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(2284
+ ,41
+ ,76403
+ ,194493
+ ,3160
+ ,90
+ ,108094
+ ,530670
+ ,4150
+ ,136
+ ,134759
+ ,518365
+ ,7285
+ ,97
+ ,188873
+ ,491303
+ ,1134
+ ,63
+ ,146216
+ ,527021
+ ,4658
+ ,114
+ ,156608
+ ,233773
+ ,2384
+ ,77
+ ,61348
+ ,405972
+ ,3748
+ ,6
+ ,50350
+ ,652925
+ ,5371
+ ,47
+ ,87720
+ ,446211
+ ,1285
+ ,51
+ ,99489
+ ,341340
+ ,9327
+ ,85
+ ,87419
+ ,387699
+ ,5565
+ ,43
+ ,94355
+ ,493408
+ ,1528
+ ,32
+ ,60326
+ ,146494
+ ,3122
+ ,25
+ ,94670
+ ,414462
+ ,7561
+ ,77
+ ,82425
+ ,364304
+ ,2675
+ ,54
+ ,59017
+ ,355178
+ ,13253
+ ,251
+ ,90829
+ ,357760
+ ,880
+ ,15
+ ,80791
+ ,261216
+ ,2053
+ ,44
+ ,100423
+ ,397144
+ ,1424
+ ,73
+ ,131116
+ ,374943
+ ,4036
+ ,85
+ ,100269
+ ,424898
+ ,3045
+ ,49
+ ,27330
+ ,202055
+ ,5119
+ ,38
+ ,39039
+ ,378525
+ ,1431
+ ,35
+ ,106885
+ ,310768
+ ,554
+ ,9
+ ,79285
+ ,325738
+ ,1975
+ ,34
+ ,118881
+ ,394510
+ ,1765
+ ,20
+ ,77623
+ ,247060
+ ,1012
+ ,29
+ ,114768
+ ,368078
+ ,810
+ ,11
+ ,74015
+ ,236761
+ ,1280
+ ,52
+ ,69465
+ ,312378
+ ,666
+ ,13
+ ,117869
+ ,339836
+ ,1380
+ ,29
+ ,60982
+ ,347385
+ ,4677
+ ,66
+ ,90131
+ ,426280
+ ,876
+ ,33
+ ,138971
+ ,352850
+ ,814
+ ,15
+ ,39625
+ ,301881
+ ,514
+ ,15
+ ,102725
+ ,377516
+ ,5692
+ ,68
+ ,64239
+ ,357312
+ ,3642
+ ,100
+ ,90262
+ ,458343
+ ,540
+ ,13
+ ,103960
+ ,354228
+ ,2099
+ ,45
+ ,106611
+ ,308636
+ ,567
+ ,14
+ ,103345
+ ,386212
+ ,2001
+ ,36
+ ,95551
+ ,393343
+ ,2949
+ ,40
+ ,82903
+ ,378509
+ ,2253
+ ,68
+ ,63593
+ ,452469
+ ,6533
+ ,29
+ ,126910
+ ,364839
+ ,1889
+ ,43
+ ,37527
+ ,358649
+ ,3055
+ ,30
+ ,60247
+ ,376641
+ ,272
+ ,9
+ ,112995
+ ,429112
+ ,1414
+ ,22
+ ,70184
+ ,330546
+ ,2564
+ ,19
+ ,130140
+ ,403560
+ ,1383
+ ,9
+ ,73221
+ ,317892)
+ ,dim=c(4
+ ,51)
+ ,dimnames=list(c('Costs'
+ ,'Orders'
+ ,'Dividends'
+ ,'Wealth')
+ ,1:51))
> y <- array(NA,dim=c(4,51),dimnames=list(c('Costs','Orders','Dividends','Wealth'),1:51))
> 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 = '4'
> #'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
Wealth Costs Orders Dividends
1 194493 2284 41 76403
2 530670 3160 90 108094
3 518365 4150 136 134759
4 491303 7285 97 188873
5 527021 1134 63 146216
6 233773 4658 114 156608
7 405972 2384 77 61348
8 652925 3748 6 50350
9 446211 5371 47 87720
10 341340 1285 51 99489
11 387699 9327 85 87419
12 493408 5565 43 94355
13 146494 1528 32 60326
14 414462 3122 25 94670
15 364304 7561 77 82425
16 355178 2675 54 59017
17 357760 13253 251 90829
18 261216 880 15 80791
19 397144 2053 44 100423
20 374943 1424 73 131116
21 424898 4036 85 100269
22 202055 3045 49 27330
23 378525 5119 38 39039
24 310768 1431 35 106885
25 325738 554 9 79285
26 394510 1975 34 118881
27 247060 1765 20 77623
28 368078 1012 29 114768
29 236761 810 11 74015
30 312378 1280 52 69465
31 339836 666 13 117869
32 347385 1380 29 60982
33 426280 4677 66 90131
34 352850 876 33 138971
35 301881 814 15 39625
36 377516 514 15 102725
37 357312 5692 68 64239
38 458343 3642 100 90262
39 354228 540 13 103960
40 308636 2099 45 106611
41 386212 567 14 103345
42 393343 2001 36 95551
43 378509 2949 40 82903
