R version 2.8.0 (2008-10-20)
Copyright (C) 2008 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(105.4,109.1,107.1,111.4,110.7,114.1,117.1,121.8,118.7,127.6,126.5,129.9,127.5,128,134.6,123.5,131.8,124,135.9,127.4,142.7,127.6,141.7,128.4,153.4,131.4,145,135.1,137.7,134,148.3,144.5,152.2,147.3,169.4,150.9,168.6,148.7,161.1,141.4,174.1,138.9,179,139.8,190.6,145.6,190,147.9,181.6,148.5,174.8,151.1,180.5,157.5,196.8,167.5,193.8,172.3,197,173.5,216.3,187.5,221.4,205.5,217.9,195.1,229.7,204.5,227.4,204.5,204.2,201.7,196.6,207,198.8,206.6,207.5,210.6,190.7,211.1,201.6,215,210.5,223.9,223.5,238.2,223.8,238.9,231.2,229.6,244,232.2,234.7,222.1,250.2,221.6,265.7,227.3,287.6,221,283.3,213.6,295.4,243.4,312.3,253.8,333.8,265.3,347.7,268.2,383.2,268.5,407.1,266.9,413.6,268.4,362.7,250.8,321.9,231.2,239.4,192),dim=c(2,61),dimnames=list(c('alg_indexcijfer_grondstoffen','indexcijfer_industr_grondstoffen'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('alg_indexcijfer_grondstoffen','indexcijfer_industr_grondstoffen'),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
alg_indexcijfer_grondstoffen indexcijfer_industr_grondstoffen
1 105.4 109.1
2 107.1 111.4
3 110.7 114.1
4 117.1 121.8
5 118.7 127.6
6 126.5 129.9
7 127.5 128.0
8 134.6 123.5
9 131.8 124.0
10 135.9 127.4
11 142.7 127.6
12 141.7 128.4
13 153.4 131.4
14 145.0 135.1
15 137.7 134.0
16 148.3 144.5
17 152.2 147.3
18 169.4 150.9
19 168.6 148.7
20 161.1 141.4
21 174.1 138.9
22 179.0 139.8
23 190.6 145.6
24 190.0 147.9
25 181.6 148.5
26 174.8 151.1
27 180.5 157.5
28 196.8 167.5
29 193.8 172.3
30 197.0 173.5
31 216.3 187.5
32 221.4 205.5
33 217.9 195.1
34 229.7 204.5
35 227.4 204.5
36 204.2 201.7
37 196.6 207.0
38 198.8 206.6
39 207.5 210.6
40 190.7 211.1
41 201.6 215.0
42 210.5 223.9
43 223.5 238.2
44 223.8 238.9
45 231.2 229.6
46 244.0 232.2
47 234.7 222.1
48 250.2 221.6
49 265.7 227.3
50 287.6 221.0
51 283.3 213.6
52 295.4 243.4
53 312.3 253.8
54 333.8 265.3
55 347.7 268.2
56 383.2 268.5
57 407.1 266.9
58 413.6 268.4
59 362.7 250.8
60 321.9 231.2
61 239.4 192.0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) indexcijfer_industr_grondstoffen
-46.020 1.395
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-63.356 -11.781 1.052 10.766 85.303
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -46.01961 15.70882 -2.93 0.00482 **
indexcijfer_industr_grondstoffen 1.39462 0.08287 16.83 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 31.53 on 59 degrees of freedom
Multiple R-squared: 0.8276, Adjusted R-squared: 0.8247
F-statistic: 283.2 on 1 and 59 DF, p-value: < 2.2e-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,] 9.793666e-05 1.958733e-04 0.99990206
[2,] 3.340774e-05 6.681548e-05 0.99996659
[3,] 1.146165e-05 2.292330e-05 0.99998854
[4,] 1.939369e-04 3.878739e-04 0.99980606
[5,] 8.782845e-05 1.756569e-04 0.99991217
[6,] 3.128374e-05 6.256747e-05 0.99996872
[7,] 2.644598e-05 5.289196e-05 0.99997355
[8,] 1.049171e-05 2.098341e-05 0.99998951
[9,] 9.441156e-06 1.888231e-05 0.99999056
[10,] 2.163048e-06 4.326096e-06 0.99999784
[11,] 6.132861e-07 1.226572e-06 0.99999939
