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 'license()' or 'licence()' for distribution details.
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Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
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> x <- array(list(325412,285351,326011,286602,328282,283042,317480,276687,317539,277915,313737,277128,312276,277103,309391,275037,302950,270150,300316,267140,304035,264993,333476,287259,337698,291186,335932,292300,323931,288186,313927,281477,314485,282656,313218,280190,309664,280408,302963,276836,298989,275216,298423,274352,310631,271311,329765,289802,335083,290726,327616,292300,309119,278506,295916,269826,291413,265861,291542,269034,284678,264176,276475,255198,272566,253353,264981,246057,263290,235372,296806,258556,303598,260993,286994,254663,276427,250643,266424,243422,267153,247105,268381,248541,262522,245039,255542,237080,253158,237085,243803,225554,250741,226839,280445,247934,285257,248333,270976,246969,261076,245098,255603,246263,260376,255765,263903,264319,264291,268347,263276,273046,262572,273963,256167,267430,264221,271993,293860,292710,300713,295881,287224,293299),dim=c(2,62),dimnames=list(c('Werkl_vrouwen','Werkl_mannen'),1:62))
> y <- array(NA,dim=c(2,62),dimnames=list(c('Werkl_vrouwen','Werkl_mannen'),1:62))
> 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
Werkl_vrouwen Werkl_mannen
1 325412 285351
2 326011 286602
3 328282 283042
4 317480 276687
5 317539 277915
6 313737 277128
7 312276 277103
8 309391 275037
9 302950 270150
10 300316 267140
11 304035 264993
12 333476 287259
13 337698 291186
14 335932 292300
15 323931 288186
16 313927 281477
17 314485 282656
18 313218 280190
19 309664 280408
20 302963 276836
21 298989 275216
22 298423 274352
23 310631 271311
24 329765 289802
25 335083 290726
26 327616 292300
27 309119 278506
28 295916 269826
29 291413 265861
30 291542 269034
31 284678 264176
32 276475 255198
33 272566 253353
34 264981 246057
35 263290 235372
36 296806 258556
37 303598 260993
38 286994 254663
39 276427 250643
40 266424 243422
41 267153 247105
42 268381 248541
43 262522 245039
44 255542 237080
45 253158 237085
46 243803 225554
47 250741 226839
48 280445 247934
49 285257 248333
50 270976 246969
51 261076 245098
52 255603 246263
53 260376 255765
54 263903 264319
55 264291 268347
56 263276 273046
57 262572 273963
58 256167 267430
59 264221 271993
60 293860 292710
61 300713 295881
62 287224 293299
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Werkl_mannen
-21931.289 1.175
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-37352 -3007 3311 10849 18911
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -21931.289 28910.696 -0.759 0.451
Werkl_mannen 1.175 0.108 10.878 8.02e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 15320 on 60 degrees of freedom
Multiple R-squared: 0.6636, Adjusted R-squared: 0.6579
F-statistic: 118.3 on 1 and 60 DF, p-value: 8.02e-16
> 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,] 8.118278e-03 1.623656e-02 0.99188172
[2,] 2.840417e-03 5.680834e-03 0.99715958
[3,] 1.064315e-03 2.128630e-03 0.99893569
[4,] 2.997808e-04 5.995616e-04 0.99970022
[5,] 6.012656e-05 1.202531e-04 0.99993987
[6,] 1.074675e-05 2.149350e-05 0.99998925
