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(6539,2605,6699,2682,6962,2755,6981,2760,7024,2735,6940,2659,6774,2654,6671,2670,6965,2785,6969,2845,6822,2723,6878,2746,6691,2767,6837,2940,7018,2977,7167,2993,7076,2892,7171,2824,7093,2771,6971,2686,7142,2738,7047,2723,6999,2731,6650,2632,6475,2606,6437,2605,6639,2646,6422,2627,6272,2535,6232,2456,6003,2404,5673,2319,6050,2519,5977,2504,5796,2382,5752,2394,5609,2381,5839,2501,6069,2532,6006,2515,5809,2429,5797,2389,5502,2261,5568,2272,5864,2439,5764,2373,5615,2327,5615,2364,5681,2388,5915,2553,6334,2663,6494,2694,6620,2679,6578,2611,6495,2580,6538,2627,6737,2732,6651,2707,6530,2633,6563,2683),dim=c(2,60),dimnames=list(c('Voeding-Mannen','Landbouw-Mannen'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Voeding-Mannen','Landbouw-Mannen'),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
Voeding-Mannen Landbouw-Mannen
1 6539 2605
2 6699 2682
3 6962 2755
4 6981 2760
5 7024 2735
6 6940 2659
7 6774 2654
8 6671 2670
9 6965 2785
10 6969 2845
11 6822 2723
12 6878 2746
13 6691 2767
14 6837 2940
15 7018 2977
16 7167 2993
17 7076 2892
18 7171 2824
19 7093 2771
20 6971 2686
21 7142 2738
22 7047 2723
23 6999 2731
24 6650 2632
25 6475 2606
26 6437 2605
27 6639 2646
28 6422 2627
29 6272 2535
30 6232 2456
31 6003 2404
32 5673 2319
33 6050 2519
34 5977 2504
35 5796 2382
36 5752 2394
37 5609 2381
38 5839 2501
39 6069 2532
40 6006 2515
41 5809 2429
42 5797 2389
43 5502 2261
44 5568 2272
45 5864 2439
46 5764 2373
47 5615 2327
48 5615 2364
49 5681 2388
50 5915 2553
51 6334 2663
52 6494 2694
53 6620 2679
54 6578 2611
55 6495 2580
56 6538 2627
57 6737 2732
58 6651 2707
59 6530 2633
60 6563 2683
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `Landbouw-Mannen`
-680.486 2.725
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-494.74 -131.20 19.46 132.60 374.06
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -680.4859 366.6620 -1.856 0.0686 .
`Landbouw-Mannen` 2.7252 0.1402 19.445 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 188.2 on 58 degrees of freedom
Multiple R-squared: 0.867, Adjusted R-squared: 0.8647
F-statistic: 378.1 on 1 and 58 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,] 0.06289996 0.1257999181 0.9371000410
[2,] 0.23030511 0.4606102173 0.7696948914
[3,] 0.13550614 0.2710122864 0.8644938568
[4,] 0.10230612 0.2046122347 0.8976938826
[5,] 0.06832937 0.1366587387 0.9316706306
[6,] 0.07051519 0.1410303870 0.9294848065
[7,] 0.04072510 0.0814502053 0.9592748974
[8,] 0.02182953 0.0436590685 0.9781704657
[9,] 0.05150842 0.1030168492 0.9484915754
[10,] 0.13534491 0.2706898234 0.8646550883
[11,] 0.14455103 0.2891020661 0.8554489670
[12,] 0.18518237 0.3703647315 0.8148176343
[13,] 0.17583918 0.3516783556 0.8241608222
[14,] 0.24460703 0.4892140688 0.7553929656
[15,] 0.28212448 0.5642489544 0.7178755228
[16,] 0.33882281 0.6776456151 0.6611771924
[17,] 0.54647625 0.9070474967 0.4535237483
[18,] 0.65230853 0.6953829334 0.3476914667
[19,] 0.69661342 0.6067731551 0.3033865776
[20,] 0.73419805 0.5316038969 0.2658019485
[21,] 0.80800477 0.3839904671 0.1919952335
