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.
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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(95.1,117.1,97,118.7,112.7,126.5,102.9,127.5,97.4,134.6,111.4,131.8,87.4,135.9,96.8,142.7,114.1,141.7,110.3,153.4,103.9,145,101.6,137.7,94.6,148.3,95.9,152.2,104.7,169.4,102.8,168.6,98.1,161.1,113.9,174.1,80.9,179,95.7,190.6,113.2,190,105.9,181.6,108.8,174.8,102.3,180.5,99,196.8,100.7,193.8,115.5,197,100.7,216.3,109.9,221.4,114.6,217.9,85.4,229.7,100.5,227.4,114.8,204.2,116.5,196.6,112.9,198.8,102,207.5,106,190.7,105.3,201.6,118.8,210.5,106.1,223.5,109.3,223.8,117.2,231.2,92.5,244,104.2,234.7,112.5,250.2,122.4,265.7,113.3,287.6,100,283.3,110.7,295.4,112.8,312.3,109.8,333.8,117.3,347.7,109.1,383.2,115.9,407.1,96,413.6,99.8,362.7,116.8,321.9,115.7,239.4,99.4,191,94.3,159.7,91,163.4),dim=c(2,61),dimnames=list(c('tot.ind.prod.index','prijsindex.grondst.incl.energie'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('tot.ind.prod.index','prijsindex.grondst.incl.energie'),1:61))
> 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
tot.ind.prod.index prijsindex.grondst.incl.energie
1 95.1 117.1
2 97.0 118.7
3 112.7 126.5
4 102.9 127.5
5 97.4 134.6
6 111.4 131.8
7 87.4 135.9
8 96.8 142.7
9 114.1 141.7
10 110.3 153.4
11 103.9 145.0
12 101.6 137.7
13 94.6 148.3
14 95.9 152.2
15 104.7 169.4
16 102.8 168.6
17 98.1 161.1
18 113.9 174.1
19 80.9 179.0
20 95.7 190.6
21 113.2 190.0
22 105.9 181.6
23 108.8 174.8
24 102.3 180.5
25 99.0 196.8
26 100.7 193.8
27 115.5 197.0
28 100.7 216.3
29 109.9 221.4
30 114.6 217.9
31 85.4 229.7
32 100.5 227.4
33 114.8 204.2
34 116.5 196.6
35 112.9 198.8
36 102.0 207.5
37 106.0 190.7
38 105.3 201.6
39 118.8 210.5
40 106.1 223.5
41 109.3 223.8
42 117.2 231.2
43 92.5 244.0
44 104.2 234.7
45 112.5 250.2
46 122.4 265.7
47 113.3 287.6
48 100.0 283.3
49 110.7 295.4
50 112.8 312.3
51 109.8 333.8
52 117.3 347.7
53 109.1 383.2
54 115.9 407.1
55 96.0 413.6
56 99.8 362.7
57 116.8 321.9
58 115.7 239.4
59 99.4 191.0
60 94.3 159.7
61 91.0 163.4
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) prijsindex.grondst.incl.energie
97.06515 0.03818
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-22.9994 -5.2473 0.5378 7.3780 15.1904
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 97.06515 3.50988 27.66 <2e-16 ***
prijsindex.grondst.incl.energie 0.03818 0.01564 2.44 0.0177 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 8.759 on 59 degrees of freedom
Multiple R-squared: 0.09169, Adjusted R-squared: 0.0763
F-statistic: 5.956 on 1 and 59 DF, p-value: 0.01769
> 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,] 0.4885204 0.9770408 0.5114796
[2,] 0.4284589 0.8569178 0.5715411
[3,] 0.7155703 0.5688594 0.2844297
[4,] 0.6092867 0.7814265 0.3907133
[5,] 0.7026633 0.5946735 0.2973367
[6,] 0.6252079 0.7495843 0.3747921
[7,] 0.5216073 0.9567854 0.4783927
[8,] 0.4211908 0.8423816 0.5788092
[9,] 0.4401103 0.8802206 0.5598897
[10,] 0.4084542 0.8169085 0.5915458
[11,] 0.3212802 0.6425603 0.6787198
[12,] 0.2441190 0.4882381 0.7558810
[13,] 0.1983372 0.3966743 0.8016628
[14,] 0.2162736 0.4325471 0.7837264
[15,] 0.6464238 0.7071523 0.3535762
[16,] 0.6094202 0.7811596 0.3905798