[7,] 1.377651e-05 2.755302e-05 0.99998622
[8,] 7.593187e-06 1.518637e-05 0.99999241
[9,] 2.432359e-06 4.864718e-06 0.99999757
[10,] 6.920007e-07 1.384001e-06 0.99999931
[11,] 1.171592e-06 2.343185e-06 0.99999883
[12,] 1.572183e-06 3.144365e-06 0.99999843
[13,] 2.166682e-06 4.333365e-06 0.99999783
[14,] 1.327340e-06 2.654680e-06 0.99999867
[15,] 2.135659e-06 4.271318e-06 0.99999786
[16,] 4.287184e-06 8.574368e-06 0.99999571
[17,] 8.994997e-06 1.798999e-05 0.99999101
[18,] 1.073292e-05 2.146584e-05 0.99998927
[19,] 1.068811e-05 2.137622e-05 0.99998931
[20,] 8.496072e-06 1.699214e-05 0.99999150
[21,] 1.625792e-05 3.251584e-05 0.99998374
[22,] 3.703682e-05 7.407364e-05 0.99996296
[23,] 4.931712e-05 9.863424e-05 0.99995068
[24,] 4.807949e-05 9.615898e-05 0.99995192
[25,] 3.670973e-05 7.341946e-05 0.99996329
[26,] 4.435764e-05 8.871527e-05 0.99995564
[27,] 3.685911e-05 7.371822e-05 0.99996314
[28,] 1.741856e-05 3.483712e-05 0.99998258
[29,] 7.621667e-06 1.524333e-05 0.99999238
[30,] 3.299157e-06 6.598315e-06 0.99999670
[31,] 1.089142e-05 2.178283e-05 0.99998911
[32,] 8.469528e-05 1.693906e-04 0.99991530
[33,] 3.083318e-03 6.166636e-03 0.99691668
[34,] 7.000530e-03 1.400106e-02 0.99299947
[35,] 6.624672e-03 1.324934e-02 0.99337533
[36,] 4.359160e-03 8.718319e-03 0.99564084
[37,] 2.957231e-03 5.914462e-03 0.99704277
[38,] 2.078846e-03 4.157692e-03 0.99792115
[39,] 1.294898e-03 2.589795e-03 0.99870510
[40,] 6.660691e-04 1.332138e-03 0.99933393
[41,] 3.569646e-04 7.139291e-04 0.99964304
[42,] 2.411650e-04 4.823300e-04 0.99975883
[43,] 1.691461e-04 3.382923e-04 0.99983085
[44,] 6.485260e-04 1.297052e-03 0.99935147
[45,] 3.041727e-02 6.083453e-02 0.96958273
[46,] 1.114301e-01 2.228602e-01 0.88856988
[47,] 2.373367e-01 4.746734e-01 0.76266328
[48,] 4.626562e-01 9.253123e-01 0.53734383
[49,] 8.147770e-01 3.704460e-01 0.18522298
[50,] 9.543230e-01 9.135402e-02 0.04567701
[51,] 9.817023e-01 3.659537e-02 0.01829769
[52,] 9.696860e-01 6.062803e-02 0.03031402
[53,] 9.463645e-01 1.072711e-01 0.05363553
> postscript(file="/var/www/html/rcomp/tmp/1j4zi1258480834.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2q8h81258480834.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3dhrr1258480834.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ive21258480834.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5cv871258480834.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 = 62
Frequency = 1
1 2 3 4 5 6
12108.9056 11238.2131 17691.5514 14355.4951 12971.8234 10094.4021
7 8 9 10 11 12
8662.7724 8204.9384 7505.2550 8407.4455 14648.7714 17931.3602
13 14 15 16 17 18
17539.8652 14465.1223 7297.3076 5175.1355 4348.0296 5978.1212
19 20 21 22 23 24
2168.0118 -336.5522 -2407.3533 -1958.3139 13822.2958 11232.8079
25 26 27 28 29 30
15465.2797 6149.1223 3857.5082 851.8948 1007.0328 -2591.6524
31 32 33 34 35 36
-3748.4054 -1403.9243 -3145.3922 -2158.9484 8702.9404 14982.0499
37 38 39 40 41 42
18911.0279 9743.6013 3899.3540 2379.6868 -1218.1536 -1677.1867
43 44 45 46 47 48
-3421.9876 -1051.6421 -3441.5161 750.2655 6178.6293 11099.9255
49 50 51 52 53 54
15443.1746 2764.6211 -4937.3017 -11778.9601 -18169.0439 -24691.4039
55 56 57 58 59 60
-29035.5551 -35571.0067 -37352.3112 -36082.2506 -33388.9274 -28088.5515
