R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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Type 'demo()' for some demos, 'help()' for on-line help, or
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> x <- array(list(97.3,0,97.4,0,97.5,0,95.5,0,95.3,0,95.4,0,95.4,0,95.4,0,95.5,0,94.6,0,95.2,0,95.2,0,94.7,0,94.7,0,94.7,0,95.3,0,94.7,0,94.8,0,94.9,0,95.4,0,96,0,95.9,0,95.8,0,95.8,0,95.1,0,95.2,0,95.2,0,95.3,0,95.4,0,95.3,0,95.3,0,95,0,94.9,0,95.7,0,95.7,0,96.3,0,91.7,1,92.2,1,92.2,1,92.6,1,93,1,93,1,93,1,93.7,1,93.1,1,93.1,1,93.2,1,93.2,1,93,1,93.7,1,94,1,93.1,1,94.2,1,94.2,1,93.5,1,95,1,93.7,1,93.9,1,94.6,1,93.8,1,91.2,1,91.4,1,91.3,1,91.5,1,91.5,1,91.5,1,91.3,1,92.8,1),dim=c(2,68),dimnames=list(c('X','Y'),1:68))
> y <- array(NA,dim=c(2,68),dimnames=list(c('X','Y'),1:68))
> 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
X Y t
1 97.3 0 1
2 97.4 0 2
3 97.5 0 3
4 95.5 0 4
5 95.3 0 5
6 95.4 0 6
7 95.4 0 7
8 95.4 0 8
9 95.5 0 9
10 94.6 0 10
11 95.2 0 11
12 95.2 0 12
13 94.7 0 13
14 94.7 0 14
15 94.7 0 15
16 95.3 0 16
17 94.7 0 17
18 94.8 0 18
19 94.9 0 19
20 95.4 0 20
21 96.0 0 21
22 95.9 0 22
23 95.8 0 23
24 95.8 0 24
25 95.1 0 25
26 95.2 0 26
27 95.2 0 27
28 95.3 0 28
29 95.4 0 29
30 95.3 0 30
31 95.3 0 31
32 95.0 0 32
33 94.9 0 33
34 95.7 0 34
35 95.7 0 35
36 96.3 0 36
37 91.7 1 37
38 92.2 1 38
39 92.2 1 39
40 92.6 1 40
41 93.0 1 41
42 93.0 1 42
43 93.0 1 43
44 93.7 1 44
45 93.1 1 45
46 93.1 1 46
47 93.2 1 47
48 93.2 1 48
49 93.0 1 49
50 93.7 1 50
51 94.0 1 51
52 93.1 1 52
53 94.2 1 53
54 94.2 1 54
55 93.5 1 55
56 95.0 1 56
57 93.7 1 57
58 93.9 1 58
59 94.6 1 59
60 93.8 1 60
61 91.2 1 61
62 91.4 1 62
63 91.3 1 63
64 91.5 1 64
65 91.5 1 65
66 91.5 1 66
67 91.3 1 67
68 92.8 1 68
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Y t
95.83118 -1.88424 -0.01970
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.54502 -0.55731 -0.09944 0.54367 2.15646
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 95.8312 0.2477 386.950 < 2e-16 ***
Y -1.8842 0.4247 -4.437 3.60e-05 ***
t -0.0197 0.0108 -1.825 0.0727 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.8782 on 65 degrees of freedom
Multiple R-squared: 0.6929, Adjusted R-squared: 0.6834
F-statistic: 73.32 on 2 and 65 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,] 0.466844142 0.93368828 0.5331559
[2,] 0.379092755 0.75818551 0.6209072
[3,] 0.328274411 0.65654882 0.6717256
[4,] 0.311585158 0.62317032 0.6884148
[5,] 0.212150455 0.42430091 0.7878495
[6,] 0.200618916 0.40123783 0.7993811
[7,] 0.186142891 0.37228578 0.8138571
[8,] 0.132648955 0.26529791 0.8673510
[9,] 0.098433613 0.19686723 0.9015664
[10,] 0.076920348 0.15384070 0.9230797
[11,] 0.107233377 0.21446675 0.8927666
[12,] 0.084263040 0.16852608 0.9157370
[13,] 0.071614416 0.14322883 0.9283856
[14,] 0.065651750 0.13130350 0.9343483
[15,] 0.089565900 0.17913180 0.9104341
[16,] 0.179739805 0.35947961 0.8202602
[17,] 0.224397237 0.44879447 0.7756028
[18,] 0.229943358 0.45988672 0.7700566
[19,] 0.220866580 0.44173316 0.7791334
[20,] 0.171429380 0.34285876 0.8285706
[21,] 0.131206373 0.26241275 0.8687936
[22,] 0.098420899 0.19684180 0.9015791
[23,] 0.073380254 0.14676051 0.9266197
[24,] 0.054726281 0.10945256 0.9452737
[25,] 0.038868969 0.07773794 0.9611310