[17,] 0.6542419 0.6915163 0.3457581
[18,] 0.5876542 0.8246917 0.4123458
[19,] 0.5390670 0.9218659 0.4609330
[20,] 0.4645228 0.9290457 0.5354772
[21,] 0.4153264 0.8306529 0.5846736
[22,] 0.3543912 0.7087823 0.6456088
[23,] 0.3970083 0.7940166 0.6029917
[24,] 0.3454354 0.6908707 0.6545646
[25,] 0.2938500 0.5877001 0.7061500
[26,] 0.2881895 0.5763790 0.7118105
[27,] 0.6121333 0.7757335 0.3878667
[28,] 0.5670736 0.8658528 0.4329264
[29,] 0.5807642 0.8384717 0.4192358
[30,] 0.6267399 0.7465201 0.3732601
[31,] 0.6085361 0.7829278 0.3914639
[32,] 0.5442587 0.9114826 0.4557413
[33,] 0.4681841 0.9363682 0.5318159
[34,] 0.3916736 0.7833472 0.6083264
[35,] 0.4829372 0.9658745 0.5170628
[36,] 0.4043061 0.8086122 0.5956939
[37,] 0.3403214 0.6806427 0.6596786
[38,] 0.3877174 0.7754347 0.6122826
[39,] 0.4953679 0.9907357 0.5046321
[40,] 0.4136000 0.8272000 0.5864000
[41,] 0.3678507 0.7357014 0.6321493
[42,] 0.5547321 0.8905357 0.4452679
[43,] 0.5142101 0.9715798 0.4857899
[44,] 0.4777619 0.9555237 0.5222381
[45,] 0.3991287 0.7982574 0.6008713
[46,] 0.3382229 0.6764457 0.6617771
[47,] 0.2540367 0.5080735 0.7459633
[48,] 0.2528873 0.5057745 0.7471127
[49,] 0.1749356 0.3498711 0.8250644
[50,] 0.1503188 0.3006375 0.8496812
[51,] 0.2490779 0.4981557 0.7509221
[52,] 0.7223288 0.5553424 0.2776712
> postscript(file="/var/www/html/rcomp/tmp/1e3qm1258643623.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2ckcf1258643623.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3vpk91258643623.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4mlvi1258643623.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/570cj1258643623.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 = 61
Frequency = 1
1 2 3 4 5
-6.436027343 -4.597115347 10.805080634 0.966900632 -4.804177385
6 7 8 9 10
9.302726621 -14.853811388 -5.713435405 11.624744598 7.378038569
11 12 13 14 15
1.298750590 -0.722535393 -8.127243418 -6.976145428 1.167158531
16 17 18 19 20
-0.702297467 -5.115947449 10.187712519 -22.999369493 -8.642257521
21 22 23 24 25
8.880650481 1.901362501 5.060986518 -1.656639496 -5.578973536
26 27 28 29 30
-3.764433528 10.913390464 -4.623483583 4.381798405 9.215428413
31 32 33 34 35
-20.435095615 -5.247281610 9.938494447 11.928662465 8.244666460
36 37 38 39 40
-2.987499561 1.653924479 0.537762453 13.697960431 0.501620400
41 42 43 44 45
3.690166399 11.307634381 -13.881069650 -1.825995627 5.882214335
46 47 48 49 50
15.190424298 5.254282245 -7.881543745 2.356478226 3.811236185
51 52 53 54 55
-0.009633867 6.959664100 -2.595725986 3.291771956 -16.856398059
56 57 58 59 60
-11.113035936 7.444708162 9.494558361 -4.957529522 -8.862495446
61
-12.303761455
> postscript(file="/var/www/html/rcomp/tmp/6vrex1258643623.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 = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 -6.436027343 NA
1 -4.597115347 -6.436027343
2 10.805080634 -4.597115347
3 0.966900632 10.805080634
4 -4.804177385 0.966900632
5 9.302726621 -4.804177385
6 -14.853811388 9.302726621
7 -5.713435405 -14.853811388
8 11.624744598 -5.713435405
9 7.378038569 11.624744598
10 1.298750590 7.378038569
11 -0.722535393 1.298750590
12 -8.127243418 -0.722535393
13 -6.976145428 -8.127243418
14 1.167158531 -6.976145428
