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 = '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 t
1 6539 2605 1
2 6699 2682 2
3 6962 2755 3
4 6981 2760 4
5 7024 2735 5
6 6940 2659 6
7 6774 2654 7
8 6671 2670 8
9 6965 2785 9
10 6969 2845 10
11 6822 2723 11
12 6878 2746 12
13 6691 2767 13
14 6837 2940 14
15 7018 2977 15
16 7167 2993 16
17 7076 2892 17
18 7171 2824 18
19 7093 2771 19
20 6971 2686 20
21 7142 2738 21
22 7047 2723 22
23 6999 2731 23
24 6650 2632 24
25 6475 2606 25
26 6437 2605 26
27 6639 2646 27
28 6422 2627 28
29 6272 2535 29
30 6232 2456 30
31 6003 2404 31
32 5673 2319 32
33 6050 2519 33
34 5977 2504 34
35 5796 2382 35
36 5752 2394 36
37 5609 2381 37
38 5839 2501 38
39 6069 2532 39
40 6006 2515 40
41 5809 2429 41
42 5797 2389 42
43 5502 2261 43
44 5568 2272 44
45 5864 2439 45
46 5764 2373 46
47 5615 2327 47
48 5615 2364 48
49 5681 2388 49
50 5915 2553 50
51 6334 2663 51
52 6494 2694 52
53 6620 2679 53
54 6578 2611 54
55 6495 2580 55
56 6538 2627 56
57 6737 2732 57
58 6651 2707 58
59 6530 2633 59
60 6563 2683 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `Landbouw-Mannen` t
6.545 2.512 -4.284
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-495.168 -123.005 -1.208 116.247 347.266
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 6.5453 424.8576 0.015 0.98776
`Landbouw-Mannen` 2.5121 0.1529 16.433 < 2e-16 ***
t -4.2840 1.5304 -2.799 0.00698 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 178 on 57 degrees of freedom
Multiple R-squared: 0.8831, Adjusted R-squared: 0.879
F-statistic: 215.2 on 2 and 57 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,] 0.006333351 0.0126667026 0.9936666487
[2,] 0.049844599 0.0996891988 0.9501554006
[3,] 0.144077606 0.2881552115 0.8559223942
[4,] 0.118576213 0.2371524258 0.8814237871
[5,] 0.122826847 0.2456536941 0.8771731530
[6,] 0.071571717 0.1431434345 0.9284282828
[7,] 0.038634327 0.0772686548 0.9613656726
[8,] 0.059640567 0.1192811334 0.9403594333
[9,] 0.163637570 0.3272751394 0.8363624303
[10,] 0.194943321 0.3898866427 0.8050566787
[11,] 0.298981658 0.5979633156 0.7010183422
[12,] 0.380338519 0.7606770376 0.6196614812
[13,] 0.512033153 0.9759336937 0.4879668468
[14,] 0.490665409 0.9813308172 0.5093345914
[15,] 0.448617288 0.8972345764 0.5513827118
[16,] 0.486497006 0.9729940112 0.5135029944
[17,] 0.473630910 0.9472618205 0.5263690898
[18,] 0.454996873 0.9099937453 0.5450031274
[19,] 0.641132569 0.7177348627 0.3588674314
[20,] 0.802695329 0.3946093429 0.1973046714
[21,] 0.857735946 0.2845281073 0.1422640537
[22,] 0.852793104 0.2944137919 0.1472068960
[23,] 0.869095579 0.2618088429 0.1309044214
[24,] 0.884767303 0.2304653932 0.1152326966
[25,] 0.951079869 0.0978402622 0.0489201311
[26,] 0.982359722 0.0352805566 0.0176402783
[27,] 0.991966498 0.0160670042 0.0080335021
[28,] 0.992098144 0.0158037126 0.0079018563
[29,] 0.991302891 0.0173942188 0.0086971094
[30,] 0.992893203 0.0142135940 0.0071067970
[31,] 0.992059397 0.0158812051 0.0079406025
[32,] 0.990347551 0.0193048971 0.0096524486
[33,] 0.989030940 0.0219381198 0.0109690599
[34,] 0.982449737 0.0351005251 0.0175502626
[35,] 0.971722218 0.0565555635 0.0282777817
[36,] 0.955283401 0.0894331972 0.0447165986
[37,] 0.943523610 0.1129527791 0.0564763895
[38,] 0.922786179 0.1544276425 0.0772138213
[39,] 0.916289248 0.1674215037 0.0837107519
[40,] 0.884377635 0.2312447309 0.1156223655
[41,] 0.866735932 0.2665281360 0.1332640680
[42,] 0.823170543 0.3536589143 0.1768294572
[43,] 0.744302197 0.5113956051 0.2556978026
[44,] 0.654998739 0.6900025217 0.3450012609
[45,] 0.943203039 0.1135939216 0.0567969608
[46,] 0.985445490 0.0291090205 0.0145545102
[47,] 0.999153230 0.0016935391 0.0008467696
[48,] 0.999701703 0.0005965945 0.0002982972
[49,] 0.997713345 0.0045733095 0.0022866548
