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(363,14.3,364,14.2,363,15.9,358,15.3,357,15.5,357,15.1,380,15,378,12.1,376,15.8,380,16.9,379,15.1,384,13.7,392,14.8,394,14.7,392,16,396,15.4,392,15,396,15.5,419,15.1,421,11.7,420,16.3,418,16.7,410,15,418,14.9,426,14.6,428,15.3,430,17.9,424,16.4,423,15.4,427,17.9,441,15.9,449,13.9,452,17.8,462,17.9,455,17.4,461,16.7,461,16,463,16.6,462,19.1,456,17.8,455,17.2,456,18.6,472,16.3,472,15.1,471,19.2,465,17.7,459,19.1,465,18,468,17.5,467,17.8,463,21.1,460,17.2,462,19.4,461,19.8,476,17.6,476,16.2,471,19.5,453,19.9,443,20,442,17.3),dim=c(2,60),dimnames=list(c('WK>25j','ExpBe'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('WK>25j','ExpBe'),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
WK>25j ExpBe
1 363 14.3
2 364 14.2
3 363 15.9
4 358 15.3
5 357 15.5
6 357 15.1
7 380 15.0
8 378 12.1
9 376 15.8
10 380 16.9
11 379 15.1
12 384 13.7
13 392 14.8
14 394 14.7
15 392 16.0
16 396 15.4
17 392 15.0
18 396 15.5
19 419 15.1
20 421 11.7
21 420 16.3
22 418 16.7
23 410 15.0
24 418 14.9
25 426 14.6
26 428 15.3
27 430 17.9
28 424 16.4
29 423 15.4
30 427 17.9
31 441 15.9
32 449 13.9
33 452 17.8
34 462 17.9
35 455 17.4
36 461 16.7
37 461 16.0
38 463 16.6
39 462 19.1
40 456 17.8
41 455 17.2
42 456 18.6
43 472 16.3
44 472 15.1
45 471 19.2
46 465 17.7
47 459 19.1
48 465 18.0
49 468 17.5
50 467 17.8
51 463 21.1
52 460 17.2
53 462 19.4
54 461 19.8
55 476 17.6
56 476 16.2
57 471 19.5
58 453 19.9
59 443 20.0
60 442 17.3
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) ExpBe
225.95 12.24
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-58.606 -18.075 2.403 19.228 61.288
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 225.948 33.117 6.823 5.81e-09 ***
ExpBe 12.236 1.991 6.144 7.87e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 29.62 on 58 degrees of freedom
Multiple R-squared: 0.3943, Adjusted R-squared: 0.3838
F-statistic: 37.75 on 1 and 58 DF, p-value: 7.87e-08
> 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,] 0.0025751305 5.150261e-03 9.974249e-01
[2,] 0.0006117708 1.223542e-03 9.993882e-01
[3,] 0.0128925028 2.578501e-02 9.871075e-01
[4,] 0.0042077317 8.415463e-03 9.957923e-01
[5,] 0.0061742676 1.234854e-02 9.938257e-01
[6,] 0.0120154654 2.403093e-02 9.879845e-01
[7,] 0.0109605291 2.192106e-02 9.890395e-01
[8,] 0.0109488658 2.189773e-02 9.890511e-01
[9,] 0.0232849933 4.656999e-02 9.767150e-01
[10,] 0.0408725043 8.174501e-02 9.591275e-01
[11,] 0.0716461498 1.432923e-01 9.283539e-01
[12,] 0.1182735331 2.365471e-01 8.817265e-01
[13,] 0.1647166314 3.294333e-01 8.352834e-01
[14,] 0.2652103224 5.304206e-01 7.347897e-01
[15,] 0.5534557430 8.930885e-01 4.465443e-01
[16,] 0.6604191767 6.791616e-01 3.395808e-01
[17,] 0.8404874163 3.190252e-01 1.595126e-01
[18,] 0.9238407487 1.523185e-01 7.615925e-02
[19,] 0.9576351676 8.472966e-02 4.236483e-02
[20,] 0.9787296058 4.254079e-02 2.127039e-02
[21,] 0.9898211788 2.035764e-02 1.017882e-02