44 452469 2253 68 63593
45 364839 6533 29 126910
46 358649 1889 43 37527
47 376641 3055 30 60247
48 429112 272 9 112995
49 330546 1414 22 70184
50 403560 2564 19 130140
51 317892 1383 9 73221
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Costs Orders Dividends
281385.616 9.226 -138.708 0.755
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-193024 -35932 2890 36862 299776
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.814e+05 3.943e+04 7.136 5.08e-09 ***
Costs 9.226e+00 7.325e+00 1.259 0.214
Orders -1.387e+02 4.567e+02 -0.304 0.763
Dividends 7.551e-01 4.012e-01 1.882 0.066 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 88340 on 47 degrees of freedom
Multiple R-squared: 0.1202, Adjusted R-squared: 0.06403
F-statistic: 2.14 on 3 and 47 DF, p-value: 0.1077
> 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,] 0.9970144 5.971194e-03 2.985597e-03
[2,] 0.9999938 1.244990e-05 6.224951e-06
[3,] 0.9999852 2.966353e-05 1.483177e-05
[4,] 0.9999679 6.421086e-05 3.210543e-05
[5,] 0.9999350 1.300870e-04 6.504349e-05
[6,] 0.9999299 1.402138e-04 7.010690e-05
[7,] 0.9999995 9.339763e-07 4.669882e-07
[8,] 0.9999990 2.061291e-06 1.030646e-06
[9,] 0.9999973 5.358236e-06 2.679118e-06
[10,] 0.9999925 1.500610e-05 7.503052e-06
[11,] 0.9999973 5.458876e-06 2.729438e-06
[12,] 0.9999975 4.971467e-06 2.485733e-06
[13,] 0.9999934 1.316748e-05 6.583738e-06
[14,] 0.9999877 2.465187e-05 1.232593e-05
[15,] 0.9999691 6.185011e-05 3.092505e-05
[16,] 0.9999960 7.904782e-06 3.952391e-06
[17,] 0.9999918 1.642479e-05 8.212394e-06
[18,] 0.9999909 1.812153e-05 9.060766e-06
[19,] 0.9999757 4.851045e-05 2.425522e-05
[20,] 0.9999374 1.251855e-04 6.259276e-05
[21,] 0.9999734 5.323415e-05 2.661708e-05
[22,] 0.9999288 1.424014e-04 7.120070e-05
[23,] 0.9999801 3.971380e-05 1.985690e-05
[24,] 0.9999853 2.933894e-05 1.466947e-05
[25,] 0.9999657 6.852150e-05 3.426075e-05
[26,] 0.9999031 1.937621e-04 9.688103e-05
[27,] 0.9997809 4.382008e-04 2.191004e-04
[28,] 0.9997829 4.341302e-04 2.170651e-04
[29,] 0.9994994 1.001233e-03 5.006164e-04
[30,] 0.9986274 2.745267e-03 1.372634e-03
[31,] 0.9967905 6.419054e-03 3.209527e-03
[32,] 0.9930634 1.387312e-02 6.936561e-03
[33,] 0.9847298 3.054034e-02 1.527017e-02
[34,] 0.9995927 8.145324e-04 4.072662e-04
[35,] 0.9983277 3.344514e-03 1.672257e-03
[36,] 0.9950984 9.803207e-03 4.901604e-03
[37,] 0.9842199 3.156027e-02 1.578013e-02
[38,] 0.9476615 1.046770e-01 5.233848e-02
> postscript(file="/var/www/html/rcomp/tmp/11b5u1291123098.ps",horizontal=F,onefile=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2uk4x1291123098.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3uk4x1291123098.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4uk4x1291123098.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5uk4x1291123098.ps",horizontal=F,onefile=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 = 51
Frequency = 1
1 2 3 4 5 6
-159967.108 150995.772 115803.790 13549.385 133508.166 -193024.062
7 8 9 10 11 12
66950.418 299775.524 55558.036 -19948.111 -33952.925 95400.496
13 14 15 16 17 18
-190100.487 36258.456 -38394.049 12041.520 -79661.609 -87210.794