> postscript(file="/var/www/html/rcomp/tmp/1ur4m1258726430.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2a2zn1258726430.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3tmc11258726430.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/478zf1258726430.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5en9v1258726430.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
-7.3032436 -36.4516174 47.4484417 58.1718587 168.2585217 279.4627031
7 8 9 10 11 12
130.3072021 -8.6025712 0.7889433 -141.6535910 22.1075678 24.6130371
13 14 15 16 17 18
-210.8572772 -495.1680385 -402.8320841 -289.7418574 -122.7349709 147.3723449
19 20 21 22 23 24
206.7980376 302.6111929 347.2655242 294.2311052 230.4181976 134.4008677
25 26 27 28 29 30
28.9996389 -2.2042949 101.0832267 -63.9027595 21.4951532 184.2356592
31 32 33 34 35 36
90.1492437 -22.0376010 -143.1752838 -174.2097028 -44.4485440 -114.3098845
37 38 39 40 41 42
-220.3685199 -287.5375464 -131.1289428 -147.1391453 -123.8138819 -31.0455958
43 44 45 46 47 48
-0.2117878 42.4389799 -76.7991321 -6.7160327 -35.8750974 -124.5391430
49 50 51 52 53 54
-114.5457820 -290.7596776 -143.8076221 -57.3990184 110.5665626 243.6738784
55 56 57 58 59 60
242.8331906 172.0480630 111.5606596 92.6473226 161.8272876 73.5058354
> postscript(file="/var/www/html/rcomp/tmp/6ov6w1258726430.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 -7.3032436 NA
1 -36.4516174 -7.3032436
2 47.4484417 -36.4516174
3 58.1718587 47.4484417
4 168.2585217 58.1718587
5 279.4627031 168.2585217
6 130.3072021 279.4627031
7 -8.6025712 130.3072021
8 0.7889433 -8.6025712
9 -141.6535910 0.7889433
10 22.1075678 -141.6535910
11 24.6130371 22.1075678
12 -210.8572772 24.6130371
13 -495.1680385 -210.8572772
14 -402.8320841 -495.1680385
15 -289.7418574 -402.8320841
16 -122.7349709 -289.7418574
17 147.3723449 -122.7349709
18 206.7980376 147.3723449
19 302.6111929 206.7980376
20 347.2655242 302.6111929
21 294.2311052 347.2655242
22 230.4181976 294.2311052
23 134.4008677 230.4181976
24 28.9996389 134.4008677
25 -2.2042949 28.9996389
26 101.0832267 -2.2042949
27 -63.9027595 101.0832267
28 21.4951532 -63.9027595
29 184.2356592 21.4951532
30 90.1492437 184.2356592
31 -22.0376010 90.1492437
32 -143.1752838 -22.0376010
33 -174.2097028 -143.1752838
34 -44.4485440 -174.2097028
35 -114.3098845 -44.4485440
36 -220.3685199 -114.3098845
37 -287.5375464 -220.3685199
38 -131.1289428 -287.5375464
39 -147.1391453 -131.1289428
40 -123.8138819 -147.1391453
41 -31.0455958 -123.8138819
42 -0.2117878 -31.0455958
43 42.4389799 -0.2117878
44 -76.7991321 42.4389799
45 -6.7160327 -76.7991321
46 -35.8750974 -6.7160327
47 -124.5391430 -35.8750974
48 -114.5457820 -124.5391430
49 -290.7596776 -114.5457820
50 -143.8076221 -290.7596776
51 -57.3990184 -143.8076221
52 110.5665626 -57.3990184
53 243.6738784 110.5665626
54 242.8331906 243.6738784
55 172.0480630 242.8331906
56 111.5606596 172.0480630
57 92.6473226 111.5606596
58 161.8272876 92.6473226
59 73.5058354 161.8272876
60 NA 73.5058354
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -36.4516174 -7.3032436
[2,] 47.4484417 -36.4516174
[3,] 58.1718587 47.4484417
[4,] 168.2585217 58.1718587
[5,] 279.4627031 168.2585217
[6,] 130.3072021 279.4627031
[7,] -8.6025712 130.3072021
[8,] 0.7889433 -8.6025712
[9,] -141.6535910 0.7889433
[10,] 22.1075678 -141.6535910
[11,] 24.6130371 22.1075678
[12,] -210.8572772 24.6130371
[13,] -495.1680385 -210.8572772
[14,] -402.8320841 -495.1680385
[15,] -289.7418574 -402.8320841
[16,] -122.7349709 -289.7418574
[17,] 147.3723449 -122.7349709
[18,] 206.7980376 147.3723449
[19,] 302.6111929 206.7980376
[20,] 347.2655242 302.6111929
[21,] 294.2311052 347.2655242
[22,] 230.4181976 294.2311052
[23,] 134.4008677 230.4181976
[24,] 28.9996389 134.4008677
[25,] -2.2042949 28.9996389
[26,] 101.0832267 -2.2042949
[27,] -63.9027595 101.0832267
[28,] 21.4951532 -63.9027595
[29,] 184.2356592 21.4951532
[30,] 90.1492437 184.2356592
[31,] -22.0376010 90.1492437
[32,] -143.1752838 -22.0376010
[33,] -174.2097028 -143.1752838