[22,] 0.9957695434 8.460913e-03 4.230457e-03
[23,] 0.9985199502 2.960100e-03 1.480050e-03
[24,] 0.9996447312 7.105375e-04 3.552688e-04
[25,] 0.9999678491 6.430179e-05 3.215089e-05
[26,] 0.9999985122 2.975569e-06 1.487784e-06
[27,] 0.9999997927 4.145454e-07 2.072727e-07
[28,] 0.9999999764 4.713839e-08 2.356920e-08
[29,] 0.9999999814 3.716230e-08 1.858115e-08
[30,] 0.9999999728 5.445107e-08 2.722553e-08
[31,] 0.9999999630 7.392993e-08 3.696496e-08
[32,] 0.9999999432 1.136365e-07 5.681826e-08
[33,] 0.9999999241 1.517423e-07 7.587116e-08
[34,] 0.9999998525 2.950196e-07 1.475098e-07
[35,] 0.9999995193 9.614131e-07 4.807065e-07
[36,] 0.9999989131 2.173784e-06 1.086892e-06
[37,] 0.9999982333 3.533412e-06 1.766706e-06
[38,] 0.9999953103 9.379495e-06 4.689747e-06
[39,] 0.9999911657 1.766856e-05 8.834282e-06
[40,] 0.9999851828 2.963437e-05 1.481719e-05
[41,] 0.9999695774 6.084528e-05 3.042264e-05
[42,] 0.9999073137 1.853725e-04 9.268627e-05
[43,] 0.9997098440 5.803120e-04 2.901560e-04
[44,] 0.9991679142 1.664172e-03 8.320858e-04
[45,] 0.9978774426 4.245115e-03 2.122557e-03
[46,] 0.9946384377 1.072312e-02 5.361562e-03
[47,] 0.9887395512 2.252090e-02 1.126045e-02
[48,] 0.9739941016 5.201180e-02 2.600590e-02
[49,] 0.9401189940 1.197620e-01 5.988101e-02
[50,] 0.8747200522 2.505599e-01 1.252799e-01
[51,] 0.8055066752 3.889866e-01 1.944933e-01
> postscript(file="/var/www/html/rcomp/tmp/1s2aa1258731636.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2tl8g1258731636.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ijyz1258731636.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4k0xd1258731636.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5k9vo1258731636.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
-37.9231085 -35.6995070 -57.5007312 -55.1591227 -58.6063255 -53.7119198
7 8 9 10 11 12
-29.4883184 3.9961228 -43.2771298 -52.7367454 -31.7119198 -9.5814999
13 14 15 16 17 18
-15.0411156 -11.8175141 -29.7243326 -18.3827241 -17.4883184 -19.6063255
19 20 21 22 23 24
8.2880802 51.8905285 -5.3951369 -12.2895426 0.5116816 9.7352830
25 26 27 28 29 30
21.4060873 14.8408773 -14.9727596 -2.6187383 8.6172759 -17.9727596
31 32 33 34 35 36
20.4992688 52.9712972 8.2508418 17.0272404 16.1452475 30.7104574
37 38 39 40 41 42
39.2756674 33.9340588 2.3440233 12.2508418 18.5924503 2.4620304
43 44 45 46 47 48
46.6048631 61.2880802 10.1204219 22.4744432 -0.6559767 18.8036389
49 50 51 52 53 54
27.9216460 23.2508418 -21.1280052 23.5924503 -1.3267810 -7.2211867
55 56 57 58 59 60
34.6980446 51.8284645 6.4496176 -16.4447881 -27.6683895 4.3688489
> postscript(file="/var/www/html/rcomp/tmp/63nnh1258731636.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 -37.9231085 NA
1 -35.6995070 -37.9231085
2 -57.5007312 -35.6995070
3 -55.1591227 -57.5007312
4 -58.6063255 -55.1591227
5 -53.7119198 -58.6063255
6 -29.4883184 -53.7119198
7 3.9961228 -29.4883184
8 -43.2771298 3.9961228
9 -52.7367454 -43.2771298
10 -31.7119198 -52.7367454
11 -9.5814999 -31.7119198
