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.
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Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
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Type 'demo()' for some demos, 'help()' for on-line help, or
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> x <- array(list(564,-0.9,581,-1,597,-0.7,587,-1.7,536,-1,524,-0.2,537,0.7,536,0.6,533,1.9,528,2.1,516,2.7,502,3.2,506,4.8,518,5.5,534,5.4,528,5.9,478,5.8,469,5.1,490,4.1,493,4.4,508,3.6,517,3.5,514,3.1,510,2.9,527,2.2,542,1.4,565,1.2,555,1.3,499,1.3,511,1.3,526,1.8,532,1.8,549,1.8,561,1.7,557,2.1,566,2,588,1.7,620,1.9,626,2.3,620,2.4,573,2.5,573,2.8,574,2.6,580,2.2,590,2.8,593,2.8,597,2.8,595,2.3,612,2.2,628,3,629,2.9,621,2.7,569,2.7,567,2.3,573,2.4,584,2.8,589,2.3,591,2,595,1.9,594,2.3),dim=c(2,60),dimnames=list(c('Y','X'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Y','X'),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 = 'Include Monthly 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
Y X M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 564 -0.9 1 0 0 0 0 0 0 0 0 0 0
2 581 -1.0 0 1 0 0 0 0 0 0 0 0 0
3 597 -0.7 0 0 1 0 0 0 0 0 0 0 0
4 587 -1.7 0 0 0 1 0 0 0 0 0 0 0
5 536 -1.0 0 0 0 0 1 0 0 0 0 0 0
6 524 -0.2 0 0 0 0 0 1 0 0 0 0 0
7 537 0.7 0 0 0 0 0 0 1 0 0 0 0
8 536 0.6 0 0 0 0 0 0 0 1 0 0 0
9 533 1.9 0 0 0 0 0 0 0 0 1 0 0
10 528 2.1 0 0 0 0 0 0 0 0 0 1 0
11 516 2.7 0 0 0 0 0 0 0 0 0 0 1
12 502 3.2 0 0 0 0 0 0 0 0 0 0 0
13 506 4.8 1 0 0 0 0 0 0 0 0 0 0
14 518 5.5 0 1 0 0 0 0 0 0 0 0 0
15 534 5.4 0 0 1 0 0 0 0 0 0 0 0
16 528 5.9 0 0 0 1 0 0 0 0 0 0 0
17 478 5.8 0 0 0 0 1 0 0 0 0 0 0
18 469 5.1 0 0 0 0 0 1 0 0 0 0 0
19 490 4.1 0 0 0 0 0 0 1 0 0 0 0
20 493 4.4 0 0 0 0 0 0 0 1 0 0 0
21 508 3.6 0 0 0 0 0 0 0 0 1 0 0
22 517 3.5 0 0 0 0 0 0 0 0 0 1 0
23 514 3.1 0 0 0 0 0 0 0 0 0 0 1
24 510 2.9 0 0 0 0 0 0 0 0 0 0 0
25 527 2.2 1 0 0 0 0 0 0 0 0 0 0
26 542 1.4 0 1 0 0 0 0 0 0 0 0 0
27 565 1.2 0 0 1 0 0 0 0 0 0 0 0
28 555 1.3 0 0 0 1 0 0 0 0 0 0 0
29 499 1.3 0 0 0 0 1 0 0 0 0 0 0
30 511 1.3 0 0 0 0 0 1 0 0 0 0 0
31 526 1.8 0 0 0 0 0 0 1 0 0 0 0
32 532 1.8 0 0 0 0 0 0 0 1 0 0 0
33 549 1.8 0 0 0 0 0 0 0 0 1 0 0
34 561 1.7 0 0 0 0 0 0 0 0 0 1 0
35 557 2.1 0 0 0 0 0 0 0 0 0 0 1
36 566 2.0 0 0 0 0 0 0 0 0 0 0 0
37 588 1.7 1 0 0 0 0 0 0 0 0 0 0
38 620 1.9 0 1 0 0 0 0 0 0 0 0 0
39 626 2.3 0 0 1 0 0 0 0 0 0 0 0
40 620 2.4 0 0 0 1 0 0 0 0 0 0 0
41 573 2.5 0 0 0 0 1 0 0 0 0 0 0
42 573 2.8 0 0 0 0 0 1 0 0 0 0 0
43 574 2.6 0 0 0 0 0 0 1 0 0 0 0
44 580 2.2 0 0 0 0 0 0 0 1 0 0 0
45 590 2.8 0 0 0 0 0 0 0 0 1 0 0
46 593 2.8 0 0 0 0 0 0 0 0 0 1 0
47 597 2.8 0 0 0 0 0 0 0 0 0 0 1
48 595 2.3 0 0 0 0 0 0 0 0 0 0 0
49 612 2.2 1 0 0 0 0 0 0 0 0 0 0
50 628 3.0 0 1 0 0 0 0 0 0 0 0 0
51 629 2.9 0 0 1 0 0 0 0 0 0 0 0
52 621 2.7 0 0 0 1 0 0 0 0 0 0 0
53 569 2.7 0 0 0 0 1 0 0 0 0 0 0
54 567 2.3 0 0 0 0 0 1 0 0 0 0 0
55 573 2.4 0 0 0 0 0 0 1 0 0 0 0
56 584 2.8 0 0 0 0 0 0 0 1 0 0 0
57 589 2.3 0 0 0 0 0 0 0 0 1 0 0
58 591 2.0 0 0 0 0 0 0 0 0 0 1 0
59 595 1.9 0 0 0 0 0 0 0 0 0 0 1
60 594 2.3 0 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
574.16240 -8.17417 1.58595 21.29381 34.18426 25.36685
M5 M6 M7 M8 M9 M10
-24.68877 -26.88877 -15.19832 -9.87135 -0.09045 3.61910