[22,] 0.85286203 0.2942759387 0.1471379694
[23,] 0.85229408 0.2954118499 0.1477059249
[24,] 0.87874416 0.2425116806 0.1212558403
[25,] 0.90116099 0.1976780164 0.0988390082
[26,] 0.94454440 0.1109112023 0.0554556011
[27,] 0.96598279 0.0680344139 0.0340172070
[28,] 0.97804686 0.0439062856 0.0219531428
[29,] 0.98081965 0.0383607091 0.0191803545
[30,] 0.98427457 0.0314508645 0.0157254323
[31,] 0.98050559 0.0389888139 0.0194944069
[32,] 0.97612286 0.0477542747 0.0238771373
[33,] 0.97990477 0.0401904587 0.0200952293
[34,] 0.99159591 0.0168081823 0.0084040912
[35,] 0.98895707 0.0220858612 0.0110429306
[36,] 0.98671994 0.0265601250 0.0132800625
[37,] 0.98130162 0.0373967688 0.0186983844
[38,] 0.96873777 0.0625244650 0.0312622325
[39,] 0.95243283 0.0951343477 0.0475671739
[40,] 0.94160764 0.1167847199 0.0583923599
[41,] 0.91176955 0.1764609015 0.0882304507
[42,] 0.87350671 0.2529865816 0.1264932908
[43,] 0.82672376 0.3465524891 0.1732762446
[44,] 0.76140810 0.4771837916 0.2385918958
[45,] 0.68612922 0.6277415630 0.3138707815
[46,] 0.97665840 0.0466831933 0.0233415967
[47,] 0.99835821 0.0032835704 0.0016417852
[48,] 0.99971937 0.0005612589 0.0002806294
[49,] 0.99851303 0.0029739388 0.0014869694
[50,] 0.99682831 0.0063433889 0.0031716944
[51,] 0.98967111 0.0206577793 0.0103288896
> postscript(file="/var/www/html/rcomp/tmp/1gb101258724818.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2kb5n1258724818.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3m6q91258724818.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4dk7k1258724818.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5bvw41258724818.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
120.2209060 70.3769875 134.4340518 139.8078233 250.9389657 374.0576385
7 8 9 10 11 12
221.6838669 75.0799358 55.6766809 -103.8380608 81.6419140 74.9612630
13 14 15 16 17 18
-169.2688966 -494.7364018 -414.5704925 -309.1744236 -124.9246084 155.3920988
19 20 21 22 23 24
221.8301206 331.4760047 360.7632286 306.6419140 236.8399484 157.6392722
25 26 27 28 29 30
53.4956603 18.2209060 108.4858325 -56.7344993 43.9881046 219.2825145
31 32 33 34 35 36
131.9952907 33.6411747 -134.4079643 -166.5292788 -15.0493041 -91.7522524
37 38 39 40 41 42
-199.3240584 -296.3535417 -150.8361583 -167.5069815 -130.1358517 -33.1260239
43 44 45 46 47 48
20.7054250 56.7277224 -102.3883087 -22.5220928 -46.1607908 -146.9948815
49 50 51 52 53 54
-146.4007782 -362.0663179 -242.8433443 -167.3259609 -0.4472754 142.8694318
55 56 57 58 59 60
144.3520484 59.2655007 -27.8852973 -45.7541549 34.9140265 -68.3482582
> postscript(file="/var/www/html/rcomp/tmp/6igtm1258724818.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
0 120.2209060 NA
1 70.3769875 120.2209060
2 134.4340518 70.3769875
3 139.8078233 134.4340518
4 250.9389657 139.8078233
5 374.0576385 250.9389657
6 221.6838669 374.0576385
7 75.0799358 221.6838669
8 55.6766809 75.0799358
9 -103.8380608 55.6766809
10 81.6419140 -103.8380608
11 74.9612630 81.6419140
12 -169.2688966 74.9612630
13 -494.7364018 -169.2688966
14 -414.5704925 -494.7364018