19 20 21 22 23 24
27094.309 -8456.624 42356.911 -121262.548 25706.278 -59670.917
25 26 27 28 29 30
-19376.300 9855.701 -106445.986 -5279.809 -106458.445 -26054.957
31 32 33 34 35 36
-34890.499 11244.476 42844.681 -36973.311 -14853.550 15904.061
37 38 39 40 41 42
-15659.700 89073.495 -8833.739 -66371.762 23504.243 26342.104
43 44 45 46 47 48
12867.074 111712.485 -68622.360 37464.710 25741.005 61145.849
49 50 51
-13827.337 2889.741 -30291.696
> postscript(file="/var/www/html/rcomp/tmp/6ntm01291123098.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 51
Frequency = 1
lag(myerror, k = 1) myerror
0 -159967.108 NA
1 150995.772 -159967.108
2 115803.790 150995.772
3 13549.385 115803.790
4 133508.166 13549.385
5 -193024.062 133508.166
6 66950.418 -193024.062
7 299775.524 66950.418
8 55558.036 299775.524
9 -19948.111 55558.036
10 -33952.925 -19948.111
11 95400.496 -33952.925
12 -190100.487 95400.496
13 36258.456 -190100.487
14 -38394.049 36258.456
15 12041.520 -38394.049
16 -79661.609 12041.520
17 -87210.794 -79661.609
18 27094.309 -87210.794
19 -8456.624 27094.309
20 42356.911 -8456.624
21 -121262.548 42356.911
22 25706.278 -121262.548
23 -59670.917 25706.278
24 -19376.300 -59670.917
25 9855.701 -19376.300
26 -106445.986 9855.701
27 -5279.809 -106445.986
28 -106458.445 -5279.809
29 -26054.957 -106458.445
30 -34890.499 -26054.957
31 11244.476 -34890.499
32 42844.681 11244.476
33 -36973.311 42844.681
34 -14853.550 -36973.311
35 15904.061 -14853.550
36 -15659.700 15904.061
37 89073.495 -15659.700
38 -8833.739 89073.495
39 -66371.762 -8833.739
40 23504.243 -66371.762
41 26342.104 23504.243
42 12867.074 26342.104
43 111712.485 12867.074
44 -68622.360 111712.485
45 37464.710 -68622.360
46 25741.005 37464.710
47 61145.849 25741.005
48 -13827.337 61145.849
49 2889.741 -13827.337
50 -30291.696 2889.741
51 NA -30291.696
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 150995.772 -159967.108
[2,] 115803.790 150995.772
[3,] 13549.385 115803.790
[4,] 133508.166 13549.385
[5,] -193024.062 133508.166
[6,] 66950.418 -193024.062
[7,] 299775.524 66950.418
[8,] 55558.036 299775.524
[9,] -19948.111 55558.036
[10,] -33952.925 -19948.111
[11,] 95400.496 -33952.925
[12,] -190100.487 95400.496
[13,] 36258.456 -190100.487
[14,] -38394.049 36258.456
[15,] 12041.520 -38394.049
[16,] -79661.609 12041.520
[17,] -87210.794 -79661.609
[18,] 27094.309 -87210.794
[19,] -8456.624 27094.309
[20,] 42356.911 -8456.624
[21,] -121262.548 42356.911
[22,] 25706.278 -121262.548
[23,] -59670.917 25706.278
[24,] -19376.300 -59670.917
[25,] 9855.701 -19376.300
[26,] -106445.986 9855.701
[27,] -5279.809 -106445.986
[28,] -106458.445 -5279.809
[29,] -26054.957 -106458.445
[30,] -34890.499 -26054.957
[31,] 11244.476 -34890.499
[32,] 42844.681 11244.476
[33,] -36973.311 42844.681
[34,] -14853.550 -36973.311
[35,] 15904.061 -14853.550
[36,] -15659.700 15904.061
[37,] 89073.495 -15659.700
[38,] -8833.739 89073.495
[39,] -66371.762 -8833.739
[40,] 23504.243 -66371.762
[41,] 26342.104 23504.243
[42,] 12867.074 26342.104
[43,] 111712.485 12867.074
[44,] -68622.360 111712.485
[45,] 37464.710 -68622.360