61 62
-24960.8871 -35416.5170
> postscript(file="/var/www/html/rcomp/tmp/698q61258480834.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 = 62
Frequency = 1
lag(myerror, k = 1) myerror
0 12108.9056 NA
1 11238.2131 12108.9056
2 17691.5514 11238.2131
3 14355.4951 17691.5514
4 12971.8234 14355.4951
5 10094.4021 12971.8234
6 8662.7724 10094.4021
7 8204.9384 8662.7724
8 7505.2550 8204.9384
9 8407.4455 7505.2550
10 14648.7714 8407.4455
11 17931.3602 14648.7714
12 17539.8652 17931.3602
13 14465.1223 17539.8652
14 7297.3076 14465.1223
15 5175.1355 7297.3076
16 4348.0296 5175.1355
17 5978.1212 4348.0296
18 2168.0118 5978.1212
19 -336.5522 2168.0118
20 -2407.3533 -336.5522
21 -1958.3139 -2407.3533
22 13822.2958 -1958.3139
23 11232.8079 13822.2958
24 15465.2797 11232.8079
25 6149.1223 15465.2797
26 3857.5082 6149.1223
27 851.8948 3857.5082
28 1007.0328 851.8948
29 -2591.6524 1007.0328
30 -3748.4054 -2591.6524
31 -1403.9243 -3748.4054
32 -3145.3922 -1403.9243
33 -2158.9484 -3145.3922
34 8702.9404 -2158.9484
35 14982.0499 8702.9404
36 18911.0279 14982.0499
37 9743.6013 18911.0279
38 3899.3540 9743.6013
39 2379.6868 3899.3540
40 -1218.1536 2379.6868
41 -1677.1867 -1218.1536
42 -3421.9876 -1677.1867
43 -1051.6421 -3421.9876
44 -3441.5161 -1051.6421
45 750.2655 -3441.5161
46 6178.6293 750.2655
47 11099.9255 6178.6293
48 15443.1746 11099.9255
49 2764.6211 15443.1746
50 -4937.3017 2764.6211
51 -11778.9601 -4937.3017
52 -18169.0439 -11778.9601
53 -24691.4039 -18169.0439
54 -29035.5551 -24691.4039
55 -35571.0067 -29035.5551
56 -37352.3112 -35571.0067
57 -36082.2506 -37352.3112
58 -33388.9274 -36082.2506
59 -28088.5515 -33388.9274
60 -24960.8871 -28088.5515
61 -35416.5170 -24960.8871
62 NA -35416.5170
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 11238.2131 12108.9056
[2,] 17691.5514 11238.2131
[3,] 14355.4951 17691.5514
[4,] 12971.8234 14355.4951
[5,] 10094.4021 12971.8234
[6,] 8662.7724 10094.4021
[7,] 8204.9384 8662.7724
[8,] 7505.2550 8204.9384
[9,] 8407.4455 7505.2550
[10,] 14648.7714 8407.4455
[11,] 17931.3602 14648.7714
[12,] 17539.8652 17931.3602
[13,] 14465.1223 17539.8652
[14,] 7297.3076 14465.1223
[15,] 5175.1355 7297.3076
[16,] 4348.0296 5175.1355
[17,] 5978.1212 4348.0296
[18,] 2168.0118 5978.1212
[19,] -336.5522 2168.0118
[20,] -2407.3533 -336.5522
[21,] -1958.3139 -2407.3533
[22,] 13822.2958 -1958.3139
[23,] 11232.8079 13822.2958
[24,] 15465.2797 11232.8079
[25,] 6149.1223 15465.2797
[26,] 3857.5082 6149.1223
[27,] 851.8948 3857.5082
[28,] 1007.0328 851.8948
[29,] -2591.6524 1007.0328
[30,] -3748.4054 -2591.6524
[31,] -1403.9243 -3748.4054
[32,] -3145.3922 -1403.9243
[33,] -2158.9484 -3145.3922
[34,] 8702.9404 -2158.9484
[35,] 14982.0499 8702.9404
[36,] 18911.0279 14982.0499
[37,] 9743.6013 18911.0279
[38,] 3899.3540 9743.6013
[39,] 2379.6868 3899.3540
[40,] -1218.1536 2379.6868
[41,] -1677.1867 -1218.1536
[42,] -3421.9876 -1677.1867
[43,] -1051.6421 -3421.9876
[44,] -3441.5161 -1051.6421
[45,] 750.2655 -3441.5161
[46,] 6178.6293 750.2655
[47,] 11099.9255 6178.6293
[48,] 15443.1746 11099.9255
[49,] 2764.6211 15443.1746
[50,] -4937.3017 2764.6211
[51,] -11778.9601 -4937.3017
[52,] -18169.0439 -11778.9601
[53,] -24691.4039 -18169.0439