15 -309.1744236 -414.5704925
16 -124.9246084 -309.1744236
17 155.3920988 -124.9246084
18 221.8301206 155.3920988
19 331.4760047 221.8301206
20 360.7632286 331.4760047
21 306.6419140 360.7632286
22 236.8399484 306.6419140
23 157.6392722 236.8399484
24 53.4956603 157.6392722
25 18.2209060 53.4956603
26 108.4858325 18.2209060
27 -56.7344993 108.4858325
28 43.9881046 -56.7344993
29 219.2825145 43.9881046
30 131.9952907 219.2825145
31 33.6411747 131.9952907
32 -134.4079643 33.6411747
33 -166.5292788 -134.4079643
34 -15.0493041 -166.5292788
35 -91.7522524 -15.0493041
36 -199.3240584 -91.7522524
37 -296.3535417 -199.3240584
38 -150.8361583 -296.3535417
39 -167.5069815 -150.8361583
40 -130.1358517 -167.5069815
41 -33.1260239 -130.1358517
42 20.7054250 -33.1260239
43 56.7277224 20.7054250
44 -102.3883087 56.7277224
45 -22.5220928 -102.3883087
46 -46.1607908 -22.5220928
47 -146.9948815 -46.1607908
48 -146.4007782 -146.9948815
49 -362.0663179 -146.4007782
50 -242.8433443 -362.0663179
51 -167.3259609 -242.8433443
52 -0.4472754 -167.3259609
53 142.8694318 -0.4472754
54 144.3520484 142.8694318
55 59.2655007 144.3520484
56 -27.8852973 59.2655007
57 -45.7541549 -27.8852973
58 34.9140265 -45.7541549
59 -68.3482582 34.9140265
60 NA -68.3482582
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 70.3769875 120.2209060
[2,] 134.4340518 70.3769875
[3,] 139.8078233 134.4340518
[4,] 250.9389657 139.8078233
[5,] 374.0576385 250.9389657
[6,] 221.6838669 374.0576385
[7,] 75.0799358 221.6838669
[8,] 55.6766809 75.0799358
[9,] -103.8380608 55.6766809
[10,] 81.6419140 -103.8380608
[11,] 74.9612630 81.6419140
[12,] -169.2688966 74.9612630
[13,] -494.7364018 -169.2688966
[14,] -414.5704925 -494.7364018
[15,] -309.1744236 -414.5704925
[16,] -124.9246084 -309.1744236
[17,] 155.3920988 -124.9246084
[18,] 221.8301206 155.3920988
[19,] 331.4760047 221.8301206
[20,] 360.7632286 331.4760047
[21,] 306.6419140 360.7632286
[22,] 236.8399484 306.6419140
[23,] 157.6392722 236.8399484
[24,] 53.4956603 157.6392722
[25,] 18.2209060 53.4956603
[26,] 108.4858325 18.2209060
[27,] -56.7344993 108.4858325
[28,] 43.9881046 -56.7344993
[29,] 219.2825145 43.9881046
[30,] 131.9952907 219.2825145
[31,] 33.6411747 131.9952907
[32,] -134.4079643 33.6411747
[33,] -166.5292788 -134.4079643
[34,] -15.0493041 -166.5292788
[35,] -91.7522524 -15.0493041
[36,] -199.3240584 -91.7522524
[37,] -296.3535417 -199.3240584
[38,] -150.8361583 -296.3535417
[39,] -167.5069815 -150.8361583
[40,] -130.1358517 -167.5069815
[41,] -33.1260239 -130.1358517
[42,] 20.7054250 -33.1260239
[43,] 56.7277224 20.7054250
[44,] -102.3883087 56.7277224
[45,] -22.5220928 -102.3883087
[46,] -46.1607908 -22.5220928
[47,] -146.9948815 -46.1607908
[48,] -146.4007782 -146.9948815
[49,] -362.0663179 -146.4007782
[50,] -242.8433443 -362.0663179
[51,] -167.3259609 -242.8433443
[52,] -0.4472754 -167.3259609
[53,] 142.8694318 -0.4472754
[54,] 144.3520484 142.8694318
[55,] 59.2655007 144.3520484
[56,] -27.8852973 59.2655007
[57,] -45.7541549 -27.8852973
[58,] 34.9140265 -45.7541549
[59,] -68.3482582 34.9140265