15 -0.702297467 1.167158531
16 -5.115947449 -0.702297467
17 10.187712519 -5.115947449
18 -22.999369493 10.187712519
19 -8.642257521 -22.999369493
20 8.880650481 -8.642257521
21 1.901362501 8.880650481
22 5.060986518 1.901362501
23 -1.656639496 5.060986518
24 -5.578973536 -1.656639496
25 -3.764433528 -5.578973536
26 10.913390464 -3.764433528
27 -4.623483583 10.913390464
28 4.381798405 -4.623483583
29 9.215428413 4.381798405
30 -20.435095615 9.215428413
31 -5.247281610 -20.435095615
32 9.938494447 -5.247281610
33 11.928662465 9.938494447
34 8.244666460 11.928662465
35 -2.987499561 8.244666460
36 1.653924479 -2.987499561
37 0.537762453 1.653924479
38 13.697960431 0.537762453
39 0.501620400 13.697960431
40 3.690166399 0.501620400
41 11.307634381 3.690166399
42 -13.881069650 11.307634381
43 -1.825995627 -13.881069650
44 5.882214335 -1.825995627
45 15.190424298 5.882214335
46 5.254282245 15.190424298
47 -7.881543745 5.254282245
48 2.356478226 -7.881543745
49 3.811236185 2.356478226
50 -0.009633867 3.811236185
51 6.959664100 -0.009633867
52 -2.595725986 6.959664100
53 3.291771956 -2.595725986
54 -16.856398059 3.291771956
55 -11.113035936 -16.856398059
56 7.444708162 -11.113035936
57 9.494558361 7.444708162
58 -4.957529522 9.494558361
59 -8.862495446 -4.957529522
60 -12.303761455 -8.862495446
61 NA -12.303761455
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -4.597115347 -6.436027343
[2,] 10.805080634 -4.597115347
[3,] 0.966900632 10.805080634
[4,] -4.804177385 0.966900632
[5,] 9.302726621 -4.804177385
[6,] -14.853811388 9.302726621
[7,] -5.713435405 -14.853811388
[8,] 11.624744598 -5.713435405
[9,] 7.378038569 11.624744598
[10,] 1.298750590 7.378038569
[11,] -0.722535393 1.298750590
[12,] -8.127243418 -0.722535393
[13,] -6.976145428 -8.127243418
[14,] 1.167158531 -6.976145428
[15,] -0.702297467 1.167158531
[16,] -5.115947449 -0.702297467
[17,] 10.187712519 -5.115947449
[18,] -22.999369493 10.187712519
[19,] -8.642257521 -22.999369493
[20,] 8.880650481 -8.642257521
[21,] 1.901362501 8.880650481
[22,] 5.060986518 1.901362501
[23,] -1.656639496 5.060986518
[24,] -5.578973536 -1.656639496
[25,] -3.764433528 -5.578973536
[26,] 10.913390464 -3.764433528
[27,] -4.623483583 10.913390464
[28,] 4.381798405 -4.623483583
[29,] 9.215428413 4.381798405
[30,] -20.435095615 9.215428413
[31,] -5.247281610 -20.435095615
[32,] 9.938494447 -5.247281610
[33,] 11.928662465 9.938494447
[34,] 8.244666460 11.928662465
[35,] -2.987499561 8.244666460
[36,] 1.653924479 -2.987499561
[37,] 0.537762453 1.653924479
[38,] 13.697960431 0.537762453
[39,] 0.501620400 13.697960431
[40,] 3.690166399 0.501620400
[41,] 11.307634381 3.690166399
[42,] -13.881069650 11.307634381
[43,] -1.825995627 -13.881069650
[44,] 5.882214335 -1.825995627
[45,] 15.190424298 5.882214335
[46,] 5.254282245 15.190424298
[47,] -7.881543745 5.254282245
[48,] 2.356478226 -7.881543745
[49,] 3.811236185 2.356478226
[50,] -0.009633867 3.811236185
[51,] 6.959664100 -0.009633867
[52,] -2.595725986 6.959664100
[53,] 3.291771956 -2.595725986
[54,] -16.856398059 3.291771956
[55,] -11.113035936 -16.856398059
[56,] 7.444708162 -11.113035936
[57,] 9.494558361 7.444708162
[58,] -4.957529522 9.494558361
[59,] -8.862495446 -4.957529522