12 -15.0411156 -9.5814999
13 -11.8175141 -15.0411156
14 -29.7243326 -11.8175141
15 -18.3827241 -29.7243326
16 -17.4883184 -18.3827241
17 -19.6063255 -17.4883184
18 8.2880802 -19.6063255
19 51.8905285 8.2880802
20 -5.3951369 51.8905285
21 -12.2895426 -5.3951369
22 0.5116816 -12.2895426
23 9.7352830 0.5116816
24 21.4060873 9.7352830
25 14.8408773 21.4060873
26 -14.9727596 14.8408773
27 -2.6187383 -14.9727596
28 8.6172759 -2.6187383
29 -17.9727596 8.6172759
30 20.4992688 -17.9727596
31 52.9712972 20.4992688
32 8.2508418 52.9712972
33 17.0272404 8.2508418
34 16.1452475 17.0272404
35 30.7104574 16.1452475
36 39.2756674 30.7104574
37 33.9340588 39.2756674
38 2.3440233 33.9340588
39 12.2508418 2.3440233
40 18.5924503 12.2508418
41 2.4620304 18.5924503
42 46.6048631 2.4620304
43 61.2880802 46.6048631
44 10.1204219 61.2880802
45 22.4744432 10.1204219
46 -0.6559767 22.4744432
47 18.8036389 -0.6559767
48 27.9216460 18.8036389
49 23.2508418 27.9216460
50 -21.1280052 23.2508418
51 23.5924503 -21.1280052
52 -1.3267810 23.5924503
53 -7.2211867 -1.3267810
54 34.6980446 -7.2211867
55 51.8284645 34.6980446
56 6.4496176 51.8284645
57 -16.4447881 6.4496176
58 -27.6683895 -16.4447881
59 4.3688489 -27.6683895
60 NA 4.3688489
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -35.6995070 -37.9231085
[2,] -57.5007312 -35.6995070
[3,] -55.1591227 -57.5007312
[4,] -58.6063255 -55.1591227
[5,] -53.7119198 -58.6063255
[6,] -29.4883184 -53.7119198
[7,] 3.9961228 -29.4883184
[8,] -43.2771298 3.9961228
[9,] -52.7367454 -43.2771298
[10,] -31.7119198 -52.7367454
[11,] -9.5814999 -31.7119198
[12,] -15.0411156 -9.5814999
[13,] -11.8175141 -15.0411156
[14,] -29.7243326 -11.8175141
[15,] -18.3827241 -29.7243326
[16,] -17.4883184 -18.3827241
[17,] -19.6063255 -17.4883184
[18,] 8.2880802 -19.6063255
[19,] 51.8905285 8.2880802
[20,] -5.3951369 51.8905285
[21,] -12.2895426 -5.3951369
[22,] 0.5116816 -12.2895426
[23,] 9.7352830 0.5116816
[24,] 21.4060873 9.7352830
[25,] 14.8408773 21.4060873
[26,] -14.9727596 14.8408773
[27,] -2.6187383 -14.9727596
[28,] 8.6172759 -2.6187383
[29,] -17.9727596 8.6172759
[30,] 20.4992688 -17.9727596
[31,] 52.9712972 20.4992688
[32,] 8.2508418 52.9712972
[33,] 17.0272404 8.2508418
[34,] 16.1452475 17.0272404
[35,] 30.7104574 16.1452475
[36,] 39.2756674 30.7104574
[37,] 33.9340588 39.2756674
[38,] 2.3440233 33.9340588
[39,] 12.2508418 2.3440233
[40,] 18.5924503 12.2508418
[41,] 2.4620304 18.5924503
[42,] 46.6048631 2.4620304
[43,] 61.2880802 46.6048631
[44,] 10.1204219 61.2880802
[45,] 22.4744432 10.1204219
[46,] -0.6559767 22.4744432
[47,] 18.8036389 -0.6559767
[48,] 27.9216460 18.8036389
[49,] 23.2508418 27.9216460
[50,] -21.1280052 23.2508418
[51,] 23.5924503 -21.1280052
[52,] -1.3267810 23.5924503
[53,] -7.2211867 -1.3267810
[54,] 34.6980446 -7.2211867
[55,] 51.8284645 34.6980446
[56,] 6.4496176 51.8284645
[57,] -16.4447881 6.4496176
[58,] -27.6683895 -16.4447881
[59,] 4.3688489 -27.6683895