M11
2.23652
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-46.01 -31.12 -17.32 38.21 57.07
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 574.16240 18.99184 30.232 <2e-16 ***
X -8.17417 3.15510 -2.591 0.0127 *
M1 1.58595 24.40974 0.065 0.9485
M2 21.29381 24.37971 0.873 0.3869
M3 34.18426 24.37113 1.403 0.1673
M4 25.36685 24.38624 1.040 0.3036
M5 -24.68877 24.36623 -1.013 0.3161
M6 -26.88877 24.36623 -1.104 0.2754
M7 -15.19832 24.36010 -0.624 0.5357
M8 -9.87135 24.35683 -0.405 0.6871
M9 -0.09045 24.35095 -0.004 0.9971
M10 3.61910 24.35315 0.149 0.8825
M11 2.23652 24.35029 0.092 0.9272
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 38.5 on 47 degrees of freedom
Multiple R-squared: 0.3041, Adjusted R-squared: 0.1264
F-statistic: 1.712 on 12 and 47 DF, p-value: 0.09454
> 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,] 4.150375e-03 8.300749e-03 9.958496e-01
[2,] 5.833512e-04 1.166702e-03 9.994166e-01
[3,] 1.086632e-04 2.173264e-04 9.998913e-01
[4,] 9.225958e-05 1.845192e-04 9.999077e-01
[5,] 2.888106e-05 5.776211e-05 9.999711e-01
[6,] 1.363702e-05 2.727404e-05 9.999864e-01
[7,] 6.773369e-06 1.354674e-05 9.999932e-01
[8,] 5.643017e-06 1.128603e-05 9.999944e-01
[9,] 2.561005e-05 5.122009e-05 9.999744e-01
[10,] 2.408323e-04 4.816645e-04 9.997592e-01
[11,] 1.595544e-03 3.191089e-03 9.984045e-01
[12,] 1.476263e-03 2.952527e-03 9.985237e-01
[13,] 1.346021e-03 2.692042e-03 9.986540e-01
[14,] 4.922094e-03 9.844187e-03 9.950779e-01
[15,] 3.422544e-03 6.845088e-03 9.965775e-01
[16,] 4.557430e-03 9.114860e-03 9.954426e-01
[17,] 1.504648e-02 3.009296e-02 9.849535e-01
[18,] 6.292488e-02 1.258498e-01 9.370751e-01
[19,] 2.289937e-01 4.579875e-01 7.710063e-01
[20,] 8.940696e-01 2.118609e-01 1.059304e-01
[21,] 9.995308e-01 9.384955e-04 4.692477e-04
[22,] 1.000000e+00 1.769292e-08 8.846462e-09
[23,] 1.000000e+00 8.418129e-09 4.209064e-09
[24,] 1.000000e+00 3.610547e-08 1.805273e-08
[25,] 9.999999e-01 2.155284e-07 1.077642e-07
[26,] 9.999999e-01 2.283215e-07 1.141607e-07
[27,] 9.999999e-01 1.153212e-07 5.766062e-08
[28,] 9.999983e-01 3.419316e-06 1.709658e-06
[29,] 9.999967e-01 6.642438e-06 3.321219e-06
> postscript(file="/var/www/html/rcomp/tmp/10sok1260902863.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2kb471260902863.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ush71260902863.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/40m9d1260902863.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5ieqx1260902863.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
-19.105107 -22.630392 -17.068590 -26.425347 -21.647809 -24.908470 -16.242163
8 9 10 11 12 13 14
-23.386547 -25.541021 -32.615736 -38.328649 -46.005045 -30.512311 -32.498257
15 16 17 18 19 20 21
-30.206125 -23.301620 -24.063422 -36.585344 -35.449969 -35.324684 -36.644924
22 23 24 25 26 27 28
-32.171891 -37.058979 -40.457297 -30.765165 -42.012373 -33.537658 -33.902823
29 30 31 32 33 34 35
-39.847208 -25.647208 -18.250571 -17.577538 -10.358439 -2.885406 -2.233153
36 37 38 39 40 41 42
8.185946 26.147748 40.074715 36.453934 40.088769 43.961802 48.614054
43 44 45 46 47 48 49
36.288769 33.692132 38.815736 38.106186 43.488769 39.638198 54.234835
50 51 52 53 54 55 56