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 70.3769875 120.2209060
2 134.4340518 70.3769875
3 139.8078233 134.4340518
4 250.9389657 139.8078233
5 374.0576385 250.9389657
6 221.6838669 374.0576385
7 75.0799358 221.6838669
8 55.6766809 75.0799358
9 -103.8380608 55.6766809
10 81.6419140 -103.8380608
11 74.9612630 81.6419140
12 -169.2688966 74.9612630
13 -494.7364018 -169.2688966
14 -414.5704925 -494.7364018
15 -309.1744236 -414.5704925
16 -124.9246084 -309.1744236
17 155.3920988 -124.9246084
18 221.8301206 155.3920988
19 331.4760047 221.8301206
20 360.7632286 331.4760047
21 306.6419140 360.7632286
22 236.8399484 306.6419140
23 157.6392722 236.8399484
24 53.4956603 157.6392722
25 18.2209060 53.4956603
26 108.4858325 18.2209060
27 -56.7344993 108.4858325
28 43.9881046 -56.7344993
29 219.2825145 43.9881046
30 131.9952907 219.2825145
31 33.6411747 131.9952907
32 -134.4079643 33.6411747
33 -166.5292788 -134.4079643
34 -15.0493041 -166.5292788
35 -91.7522524 -15.0493041
36 -199.3240584 -91.7522524
37 -296.3535417 -199.3240584
38 -150.8361583 -296.3535417
39 -167.5069815 -150.8361583
40 -130.1358517 -167.5069815
41 -33.1260239 -130.1358517
42 20.7054250 -33.1260239
43 56.7277224 20.7054250
44 -102.3883087 56.7277224
45 -22.5220928 -102.3883087
46 -46.1607908 -22.5220928
47 -146.9948815 -46.1607908
48 -146.4007782 -146.9948815
49 -362.0663179 -146.4007782
50 -242.8433443 -362.0663179
51 -167.3259609 -242.8433443
52 -0.4472754 -167.3259609
53 142.8694318 -0.4472754
54 144.3520484 142.8694318
55 59.2655007 144.3520484
56 -27.8852973 59.2655007
57 -45.7541549 -27.8852973
58 34.9140265 -45.7541549
59 -68.3482582 34.9140265
> 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/7z1no1258724818.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8je9a1258724818.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9m4jf1258724818.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10tbfz1258724818.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11d7so1258724818.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/129w2i1258724818.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/1378sv1258724819.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/14d1cn1258724819.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/15e2e01258724819.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/16fsfx1258724819.tab")
+ }
>
> system("convert tmp/1gb101258724818.ps tmp/1gb101258724818.png")
> system("convert tmp/2kb5n1258724818.ps tmp/2kb5n1258724818.png")
> system("convert tmp/3m6q91258724818.ps tmp/3m6q91258724818.png")
> system("convert tmp/4dk7k1258724818.ps tmp/4dk7k1258724818.png")
> system("convert tmp/5bvw41258724818.ps tmp/5bvw41258724818.png")
> system("convert tmp/6igtm1258724818.ps tmp/6igtm1258724818.png")
> system("convert tmp/7z1no1258724818.ps tmp/7z1no1258724818.png")
> system("convert tmp/8je9a1258724818.ps tmp/8je9a1258724818.png")
> system("convert tmp/9m4jf1258724818.ps tmp/9m4jf1258724818.png")
> system("convert tmp/10tbfz1258724818.ps tmp/10tbfz1258724818.png")
>
>
> proc.time()
user system elapsed
2.482 1.568 2.898