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -35.6995070 -37.9231085
2 -57.5007312 -35.6995070
3 -55.1591227 -57.5007312
4 -58.6063255 -55.1591227
5 -53.7119198 -58.6063255
6 -29.4883184 -53.7119198
7 3.9961228 -29.4883184
8 -43.2771298 3.9961228
9 -52.7367454 -43.2771298
10 -31.7119198 -52.7367454
11 -9.5814999 -31.7119198
12 -15.0411156 -9.5814999
13 -11.8175141 -15.0411156
14 -29.7243326 -11.8175141
15 -18.3827241 -29.7243326
16 -17.4883184 -18.3827241
17 -19.6063255 -17.4883184
18 8.2880802 -19.6063255
19 51.8905285 8.2880802
20 -5.3951369 51.8905285
21 -12.2895426 -5.3951369
22 0.5116816 -12.2895426
23 9.7352830 0.5116816
24 21.4060873 9.7352830
25 14.8408773 21.4060873
26 -14.9727596 14.8408773
27 -2.6187383 -14.9727596
28 8.6172759 -2.6187383
29 -17.9727596 8.6172759
30 20.4992688 -17.9727596
31 52.9712972 20.4992688
32 8.2508418 52.9712972
33 17.0272404 8.2508418
34 16.1452475 17.0272404
35 30.7104574 16.1452475
36 39.2756674 30.7104574
37 33.9340588 39.2756674
38 2.3440233 33.9340588
39 12.2508418 2.3440233
40 18.5924503 12.2508418
41 2.4620304 18.5924503
42 46.6048631 2.4620304
43 61.2880802 46.6048631
44 10.1204219 61.2880802
45 22.4744432 10.1204219
46 -0.6559767 22.4744432
47 18.8036389 -0.6559767
48 27.9216460 18.8036389
49 23.2508418 27.9216460
50 -21.1280052 23.2508418
51 23.5924503 -21.1280052
52 -1.3267810 23.5924503
53 -7.2211867 -1.3267810
54 34.6980446 -7.2211867
55 51.8284645 34.6980446
56 6.4496176 51.8284645
57 -16.4447881 6.4496176
58 -27.6683895 -16.4447881
59 4.3688489 -27.6683895
> 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/7lgbt1258731636.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8lgp01258731636.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9rwu91258731636.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10grk11258731636.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ffh81258731636.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/12ju3t1258731636.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/13z5e91258731636.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/1410181258731636.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/15sh3z1258731636.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/16zb0h1258731636.tab")
+ }
>
> system("convert tmp/1s2aa1258731636.ps tmp/1s2aa1258731636.png")
> system("convert tmp/2tl8g1258731636.ps tmp/2tl8g1258731636.png")
> system("convert tmp/3ijyz1258731636.ps tmp/3ijyz1258731636.png")
> system("convert tmp/4k0xd1258731636.ps tmp/4k0xd1258731636.png")
> system("convert tmp/5k9vo1258731636.ps tmp/5k9vo1258731636.png")
> system("convert tmp/63nnh1258731636.ps tmp/63nnh1258731636.png")
> system("convert tmp/7lgbt1258731636.ps tmp/7lgbt1258731636.png")
> system("convert tmp/8lgp01258731636.ps tmp/8lgp01258731636.png")
> system("convert tmp/9rwu91258731636.ps tmp/9rwu91258731636.png")
> system("convert tmp/10grk11258731636.ps tmp/10grk11258731636.png")
>
>
> proc.time()
user system elapsed
2.537 1.600 2.943