57.066307 44.358439 43.541021 41.596637 38.526967 33.653934 42.596637
57 58 59 60
33.728649 29.566847 34.132012 38.638198
> postscript(file="/var/www/html/rcomp/tmp/6213k1260902863.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 -19.105107 NA
1 -22.630392 -19.105107
2 -17.068590 -22.630392
3 -26.425347 -17.068590
4 -21.647809 -26.425347
5 -24.908470 -21.647809
6 -16.242163 -24.908470
7 -23.386547 -16.242163
8 -25.541021 -23.386547
9 -32.615736 -25.541021
10 -38.328649 -32.615736
11 -46.005045 -38.328649
12 -30.512311 -46.005045
13 -32.498257 -30.512311
14 -30.206125 -32.498257
15 -23.301620 -30.206125
16 -24.063422 -23.301620
17 -36.585344 -24.063422
18 -35.449969 -36.585344
19 -35.324684 -35.449969
20 -36.644924 -35.324684
21 -32.171891 -36.644924
22 -37.058979 -32.171891
23 -40.457297 -37.058979
24 -30.765165 -40.457297
25 -42.012373 -30.765165
26 -33.537658 -42.012373
27 -33.902823 -33.537658
28 -39.847208 -33.902823
29 -25.647208 -39.847208
30 -18.250571 -25.647208
31 -17.577538 -18.250571
32 -10.358439 -17.577538
33 -2.885406 -10.358439
34 -2.233153 -2.885406
35 8.185946 -2.233153
36 26.147748 8.185946
37 40.074715 26.147748
38 36.453934 40.074715
39 40.088769 36.453934
40 43.961802 40.088769
41 48.614054 43.961802
42 36.288769 48.614054
43 33.692132 36.288769
44 38.815736 33.692132
45 38.106186 38.815736
46 43.488769 38.106186
47 39.638198 43.488769
48 54.234835 39.638198
49 57.066307 54.234835
50 44.358439 57.066307
51 43.541021 44.358439
52 41.596637 43.541021
53 38.526967 41.596637
54 33.653934 38.526967
55 42.596637 33.653934
56 33.728649 42.596637
57 29.566847 33.728649
58 34.132012 29.566847
59 38.638198 34.132012
60 NA 38.638198
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -22.630392 -19.105107
[2,] -17.068590 -22.630392
[3,] -26.425347 -17.068590
[4,] -21.647809 -26.425347
[5,] -24.908470 -21.647809
[6,] -16.242163 -24.908470
[7,] -23.386547 -16.242163
[8,] -25.541021 -23.386547
[9,] -32.615736 -25.541021
[10,] -38.328649 -32.615736
[11,] -46.005045 -38.328649
[12,] -30.512311 -46.005045
[13,] -32.498257 -30.512311
[14,] -30.206125 -32.498257
[15,] -23.301620 -30.206125
[16,] -24.063422 -23.301620
[17,] -36.585344 -24.063422
[18,] -35.449969 -36.585344
[19,] -35.324684 -35.449969
[20,] -36.644924 -35.324684
[21,] -32.171891 -36.644924
[22,] -37.058979 -32.171891
[23,] -40.457297 -37.058979
[24,] -30.765165 -40.457297
[25,] -42.012373 -30.765165
[26,] -33.537658 -42.012373
[27,] -33.902823 -33.537658
[28,] -39.847208 -33.902823
[29,] -25.647208 -39.847208
[30,] -18.250571 -25.647208
[31,] -17.577538 -18.250571
[32,] -10.358439 -17.577538
[33,] -2.885406 -10.358439
[34,] -2.233153 -2.885406
[35,] 8.185946 -2.233153
[36,] 26.147748 8.185946
[37,] 40.074715 26.147748
[38,] 36.453934 40.074715
[39,] 40.088769 36.453934
[40,] 43.961802 40.088769
[41,] 48.614054 43.961802
[42,] 36.288769 48.614054
[43,] 33.692132 36.288769
[44,] 38.815736 33.692132
[45,] 38.106186 38.815736
[46,] 43.488769 38.106186
[47,] 39.638198 43.488769
[48,] 54.234835 39.638198
[49,] 57.066307 54.234835
[50,] 44.358439 57.066307
[51,] 43.541021 44.358439
[52,] 41.596637 43.541021
[53,] 38.526967 41.596637
[54,] 33.653934 38.526967
[55,] 42.596637 33.653934
[56,] 33.728649 42.596637
[57,] 29.566847 33.728649