[12,] 2.442956e-07 4.885913e-07 0.99999976
[13,] 6.942939e-08 1.388588e-07 0.99999993
[14,] 1.883918e-08 3.767837e-08 0.99999998
[15,] 5.322403e-09 1.064481e-08 0.99999999
[16,] 1.844048e-09 3.688096e-09 1.00000000
[17,] 1.442299e-08 2.884598e-08 0.99999999
[18,] 7.766883e-08 1.553377e-07 0.99999992
[19,] 2.709662e-07 5.419324e-07 0.99999973
[20,] 3.248465e-07 6.496930e-07 0.99999968
[21,] 1.728413e-07 3.456826e-07 0.99999983
[22,] 8.015984e-08 1.603197e-07 0.99999992
[23,] 4.808303e-08 9.616605e-08 0.99999995
[24,] 3.207250e-08 6.414501e-08 0.99999997
[25,] 3.650605e-08 7.301210e-08 0.99999996
[26,] 3.487884e-08 6.975768e-08 0.99999997
[27,] 2.953982e-08 5.907963e-08 0.99999997
[28,] 6.521236e-08 1.304247e-07 0.99999993
[29,] 3.975272e-08 7.950543e-08 0.99999996
[30,] 1.935990e-08 3.871981e-08 0.99999998
[31,] 9.526800e-09 1.905360e-08 0.99999999
[32,] 1.643103e-08 3.286205e-08 0.99999998
[33,] 7.723959e-08 1.544792e-07 0.99999992
[34,] 1.167512e-07 2.335024e-07 0.99999988
[35,] 9.060007e-08 1.812001e-07 0.99999991
[36,] 3.019979e-07 6.039959e-07 0.99999970
[37,] 4.106477e-07 8.212955e-07 0.99999959
[38,] 8.124339e-07 1.624868e-06 0.99999919
[39,] 5.837747e-06 1.167549e-05 0.99999416
[40,] 9.320100e-05 1.864020e-04 0.99990680
[41,] 2.822010e-04 5.644020e-04 0.99971780
[42,] 9.265061e-04 1.853012e-03 0.99907349
[43,] 2.238012e-03 4.476024e-03 0.99776199
[44,] 3.958790e-03 7.917579e-03 0.99604121
[45,] 8.660064e-03 1.732013e-02 0.99133994
[46,] 1.790913e-02 3.581825e-02 0.98209087
[47,] 2.756706e-02 5.513413e-02 0.97243294
[48,] 4.653523e-02 9.307045e-02 0.95346477
[49,] 1.060465e-01 2.120931e-01 0.89395346
[50,] 3.257506e-01 6.515011e-01 0.67424943
[51,] 8.918004e-01 2.163992e-01 0.10819962
[52,] 9.870801e-01 2.583975e-02 0.01291988
> postscript(file="/var/www/html/rcomp/tmp/1fk831227788945.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2vvye1227788945.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/36hjc1227788945.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4guxu1227788945.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5350g1227788945.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
-0.7337834 -2.2414169 -2.4068996 -6.7454986 -13.2343134 -8.6419469
7 8 9 10 11 12
-4.9921627 8.3836419 4.8863302 4.2446112 10.7656866 8.6499880
13 14 15 16 17 18
16.1661182 2.6060122 -3.1599022 -7.2034462 -7.2083913 4.9709650
19 20 21 22 23 24
7.2391361 9.9198858 26.4064439 30.0512830 33.5624682 29.7548347
25 26 27 28 29 30
20.5180608 10.0920403 6.8664516 9.2202192 -0.4739724 1.0524797
31 32 33 34 35 36
0.8277543 -19.1754641 -8.1713824 -9.4808408 -11.7808408 -31.0758958
37 38 39 40 41 42
-46.0673990 -43.3095497 -40.1880426 -57.6853543 -52.2243849 -55.7365318
43 44 45 46 47 48
-62.6796442 -63.3558804 -42.9858843 -33.8119047 -29.0262099 -12.8288983
49 50 51 52 53 54
-5.2782508 25.4078756 31.4280876 1.9683150 4.3642332 9.8260660
55 56 57 58 59 60
19.6816585 54.7632716 80.8946688 85.3027339 58.9481030 45.4827186
61
17.6519497
> postscript(file="/var/www/html/rcomp/tmp/6iak11227788945.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 -0.7337834 NA