[34,] -44.4485440 -174.2097028
[35,] -114.3098845 -44.4485440
[36,] -220.3685199 -114.3098845
[37,] -287.5375464 -220.3685199
[38,] -131.1289428 -287.5375464
[39,] -147.1391453 -131.1289428
[40,] -123.8138819 -147.1391453
[41,] -31.0455958 -123.8138819
[42,] -0.2117878 -31.0455958
[43,] 42.4389799 -0.2117878
[44,] -76.7991321 42.4389799
[45,] -6.7160327 -76.7991321
[46,] -35.8750974 -6.7160327
[47,] -124.5391430 -35.8750974
[48,] -114.5457820 -124.5391430
[49,] -290.7596776 -114.5457820
[50,] -143.8076221 -290.7596776
[51,] -57.3990184 -143.8076221
[52,] 110.5665626 -57.3990184
[53,] 243.6738784 110.5665626
[54,] 242.8331906 243.6738784
[55,] 172.0480630 242.8331906
[56,] 111.5606596 172.0480630
[57,] 92.6473226 111.5606596
[58,] 161.8272876 92.6473226
[59,] 73.5058354 161.8272876
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -36.4516174 -7.3032436
2 47.4484417 -36.4516174
3 58.1718587 47.4484417
4 168.2585217 58.1718587
5 279.4627031 168.2585217
6 130.3072021 279.4627031
7 -8.6025712 130.3072021
8 0.7889433 -8.6025712
9 -141.6535910 0.7889433
10 22.1075678 -141.6535910
11 24.6130371 22.1075678
12 -210.8572772 24.6130371
13 -495.1680385 -210.8572772
14 -402.8320841 -495.1680385
15 -289.7418574 -402.8320841
16 -122.7349709 -289.7418574
17 147.3723449 -122.7349709
18 206.7980376 147.3723449
19 302.6111929 206.7980376
20 347.2655242 302.6111929
21 294.2311052 347.2655242
22 230.4181976 294.2311052
23 134.4008677 230.4181976
24 28.9996389 134.4008677
25 -2.2042949 28.9996389
26 101.0832267 -2.2042949
27 -63.9027595 101.0832267
28 21.4951532 -63.9027595
29 184.2356592 21.4951532
30 90.1492437 184.2356592
31 -22.0376010 90.1492437
32 -143.1752838 -22.0376010
33 -174.2097028 -143.1752838
34 -44.4485440 -174.2097028
35 -114.3098845 -44.4485440
36 -220.3685199 -114.3098845
37 -287.5375464 -220.3685199
38 -131.1289428 -287.5375464
39 -147.1391453 -131.1289428
40 -123.8138819 -147.1391453
41 -31.0455958 -123.8138819
42 -0.2117878 -31.0455958
43 42.4389799 -0.2117878
44 -76.7991321 42.4389799
45 -6.7160327 -76.7991321
46 -35.8750974 -6.7160327
47 -124.5391430 -35.8750974
48 -114.5457820 -124.5391430
49 -290.7596776 -114.5457820
50 -143.8076221 -290.7596776
51 -57.3990184 -143.8076221
52 110.5665626 -57.3990184
53 243.6738784 110.5665626
54 242.8331906 243.6738784
55 172.0480630 242.8331906
56 111.5606596 172.0480630
57 92.6473226 111.5606596
58 161.8272876 92.6473226
59 73.5058354 161.8272876
> 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/7dg9n1258726430.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/88knc1258726430.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9gczj1258726430.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10dcmc1258726430.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11cxi81258726430.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/12ajk91258726430.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/13cmle1258726430.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/148bhj1258726430.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/150l4d1258726430.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/162bot1258726430.tab")
+ }
>
> system("convert tmp/1ur4m1258726430.ps tmp/1ur4m1258726430.png")
> system("convert tmp/2a2zn1258726430.ps tmp/2a2zn1258726430.png")
> system("convert tmp/3tmc11258726430.ps tmp/3tmc11258726430.png")
> system("convert tmp/478zf1258726430.ps tmp/478zf1258726430.png")
> system("convert tmp/5en9v1258726430.ps tmp/5en9v1258726430.png")
> system("convert tmp/6ov6w1258726430.ps tmp/6ov6w1258726430.png")
> system("convert tmp/7dg9n1258726430.ps tmp/7dg9n1258726430.png")
> system("convert tmp/88knc1258726430.ps tmp/88knc1258726430.png")
> system("convert tmp/9gczj1258726430.ps tmp/9gczj1258726430.png")
> system("convert tmp/10dcmc1258726430.ps tmp/10dcmc1258726430.png")
>
>
> proc.time()
user system elapsed
2.494 1.575 2.931