[26,] 0.026995825 0.05399165 0.9730042
[27,] 0.018604044 0.03720809 0.9813960
[28,] 0.013685672 0.02737134 0.9863143
[29,] 0.011251074 0.02250215 0.9887489
[30,] 0.009009781 0.01801956 0.9909902
[31,] 0.010653182 0.02130636 0.9893468
[32,] 0.012171713 0.02434343 0.9878283
[33,] 0.012168145 0.02433629 0.9878319
[34,] 0.013439154 0.02687831 0.9865608
[35,] 0.013952692 0.02790538 0.9860473
[36,] 0.013996889 0.02799378 0.9860031
[37,] 0.013582913 0.02716583 0.9864171
[38,] 0.013380843 0.02676169 0.9866192
[39,] 0.014217638 0.02843528 0.9857824
[40,] 0.013121734 0.02624347 0.9868783
[41,] 0.012810689 0.02562138 0.9871893
[42,] 0.012798489 0.02559698 0.9872015
[43,] 0.013811414 0.02762283 0.9861886
[44,] 0.020515982 0.04103196 0.9794840
[45,] 0.021918243 0.04383649 0.9780818
[46,] 0.021643636 0.04328727 0.9783564
[47,] 0.034341114 0.06868223 0.9656589
[48,] 0.032577291 0.06515458 0.9674227
[49,] 0.027196348 0.05439270 0.9728037
[50,] 0.022785131 0.04557026 0.9772149
[51,] 0.039732513 0.07946503 0.9602675
[52,] 0.023706476 0.04741295 0.9762935
[53,] 0.016710240 0.03342048 0.9832898
[54,] 0.108166269 0.21633254 0.8918337
[55,] 0.850379653 0.29924069 0.1496203
[56,] 0.787980867 0.42403827 0.2120191
[57,] 0.698590232 0.60281954 0.3014098
> postscript(file="/var/www/html/rcomp/tmp/1rcst1227789504.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2b6qa1227789504.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3hnr51227789504.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4ob7m1227789504.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/51axq1227789504.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 = 68
Frequency = 1
1 2 3 4 5 6
1.48852009 1.60822370 1.72792731 -0.25236907 -0.43266546 -0.31296184
7 8 9 10 11 12
-0.29325823 -0.27355461 -0.15385100 -1.03414739 -0.41444377 -0.39474016
13 14 15 16 17 18
-0.87503654 -0.85533293 -0.83562932 -0.21592570 -0.79622209 -0.67651847
19 20 21 22 23 24
-0.55681486 -0.03711125 0.58259237 0.50229598 0.42199960 0.44170321
25 26 27 28 29 30
-0.23859318 -0.11888956 -0.09918595 0.02051767 0.14022128 0.05992490
31 32 33 34 35 36
0.07962851 -0.20066788 -0.28096426 0.53873935 0.55844297 1.17814658
37 38 39 40 41 42
-1.51790602 -0.99820240 -0.97849879 -0.55879518 -0.13909156 -0.11938795
43 44 45 46 47 48
-0.09968433 0.62001928 0.03972289 0.05942651 0.17913012 0.19883374
49 50 51 52 53 54
0.01853735 0.73824096 1.05794458 0.17764819 1.29735181 1.31705542
55 56 57 58 59 60
0.63675904 2.15646265 0.87616626 1.09586988 1.81557349 1.03527711
61 62 63 64 65 66
-1.54501928 -1.32531567 -1.40561205 -1.18590844 -1.16620482 -1.14650121
67 68
-1.32679760 0.19290602
> postscript(file="/var/www/html/rcomp/tmp/6p5bf1227789504.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 = 68
Frequency = 1
lag(myerror, k = 1) myerror
0 1.48852009 NA
1 1.60822370 1.48852009
2 1.72792731 1.60822370
3 -0.25236907 1.72792731
4 -0.43266546 -0.25236907
5 -0.31296184 -0.43266546
6 -0.29325823 -0.31296184
7 -0.27355461 -0.29325823
8 -0.15385100 -0.27355461
9 -1.03414739 -0.15385100
10 -0.41444377 -1.03414739
11 -0.39474016 -0.41444377
12 -0.87503654 -0.39474016
13 -0.85533293 -0.87503654
14 -0.83562932 -0.85533293
15 -0.21592570 -0.83562932
16 -0.79622209 -0.21592570
17 -0.67651847 -0.79622209