[46,] 25741.005 37464.710
[47,] 61145.849 25741.005
[48,] -13827.337 61145.849
[49,] 2889.741 -13827.337
[50,] -30291.696 2889.741
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 150995.772 -159967.108
2 115803.790 150995.772
3 13549.385 115803.790
4 133508.166 13549.385
5 -193024.062 133508.166
6 66950.418 -193024.062
7 299775.524 66950.418
8 55558.036 299775.524
9 -19948.111 55558.036
10 -33952.925 -19948.111
11 95400.496 -33952.925
12 -190100.487 95400.496
13 36258.456 -190100.487
14 -38394.049 36258.456
15 12041.520 -38394.049
16 -79661.609 12041.520
17 -87210.794 -79661.609
18 27094.309 -87210.794
19 -8456.624 27094.309
20 42356.911 -8456.624
21 -121262.548 42356.911
22 25706.278 -121262.548
23 -59670.917 25706.278
24 -19376.300 -59670.917
25 9855.701 -19376.300
26 -106445.986 9855.701
27 -5279.809 -106445.986
28 -106458.445 -5279.809
29 -26054.957 -106458.445
30 -34890.499 -26054.957
31 11244.476 -34890.499
32 42844.681 11244.476
33 -36973.311 42844.681
34 -14853.550 -36973.311
35 15904.061 -14853.550
36 -15659.700 15904.061
37 89073.495 -15659.700
38 -8833.739 89073.495
39 -66371.762 -8833.739
40 23504.243 -66371.762
41 26342.104 23504.243
42 12867.074 26342.104
43 111712.485 12867.074
44 -68622.360 111712.485
45 37464.710 -68622.360
46 25741.005 37464.710
47 61145.849 25741.005
48 -13827.337 61145.849
49 2889.741 -13827.337
50 -30291.696 2889.741
> 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/7x23l1291123098.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8x23l1291123098.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9i4511291123099.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10i4511291123099.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11m4371291123099.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/12pnkd1291123099.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/13eoho1291123099.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/147fyr1291123099.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/15axwf1291123099.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/16dyvl1291123099.tab")
+ }
>
> try(system("convert tmp/11b5u1291123098.ps tmp/11b5u1291123098.png",intern=TRUE))
character(0)
> try(system("convert tmp/2uk4x1291123098.ps tmp/2uk4x1291123098.png",intern=TRUE))
character(0)
> try(system("convert tmp/3uk4x1291123098.ps tmp/3uk4x1291123098.png",intern=TRUE))
character(0)
> try(system("convert tmp/4uk4x1291123098.ps tmp/4uk4x1291123098.png",intern=TRUE))
character(0)
> try(system("convert tmp/5uk4x1291123098.ps tmp/5uk4x1291123098.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ntm01291123098.ps tmp/6ntm01291123098.png",intern=TRUE))
character(0)
> try(system("convert tmp/7x23l1291123098.ps tmp/7x23l1291123098.png",intern=TRUE))
character(0)
> try(system("convert tmp/8x23l1291123098.ps tmp/8x23l1291123098.png",intern=TRUE))
character(0)
> try(system("convert tmp/9i4511291123099.ps tmp/9i4511291123099.png",intern=TRUE))
character(0)
> try(system("convert tmp/10i4511291123099.ps tmp/10i4511291123099.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.484 1.623 5.554