/var/www/html/rcomp/tmp/6cgj41258626008.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 14.6255623 NA
1 15.4652924 14.6255623
2 7.0147893 15.4652924
3 -10.3841609 7.0147893
4 -6.3742877 -10.3841609
5 -6.5084063 -6.3742877
6 -2.1200791 -6.5084063
7 -5.4397192 -2.1200791
8 -13.1633211 -5.4397192
9 4.1939495 -13.1633211
10 -21.4748876 4.1939495
11 -18.1308521 -21.4748876
12 0.4943994 -18.1308521
13 -1.8224349 0.4943994
14 -2.3048508 -1.8224349
15 -6.9540478 -2.3048508
16 -3.8968835 -6.9540478
17 -9.3222850 -3.8968835
18 3.8548193 -9.3222850
19 -5.0078065 3.8548193
20 -5.4117683 -5.0078065
21 6.9746094 -5.4117683
22 -14.2714820 6.9746094
23 -10.4878664 -14.2714820
24 9.2716537 -10.4878664
25 11.6087280 9.2716537
26 4.9778650 11.6087280
27 -2.4314520 4.9778650
28 7.0172951 -2.4314520
29 0.9388847 7.0172951
30 16.0805207 0.9388847
31 4.9577750 16.0805207
32 1.4108275 4.9577750
33 9.8347293 1.4108275
34 -8.7971834 9.8347293
35 -4.3079564 -8.7971834
36 11.4350293 -4.3079564
37 22.3351792 11.4350293
38 5.4359291 22.3351792
39 -5.0050007 5.4359291
40 13.4715037 -5.0050007
41 12.6213006 13.4715037
42 18.9842263 12.6213006
43 23.5923435 18.9842263
44 16.6739031 23.5923435
45 24.8815705 16.6739031
46 8.6552692 24.8815705
47 3.9041663 8.6552692
48 19.1264621 3.9041663
49 13.8275119 19.1264621
50 -2.2503422 13.8275119
51 -12.5964336 -2.2503422
52 -13.9166735 -12.5964336
53 -14.4098624 -13.9166735
54 -15.8815052 -14.4098624
55 -18.2791493 -15.8815052
56 -17.7119183 -18.2791493
57 -13.6679264 -17.7119183
58 -13.2029448 -13.6679264
59 -28.1326081 -13.2029448
60 NA -28.1326081
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 15.4652924 14.6255623
[2,] 7.0147893 15.4652924
[3,] -10.3841609 7.0147893
[4,] -6.3742877 -10.3841609
[5,] -6.5084063 -6.3742877
[6,] -2.1200791 -6.5084063
[7,] -5.4397192 -2.1200791
[8,] -13.1633211 -5.4397192
[9,] 4.1939495 -13.1633211
[10,] -21.4748876 4.1939495
[11,] -18.1308521 -21.4748876
[12,] 0.4943994 -18.1308521
[13,] -1.8224349 0.4943994
[14,] -2.3048508 -1.8224349
[15,] -6.9540478 -2.3048508
[16,] -3.8968835 -6.9540478
[17,] -9.3222850 -3.8968835
[18,] 3.8548193 -9.3222850
[19,] -5.0078065 3.8548193
[20,] -5.4117683 -5.0078065
[21,] 6.9746094 -5.4117683
[22,] -14.2714820 6.9746094
[23,] -10.4878664 -14.2714820
[24,] 9.2716537 -10.4878664
[25,] 11.6087280 9.2716537
[26,] 4.9778650 11.6087280
[27,] -2.4314520 4.9778650
[28,] 7.0172951 -2.4314520
[29,] 0.9388847 7.0172951
[30,] 16.0805207 0.9388847
[31,] 4.9577750 16.0805207
[32,] 1.4108275 4.9577750
[33,] 9.8347293 1.4108275
[34,] -8.7971834 9.8347293
[35,] -4.3079564 -8.7971834
[36,] 11.4350293 -4.3079564
[37,] 22.3351792 11.4350293
[38,] 5.4359291 22.3351792
[39,] -5.0050007 5.4359291
[40,] 13.4715037 -5.0050007
[41,] 12.6213006 13.4715037
[42,] 18.9842263 12.6213006
[43,] 23.5923435 18.9842263
[44,] 16.6739031 23.5923435
[45,] 24.8815705 16.6739031
[46,] 8.6552692 24.8815705
[47,] 3.9041663 8.6552692
[48,] 19.1264621 3.9041663
[49,] 13.8275119 19.1264621
[50,] -2.2503422 13.8275119
[51,] -12.5964336 -2.2503422
[52,] -13.9166735 -12.5964336
[53,] -14.4098624 -13.9166735
[54,] -15.8815052 -14.4098624