18 -0.55681486 -0.67651847
19 -0.03711125 -0.55681486
20 0.58259237 -0.03711125
21 0.50229598 0.58259237
22 0.42199960 0.50229598
23 0.44170321 0.42199960
24 -0.23859318 0.44170321
25 -0.11888956 -0.23859318
26 -0.09918595 -0.11888956
27 0.02051767 -0.09918595
28 0.14022128 0.02051767
29 0.05992490 0.14022128
30 0.07962851 0.05992490
31 -0.20066788 0.07962851
32 -0.28096426 -0.20066788
33 0.53873935 -0.28096426
34 0.55844297 0.53873935
35 1.17814658 0.55844297
36 -1.51790602 1.17814658
37 -0.99820240 -1.51790602
38 -0.97849879 -0.99820240
39 -0.55879518 -0.97849879
40 -0.13909156 -0.55879518
41 -0.11938795 -0.13909156
42 -0.09968433 -0.11938795
43 0.62001928 -0.09968433
44 0.03972289 0.62001928
45 0.05942651 0.03972289
46 0.17913012 0.05942651
47 0.19883374 0.17913012
48 0.01853735 0.19883374
49 0.73824096 0.01853735
50 1.05794458 0.73824096
51 0.17764819 1.05794458
52 1.29735181 0.17764819
53 1.31705542 1.29735181
54 0.63675904 1.31705542
55 2.15646265 0.63675904
56 0.87616626 2.15646265
57 1.09586988 0.87616626
58 1.81557349 1.09586988
59 1.03527711 1.81557349
60 -1.54501928 1.03527711
61 -1.32531567 -1.54501928
62 -1.40561205 -1.32531567
63 -1.18590844 -1.40561205
64 -1.16620482 -1.18590844
65 -1.14650121 -1.16620482
66 -1.32679760 -1.14650121
67 0.19290602 -1.32679760
68 NA 0.19290602
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.60822370 1.48852009
[2,] 1.72792731 1.60822370
[3,] -0.25236907 1.72792731
[4,] -0.43266546 -0.25236907
[5,] -0.31296184 -0.43266546
[6,] -0.29325823 -0.31296184
[7,] -0.27355461 -0.29325823
[8,] -0.15385100 -0.27355461
[9,] -1.03414739 -0.15385100
[10,] -0.41444377 -1.03414739
[11,] -0.39474016 -0.41444377
[12,] -0.87503654 -0.39474016
[13,] -0.85533293 -0.87503654
[14,] -0.83562932 -0.85533293
[15,] -0.21592570 -0.83562932
[16,] -0.79622209 -0.21592570
[17,] -0.67651847 -0.79622209
[18,] -0.55681486 -0.67651847
[19,] -0.03711125 -0.55681486
[20,] 0.58259237 -0.03711125
[21,] 0.50229598 0.58259237
[22,] 0.42199960 0.50229598
[23,] 0.44170321 0.42199960
[24,] -0.23859318 0.44170321
[25,] -0.11888956 -0.23859318
[26,] -0.09918595 -0.11888956
[27,] 0.02051767 -0.09918595
[28,] 0.14022128 0.02051767
[29,] 0.05992490 0.14022128
[30,] 0.07962851 0.05992490
[31,] -0.20066788 0.07962851
[32,] -0.28096426 -0.20066788
[33,] 0.53873935 -0.28096426
[34,] 0.55844297 0.53873935
[35,] 1.17814658 0.55844297
[36,] -1.51790602 1.17814658
[37,] -0.99820240 -1.51790602
[38,] -0.97849879 -0.99820240
[39,] -0.55879518 -0.97849879
[40,] -0.13909156 -0.55879518
[41,] -0.11938795 -0.13909156
[42,] -0.09968433 -0.11938795
[43,] 0.62001928 -0.09968433
[44,] 0.03972289 0.62001928
[45,] 0.05942651 0.03972289
[46,] 0.17913012 0.05942651
[47,] 0.19883374 0.17913012
[48,] 0.01853735 0.19883374
[49,] 0.73824096 0.01853735
[50,] 1.05794458 0.73824096
[51,] 0.17764819 1.05794458
[52,] 1.29735181 0.17764819
[53,] 1.31705542 1.29735181
[54,] 0.63675904 1.31705542
[55,] 2.15646265 0.63675904
[56,] 0.87616626 2.15646265
[57,] 1.09586988 0.87616626
[58,] 1.81557349 1.09586988
[59,] 1.03527711 1.81557349
[60,] -1.54501928 1.03527711
[61,] -1.32531567 -1.54501928
[62,] -1.40561205 -1.32531567
[63,] -1.18590844 -1.40561205
[64,] -1.16620482 -1.18590844
[65,] -1.14650121 -1.16620482
[66,] -1.32679760 -1.14650121