[58,] 34.132012 29.566847
[59,] 38.638198 34.132012
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -22.630392 -19.105107
2 -17.068590 -22.630392
3 -26.425347 -17.068590
4 -21.647809 -26.425347
5 -24.908470 -21.647809
6 -16.242163 -24.908470
7 -23.386547 -16.242163
8 -25.541021 -23.386547
9 -32.615736 -25.541021
10 -38.328649 -32.615736
11 -46.005045 -38.328649
12 -30.512311 -46.005045
13 -32.498257 -30.512311
14 -30.206125 -32.498257
15 -23.301620 -30.206125
16 -24.063422 -23.301620
17 -36.585344 -24.063422
18 -35.449969 -36.585344
19 -35.324684 -35.449969
20 -36.644924 -35.324684
21 -32.171891 -36.644924
22 -37.058979 -32.171891
23 -40.457297 -37.058979
24 -30.765165 -40.457297
25 -42.012373 -30.765165
26 -33.537658 -42.012373
27 -33.902823 -33.537658
28 -39.847208 -33.902823
29 -25.647208 -39.847208
30 -18.250571 -25.647208
31 -17.577538 -18.250571
32 -10.358439 -17.577538
33 -2.885406 -10.358439
34 -2.233153 -2.885406
35 8.185946 -2.233153
36 26.147748 8.185946
37 40.074715 26.147748
38 36.453934 40.074715
39 40.088769 36.453934
40 43.961802 40.088769
41 48.614054 43.961802
42 36.288769 48.614054
43 33.692132 36.288769
44 38.815736 33.692132
45 38.106186 38.815736
46 43.488769 38.106186
47 39.638198 43.488769
48 54.234835 39.638198
49 57.066307 54.234835
50 44.358439 57.066307
51 43.541021 44.358439
52 41.596637 43.541021
53 38.526967 41.596637
54 33.653934 38.526967
55 42.596637 33.653934
56 33.728649 42.596637
57 29.566847 33.728649
58 34.132012 29.566847
59 38.638198 34.132012
> 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/7igjs1260902863.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8356s1260902863.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9cwlp1260902863.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ff5d1260902863.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/115idk1260902863.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/123c2b1260902863.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/138vjg1260902863.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/140rop1260902863.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/15m0ko1260902863.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/16hh471260902863.tab")
+ }
>
> try(system("convert tmp/10sok1260902863.ps tmp/10sok1260902863.png",intern=TRUE))
character(0)
> try(system("convert tmp/2kb471260902863.ps tmp/2kb471260902863.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ush71260902863.ps tmp/3ush71260902863.png",intern=TRUE))
character(0)
> try(system("convert tmp/40m9d1260902863.ps tmp/40m9d1260902863.png",intern=TRUE))
character(0)
> try(system("convert tmp/5ieqx1260902863.ps tmp/5ieqx1260902863.png",intern=TRUE))
character(0)
> try(system("convert tmp/6213k1260902863.ps tmp/6213k1260902863.png",intern=TRUE))
character(0)
> try(system("convert tmp/7igjs1260902863.ps tmp/7igjs1260902863.png",intern=TRUE))
character(0)
> try(system("convert tmp/8356s1260902863.ps tmp/8356s1260902863.png",intern=TRUE))
character(0)
> try(system("convert tmp/9cwlp1260902863.ps tmp/9cwlp1260902863.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ff5d1260902863.ps tmp/10ff5d1260902863.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.420 1.567 3.520