[60,] -12.303761455 -8.862495446
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -4.597115347 -6.436027343
2 10.805080634 -4.597115347
3 0.966900632 10.805080634
4 -4.804177385 0.966900632
5 9.302726621 -4.804177385
6 -14.853811388 9.302726621
7 -5.713435405 -14.853811388
8 11.624744598 -5.713435405
9 7.378038569 11.624744598
10 1.298750590 7.378038569
11 -0.722535393 1.298750590
12 -8.127243418 -0.722535393
13 -6.976145428 -8.127243418
14 1.167158531 -6.976145428
15 -0.702297467 1.167158531
16 -5.115947449 -0.702297467
17 10.187712519 -5.115947449
18 -22.999369493 10.187712519
19 -8.642257521 -22.999369493
20 8.880650481 -8.642257521
21 1.901362501 8.880650481
22 5.060986518 1.901362501
23 -1.656639496 5.060986518
24 -5.578973536 -1.656639496
25 -3.764433528 -5.578973536
26 10.913390464 -3.764433528
27 -4.623483583 10.913390464
28 4.381798405 -4.623483583
29 9.215428413 4.381798405
30 -20.435095615 9.215428413
31 -5.247281610 -20.435095615
32 9.938494447 -5.247281610
33 11.928662465 9.938494447
34 8.244666460 11.928662465
35 -2.987499561 8.244666460
36 1.653924479 -2.987499561
37 0.537762453 1.653924479
38 13.697960431 0.537762453
39 0.501620400 13.697960431
40 3.690166399 0.501620400
41 11.307634381 3.690166399
42 -13.881069650 11.307634381
43 -1.825995627 -13.881069650
44 5.882214335 -1.825995627
45 15.190424298 5.882214335
46 5.254282245 15.190424298
47 -7.881543745 5.254282245
48 2.356478226 -7.881543745
49 3.811236185 2.356478226
50 -0.009633867 3.811236185
51 6.959664100 -0.009633867
52 -2.595725986 6.959664100
53 3.291771956 -2.595725986
54 -16.856398059 3.291771956
55 -11.113035936 -16.856398059
56 7.444708162 -11.113035936
57 9.494558361 7.444708162
58 -4.957529522 9.494558361
59 -8.862495446 -4.957529522
60 -12.303761455 -8.862495446
> 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/7fcig1258643623.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/80plh1258643623.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9orli1258643623.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/101w841258643623.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11sedw1258643623.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/12kpfr1258643623.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/135qw91258643624.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/14ev311258643624.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/15ev651258643624.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/16eado1258643624.tab")
+ }
>
> system("convert tmp/1e3qm1258643623.ps tmp/1e3qm1258643623.png")
> system("convert tmp/2ckcf1258643623.ps tmp/2ckcf1258643623.png")
> system("convert tmp/3vpk91258643623.ps tmp/3vpk91258643623.png")
> system("convert tmp/4mlvi1258643623.ps tmp/4mlvi1258643623.png")
> system("convert tmp/570cj1258643623.ps tmp/570cj1258643623.png")
> system("convert tmp/6vrex1258643623.ps tmp/6vrex1258643623.png")
> system("convert tmp/7fcig1258643623.ps tmp/7fcig1258643623.png")
> system("convert tmp/80plh1258643623.ps tmp/80plh1258643623.png")
> system("convert tmp/9orli1258643623.ps tmp/9orli1258643623.png")
> system("convert tmp/101w841258643623.ps tmp/101w841258643623.png")
>
>
> proc.time()
user system elapsed
2.517 1.616 5.880