[67,] 0.19290602 -1.32679760
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.60822370 1.48852009
2 1.72792731 1.60822370
3 -0.25236907 1.72792731
4 -0.43266546 -0.25236907
5 -0.31296184 -0.43266546
6 -0.29325823 -0.31296184
7 -0.27355461 -0.29325823
8 -0.15385100 -0.27355461
9 -1.03414739 -0.15385100
10 -0.41444377 -1.03414739
11 -0.39474016 -0.41444377
12 -0.87503654 -0.39474016
13 -0.85533293 -0.87503654
14 -0.83562932 -0.85533293
15 -0.21592570 -0.83562932
16 -0.79622209 -0.21592570
17 -0.67651847 -0.79622209
18 -0.55681486 -0.67651847
19 -0.03711125 -0.55681486
20 0.58259237 -0.03711125
21 0.50229598 0.58259237
22 0.42199960 0.50229598
23 0.44170321 0.42199960
24 -0.23859318 0.44170321
25 -0.11888956 -0.23859318
26 -0.09918595 -0.11888956
27 0.02051767 -0.09918595
28 0.14022128 0.02051767
29 0.05992490 0.14022128
30 0.07962851 0.05992490
31 -0.20066788 0.07962851
32 -0.28096426 -0.20066788
33 0.53873935 -0.28096426
34 0.55844297 0.53873935
35 1.17814658 0.55844297
36 -1.51790602 1.17814658
37 -0.99820240 -1.51790602
38 -0.97849879 -0.99820240
39 -0.55879518 -0.97849879
40 -0.13909156 -0.55879518
41 -0.11938795 -0.13909156
42 -0.09968433 -0.11938795
43 0.62001928 -0.09968433
44 0.03972289 0.62001928
45 0.05942651 0.03972289
46 0.17913012 0.05942651
47 0.19883374 0.17913012
48 0.01853735 0.19883374
49 0.73824096 0.01853735
50 1.05794458 0.73824096
51 0.17764819 1.05794458
52 1.29735181 0.17764819
53 1.31705542 1.29735181
54 0.63675904 1.31705542
55 2.15646265 0.63675904
56 0.87616626 2.15646265
57 1.09586988 0.87616626
58 1.81557349 1.09586988
59 1.03527711 1.81557349
60 -1.54501928 1.03527711
61 -1.32531567 -1.54501928
62 -1.40561205 -1.32531567
63 -1.18590844 -1.40561205
64 -1.16620482 -1.18590844
65 -1.14650121 -1.16620482
66 -1.32679760 -1.14650121
67 0.19290602 -1.32679760
> 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/7bpay1227789504.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8zf8o1227789504.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/913yy1227789504.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/100bkq1227789504.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/119hqn1227789504.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/12zxgv1227789504.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/130sm21227789505.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/149z4e1227789505.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/15bort1227789505.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/160lhc1227789505.tab")
+ }
> system("convert tmp/1rcst1227789504.ps tmp/1rcst1227789504.png")
> system("convert tmp/2b6qa1227789504.ps tmp/2b6qa1227789504.png")
> system("convert tmp/3hnr51227789504.ps tmp/3hnr51227789504.png")
> system("convert tmp/4ob7m1227789504.ps tmp/4ob7m1227789504.png")
> system("convert tmp/51axq1227789504.ps tmp/51axq1227789504.png")
> system("convert tmp/6p5bf1227789504.ps tmp/6p5bf1227789504.png")
> system("convert tmp/7bpay1227789504.ps tmp/7bpay1227789504.png")
> system("convert tmp/8zf8o1227789504.ps tmp/8zf8o1227789504.png")
> system("convert tmp/913yy1227789504.ps tmp/913yy1227789504.png")
> system("convert tmp/100bkq1227789504.ps tmp/100bkq1227789504.png")
>
>
> proc.time()
user system elapsed
2.793 1.744 3.390