[55,] -18.2791493 -15.8815052
[56,] -17.7119183 -18.2791493
[57,] -13.6679264 -17.7119183
[58,] -13.2029448 -13.6679264
[59,] -28.1326081 -13.2029448
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 15.4652924 14.6255623
2 7.0147893 15.4652924
3 -10.3841609 7.0147893
4 -6.3742877 -10.3841609
5 -6.5084063 -6.3742877
6 -2.1200791 -6.5084063
7 -5.4397192 -2.1200791
8 -13.1633211 -5.4397192
9 4.1939495 -13.1633211
10 -21.4748876 4.1939495
11 -18.1308521 -21.4748876
12 0.4943994 -18.1308521
13 -1.8224349 0.4943994
14 -2.3048508 -1.8224349
15 -6.9540478 -2.3048508
16 -3.8968835 -6.9540478
17 -9.3222850 -3.8968835
18 3.8548193 -9.3222850
19 -5.0078065 3.8548193
20 -5.4117683 -5.0078065
21 6.9746094 -5.4117683
22 -14.2714820 6.9746094
23 -10.4878664 -14.2714820
24 9.2716537 -10.4878664
25 11.6087280 9.2716537
26 4.9778650 11.6087280
27 -2.4314520 4.9778650
28 7.0172951 -2.4314520
29 0.9388847 7.0172951
30 16.0805207 0.9388847
31 4.9577750 16.0805207
32 1.4108275 4.9577750
33 9.8347293 1.4108275
34 -8.7971834 9.8347293
35 -4.3079564 -8.7971834
36 11.4350293 -4.3079564
37 22.3351792 11.4350293
38 5.4359291 22.3351792
39 -5.0050007 5.4359291
40 13.4715037 -5.0050007
41 12.6213006 13.4715037
42 18.9842263 12.6213006
43 23.5923435 18.9842263
44 16.6739031 23.5923435
45 24.8815705 16.6739031
46 8.6552692 24.8815705
47 3.9041663 8.6552692
48 19.1264621 3.9041663
49 13.8275119 19.1264621
50 -2.2503422 13.8275119
51 -12.5964336 -2.2503422
52 -13.9166735 -12.5964336
53 -14.4098624 -13.9166735
54 -15.8815052 -14.4098624
55 -18.2791493 -15.8815052
56 -17.7119183 -18.2791493
57 -13.6679264 -17.7119183
58 -13.2029448 -13.6679264
59 -28.1326081 -13.2029448
> 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/7qm4y1258626008.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8p8b51258626008.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9rro71258626008.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10txoz1258626008.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11z5lw1258626008.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/12oy0f1258626008.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/130fmb1258626008.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/14z4j71258626008.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/15v6et1258626008.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/163qtq1258626008.tab")
+ }
>
> system("convert tmp/1bkey1258626008.ps tmp/1bkey1258626008.png")
> system("convert tmp/293j41258626008.ps tmp/293j41258626008.png")
> system("convert tmp/3nj4q1258626008.ps tmp/3nj4q1258626008.png")
> system("convert tmp/4ldfw1258626008.ps tmp/4ldfw1258626008.png")
> system("convert tmp/5fh4a1258626008.ps tmp/5fh4a1258626008.png")
> system("convert tmp/6cgj41258626008.ps tmp/6cgj41258626008.png")
> system("convert tmp/7qm4y1258626008.ps tmp/7qm4y1258626008.png")
> system("convert tmp/8p8b51258626008.ps tmp/8p8b51258626008.png")
> system("convert tmp/9rro71258626008.ps tmp/9rro71258626008.png")
> system("convert tmp/10txoz1258626008.ps tmp/10txoz1258626008.png")
>
>
> proc.time()
user system elapsed
2.470 1.566 3.936