[54,] -29035.5551 -24691.4039
[55,] -35571.0067 -29035.5551
[56,] -37352.3112 -35571.0067
[57,] -36082.2506 -37352.3112
[58,] -33388.9274 -36082.2506
[59,] -28088.5515 -33388.9274
[60,] -24960.8871 -28088.5515
[61,] -35416.5170 -24960.8871
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 11238.2131 12108.9056
2 17691.5514 11238.2131
3 14355.4951 17691.5514
4 12971.8234 14355.4951
5 10094.4021 12971.8234
6 8662.7724 10094.4021
7 8204.9384 8662.7724
8 7505.2550 8204.9384
9 8407.4455 7505.2550
10 14648.7714 8407.4455
11 17931.3602 14648.7714
12 17539.8652 17931.3602
13 14465.1223 17539.8652
14 7297.3076 14465.1223
15 5175.1355 7297.3076
16 4348.0296 5175.1355
17 5978.1212 4348.0296
18 2168.0118 5978.1212
19 -336.5522 2168.0118
20 -2407.3533 -336.5522
21 -1958.3139 -2407.3533
22 13822.2958 -1958.3139
23 11232.8079 13822.2958
24 15465.2797 11232.8079
25 6149.1223 15465.2797
26 3857.5082 6149.1223
27 851.8948 3857.5082
28 1007.0328 851.8948
29 -2591.6524 1007.0328
30 -3748.4054 -2591.6524
31 -1403.9243 -3748.4054
32 -3145.3922 -1403.9243
33 -2158.9484 -3145.3922
34 8702.9404 -2158.9484
35 14982.0499 8702.9404
36 18911.0279 14982.0499
37 9743.6013 18911.0279
38 3899.3540 9743.6013
39 2379.6868 3899.3540
40 -1218.1536 2379.6868
41 -1677.1867 -1218.1536
42 -3421.9876 -1677.1867
43 -1051.6421 -3421.9876
44 -3441.5161 -1051.6421
45 750.2655 -3441.5161
46 6178.6293 750.2655
47 11099.9255 6178.6293
48 15443.1746 11099.9255
49 2764.6211 15443.1746
50 -4937.3017 2764.6211
51 -11778.9601 -4937.3017
52 -18169.0439 -11778.9601
53 -24691.4039 -18169.0439
54 -29035.5551 -24691.4039
55 -35571.0067 -29035.5551
56 -37352.3112 -35571.0067
57 -36082.2506 -37352.3112
58 -33388.9274 -36082.2506
59 -28088.5515 -33388.9274
60 -24960.8871 -28088.5515
61 -35416.5170 -24960.8871
> 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/7a2tm1258480834.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8h6b31258480834.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9zqxf1258480834.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10k2731258480834.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11fuha1258480834.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/121ikx1258480834.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/1319pb1258480834.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/14r1kg1258480834.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/15xtuy1258480834.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/16nbsi1258480834.tab")
+ }
>
> system("convert tmp/1j4zi1258480834.ps tmp/1j4zi1258480834.png")
> system("convert tmp/2q8h81258480834.ps tmp/2q8h81258480834.png")
> system("convert tmp/3dhrr1258480834.ps tmp/3dhrr1258480834.png")
> system("convert tmp/4ive21258480834.ps tmp/4ive21258480834.png")
> system("convert tmp/5cv871258480834.ps tmp/5cv871258480834.png")
> system("convert tmp/698q61258480834.ps tmp/698q61258480834.png")
> system("convert tmp/7a2tm1258480834.ps tmp/7a2tm1258480834.png")
> system("convert tmp/8h6b31258480834.ps tmp/8h6b31258480834.png")
> system("convert tmp/9zqxf1258480834.ps tmp/9zqxf1258480834.png")
> system("convert tmp/10k2731258480834.ps tmp/10k2731258480834.png")
>
>
> proc.time()
user system elapsed
2.516 1.575 3.524