1 -2.2414169 -0.7337834
2 -2.4068996 -2.2414169
3 -6.7454986 -2.4068996
4 -13.2343134 -6.7454986
5 -8.6419469 -13.2343134
6 -4.9921627 -8.6419469
7 8.3836419 -4.9921627
8 4.8863302 8.3836419
9 4.2446112 4.8863302
10 10.7656866 4.2446112
11 8.6499880 10.7656866
12 16.1661182 8.6499880
13 2.6060122 16.1661182
14 -3.1599022 2.6060122
15 -7.2034462 -3.1599022
16 -7.2083913 -7.2034462
17 4.9709650 -7.2083913
18 7.2391361 4.9709650
19 9.9198858 7.2391361
20 26.4064439 9.9198858
21 30.0512830 26.4064439
22 33.5624682 30.0512830
23 29.7548347 33.5624682
24 20.5180608 29.7548347
25 10.0920403 20.5180608
26 6.8664516 10.0920403
27 9.2202192 6.8664516
28 -0.4739724 9.2202192
29 1.0524797 -0.4739724
30 0.8277543 1.0524797
31 -19.1754641 0.8277543
32 -8.1713824 -19.1754641
33 -9.4808408 -8.1713824
34 -11.7808408 -9.4808408
35 -31.0758958 -11.7808408
36 -46.0673990 -31.0758958
37 -43.3095497 -46.0673990
38 -40.1880426 -43.3095497
39 -57.6853543 -40.1880426
40 -52.2243849 -57.6853543
41 -55.7365318 -52.2243849
42 -62.6796442 -55.7365318
43 -63.3558804 -62.6796442
44 -42.9858843 -63.3558804
45 -33.8119047 -42.9858843
46 -29.0262099 -33.8119047
47 -12.8288983 -29.0262099
48 -5.2782508 -12.8288983
49 25.4078756 -5.2782508
50 31.4280876 25.4078756
51 1.9683150 31.4280876
52 4.3642332 1.9683150
53 9.8260660 4.3642332
54 19.6816585 9.8260660
55 54.7632716 19.6816585
56 80.8946688 54.7632716
57 85.3027339 80.8946688
58 58.9481030 85.3027339
59 45.4827186 58.9481030
60 17.6519497 45.4827186
61 NA 17.6519497
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -2.2414169 -0.7337834
[2,] -2.4068996 -2.2414169
[3,] -6.7454986 -2.4068996
[4,] -13.2343134 -6.7454986
[5,] -8.6419469 -13.2343134
[6,] -4.9921627 -8.6419469
[7,] 8.3836419 -4.9921627
[8,] 4.8863302 8.3836419
[9,] 4.2446112 4.8863302
[10,] 10.7656866 4.2446112
[11,] 8.6499880 10.7656866
[12,] 16.1661182 8.6499880
[13,] 2.6060122 16.1661182
[14,] -3.1599022 2.6060122
[15,] -7.2034462 -3.1599022
[16,] -7.2083913 -7.2034462
[17,] 4.9709650 -7.2083913
[18,] 7.2391361 4.9709650
[19,] 9.9198858 7.2391361
[20,] 26.4064439 9.9198858
[21,] 30.0512830 26.4064439
[22,] 33.5624682 30.0512830
[23,] 29.7548347 33.5624682
[24,] 20.5180608 29.7548347
[25,] 10.0920403 20.5180608
[26,] 6.8664516 10.0920403
[27,] 9.2202192 6.8664516
[28,] -0.4739724 9.2202192
[29,] 1.0524797 -0.4739724
[30,] 0.8277543 1.0524797
[31,] -19.1754641 0.8277543
[32,] -8.1713824 -19.1754641
[33,] -9.4808408 -8.1713824
[34,] -11.7808408 -9.4808408
[35,] -31.0758958 -11.7808408
[36,] -46.0673990 -31.0758958
[37,] -43.3095497 -46.0673990
[38,] -40.1880426 -43.3095497
[39,] -57.6853543 -40.1880426
[40,] -52.2243849 -57.6853543
[41,] -55.7365318 -52.2243849
[42,] -62.6796442 -55.7365318
[43,] -63.3558804 -62.6796442
[44,] -42.9858843 -63.3558804
[45,] -33.8119047 -42.9858843
[46,] -29.0262099 -33.8119047
[47,] -12.8288983 -29.0262099
[48,] -5.2782508 -12.8288983
[49,] 25.4078756 -5.2782508
[50,] 31.4280876 25.4078756
[51,] 1.9683150 31.4280876
[52,] 4.3642332 1.9683150
[53,] 9.8260660 4.3642332
[54,] 19.6816585 9.8260660
[55,] 54.7632716 19.6816585
[56,] 80.8946688 54.7632716
[57,] 85.3027339 80.8946688
[58,] 58.9481030 85.3027339
[59,] 45.4827186 58.9481030
[60,] 17.6519497 45.4827186
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -2.2414169 -0.7337834
2 -2.4068996 -2.2414169
3 -6.7454986 -2.4068996
4 -13.2343134 -6.7454986
5 -8.6419469 -13.2343134
6 -4.9921627 -8.6419469
7 8.3836419 -4.9921627
8 4.8863302 8.3836419
9 4.2446112 4.8863302
10 10.7656866 4.2446112
11 8.6499880 10.7656866
12 16.1661182 8.6499880
13 2.6060122 16.1661182
14 -3.1599022 2.6060122
15 -7.2034462 -3.1599022
16 -7.2083913 -7.2034462
17 4.9709650 -7.2083913
18 7.2391361 4.9709650
19 9.9198858 7.2391361
20 26.4064439 9.9198858
21 30.0512830 26.4064439
22 33.5624682 30.0512830
23 29.7548347 33.5624682
24 20.5180608 29.7548347
25 10.0920403 20.5180608
26 6.8664516 10.0920403
27 9.2202192 6.8664516
28 -0.4739724 9.2202192
29 1.0524797 -0.4739724
30 0.8277543 1.0524797
31 -19.1754641 0.8277543
32 -8.1713824 -19.1754641
33 -9.4808408 -8.1713824
34 -11.7808408 -9.4808408
35 -31.0758958 -11.7808408
36 -46.0673990 -31.0758958
37 -43.3095497 -46.0673990
38 -40.1880426 -43.3095497
39 -57.6853543 -40.1880426
40 -52.2243849 -57.6853543
41 -55.7365318 -52.2243849
42 -62.6796442 -55.7365318
43 -63.3558804 -62.6796442
44 -42.9858843 -63.3558804
45 -33.8119047 -42.9858843
46 -29.0262099 -33.8119047
47 -12.8288983 -29.0262099
48 -5.2782508 -12.8288983
49 25.4078756 -5.2782508
50 31.4280876 25.4078756
51 1.9683150 31.4280876
52 4.3642332 1.9683150
53 9.8260660 4.3642332
54 19.6816585 9.8260660
55 54.7632716 19.6816585
56 80.8946688 54.7632716
57 85.3027339 80.8946688
58 58.9481030 85.3027339
59 45.4827186 58.9481030
60 17.6519497 45.4827186
> 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/7e6nc1227788945.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8sjqh1227788945.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9esyx1227788945.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/106dia1227788945.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11xdtk1227788945.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/12uuf91227788945.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/13fx0t1227788945.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/14g1271227788945.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/15daze1227788945.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/16vgkr1227788945.tab")
+ }
>
> system("convert tmp/1fk831227788945.ps tmp/1fk831227788945.png")
> system("convert tmp/2vvye1227788945.ps tmp/2vvye1227788945.png")
> system("convert tmp/36hjc1227788945.ps tmp/36hjc1227788945.png")
> system("convert tmp/4guxu1227788945.ps tmp/4guxu1227788945.png")
> system("convert tmp/5350g1227788945.ps tmp/5350g1227788945.png")
> system("convert tmp/6iak11227788945.ps tmp/6iak11227788945.png")
> system("convert tmp/7e6nc1227788945.ps tmp/7e6nc1227788945.png")
> system("convert tmp/8sjqh1227788945.ps tmp/8sjqh1227788945.png")
> system("convert tmp/9esyx1227788945.ps tmp/9esyx1227788945.png")
> system("convert tmp/106dia1227788945.ps tmp/106dia1227788945.png")
>
>
> proc.time()
user system elapsed
2.702 1.679 4.093