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(593530.00,0,610943.00,0,612613.00,0,611324.00,0,594167.00,0,595454.00,0,590865.00,0,589379.00,0,584428.00,0,573100.00,0,567456.00,0,569028.00,0,620735.00,0,628884.00,0,628232.00,0,612117.00,0,595404.00,0,597141.00,0,593408.00,0,590072.00,0,579799.00,0,574205.00,0,572775.00,0,572942.00,0,619567.00,0,625809.00,0,619916.00,0,587625.00,0,565742.00,0,557274.00,0,560576.00,0,548854.00,0,531673.00,0,525919.00,0,511038.00,0,498662.00,0,555362.00,0,564591.00,0,541657.00,0,527070.00,0,509846.00,0,514258.00,0,516922.00,0,507561.00,0,492622.00,0,490243.00,0,469357.00,0,477580.00,0,528379.00,1,533590.00,1,517945.00,1,506174.00,1,501866.00,1,516141.00,1,528222.00,1,532638.00,1,536322.00,1,536535.00,1,523597.00,1,536214.00,1,586570.00,1,596594.00,1,580523.00,1),dim=c(2,63),dimnames=list(c('werklozen','crisis
'),1:63))
> y <- array(NA,dim=c(2,63),dimnames=list(c('werklozen','crisis
'),1:63))
> 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
werklozen crisis\r
1 593530 0
2 610943 0
3 612613 0
4 611324 0
5 594167 0
6 595454 0
7 590865 0
8 589379 0
9 584428 0
10 573100 0
11 567456 0
12 569028 0
13 620735 0
14 628884 0
15 628232 0
16 612117 0
17 595404 0
18 597141 0
19 593408 0
20 590072 0
21 579799 0
22 574205 0
23 572775 0
24 572942 0
25 619567 0
26 625809 0
27 619916 0
28 587625 0
29 565742 0
30 557274 0
31 560576 0
32 548854 0
33 531673 0
34 525919 0
35 511038 0
36 498662 0
37 555362 0
38 564591 0
39 541657 0
40 527070 0
41 509846 0
42 514258 0
43 516922 0
44 507561 0
45 492622 0
46 490243 0
47 469357 0
48 477580 0
49 528379 1
50 533590 1
51 517945 1
52 506174 1
53 501866 1
54 516141 1
55 528222 1
56 532638 1
57 536322 1
58 536535 1
59 523597 1
60 536214 1
61 586570 1
62 596594 1
63 580523 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `crisis\r`
566203 -28782
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-96845.6 -22912.6 -460.6 28582.9 62681.4
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 566203 5863 96.566 <2e-16 ***
`crisis\r` -28782 12016 -2.395 0.0197 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 40620 on 61 degrees of freedom
Multiple R-squared: 0.08597, Adjusted R-squared: 0.07098
F-statistic: 5.737 on 1 and 61 DF, p-value: 0.01970
> 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,] 0.0279517691 0.0559035382 0.97204823
[2,] 0.0086941345 0.0173882689 0.99130587
[3,] 0.0034924733 0.0069849466 0.99650753
[4,] 0.0014084431 0.0028168862 0.99859156
[5,] 0.0007884338 0.0015768677 0.99921157
[6,] 0.0011533968 0.0023067936 0.99884660
[7,] 0.0016750434 0.0033500868 0.99832496
[8,] 0.0014412132 0.0028824264 0.99855879
[9,] 0.0021376089 0.0042752179 0.99786239
[10,] 0.0045801216 0.0091602432 0.99541988
[11,] 0.0073634795 0.0147269590 0.99263652
[12,] 0.0054456311 0.0108912622 0.99455437
[13,] 0.0031252283 0.0062504566 0.99687477
[14,] 0.0018204518 0.0036409036 0.99817955
[15,] 0.0010683698 0.0021367397 0.99893163
[16,] 0.0006471457 0.0012942915 0.99935285
[17,] 0.0004807765 0.0009615530 0.99951922
[18,] 0.0004243834 0.0008487669 0.99957562
[19,] 0.0003796361 0.0007592721 0.99962036
[20,] 0.0003261571 0.0006523142 0.99967384
[21,] 0.0007741824 0.0015483648 0.99922582
[22,] 0.0035613282 0.0071226565 0.99643867
[23,] 0.0140683922 0.0281367844 0.98593161
[24,] 0.0206972230 0.0413944461 0.97930278
[25,] 0.0339502847 0.0679005695 0.96604972
[26,] 0.0600800530 0.1201601060 0.93991995
[27,] 0.0947842284 0.1895684568 0.90521577
[28,] 0.1561608681 0.3123217363 0.84383913
[29,] 0.2734914051 0.5469828101 0.72650859
[30,] 0.4013776159 0.8027552318 0.59862238
[31,] 0.5667447339 0.8665105322 0.43325527
[32,] 0.7308721794 0.5382556413 0.26912782
[33,] 0.7656856713 0.4686286573 0.23431433
[34,] 0.8496902700 0.3006194600 0.15030973
[35,] 0.8845448964 0.2309102071 0.11545510
[36,] 0.9052187540 0.1895624920 0.09478125
[37,] 0.9193597455 0.1612805090 0.08064025
[38,] 0.9277170605 0.1445658790 0.07228294
[39,] 0.9370452241 0.1259095517 0.06295478
[40,] 0.9433133521 0.1133732958 0.05668665
[41,] 0.9462576890 0.1074846220 0.05374231
[42,] 0.9467092483 0.1065815034 0.05329075
[43,] 0.9499700856 0.1000598288 0.05002991
[44,] 0.9432370170 0.1135259660 0.05676298
[45,] 0.9111602602 0.1776794797 0.08883974
[46,] 0.8634710343 0.2730579314 0.13652897
[47,] 0.8185430077 0.3629139846 0.18145699
[48,] 0.8048189678 0.3903620645 0.19518103
[49,] 0.8256917280 0.3486165440 0.17430827
[50,] 0.8057668807 0.3884662387 0.19423312
[51,] 0.7472414301 0.5055171398 0.25275857
[52,] 0.6675082760 0.6649834480 0.33249172
[53,] 0.5659207025 0.8681585949 0.43407930
[54,] 0.4607588041 0.9215176082 0.53924120
> postscript(file="/var/www/html/rcomp/tmp/1etdf1258645293.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2k4py1258645293.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3amto1258645293.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4weix1258645293.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5rbmm1258645293.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 = 63
Frequency = 1
1 2 3 4 5 6
27327.3958 44740.3958 46410.3958 45121.3958 27964.3958 29251.3958
7 8 9 10 11 12
24662.3958 23176.3958 18225.3958 6897.3958 1253.3958 2825.3958
13 14 15 16 17 18
54532.3958 62681.3958 62029.3958 45914.3958 29201.3958 30938.3958
19 20 21 22 23 24
27205.3958 23869.3958 13596.3958 8002.3958 6572.3958 6739.3958
25 26 27 28 29 30
53364.3958 59606.3958 53713.3958 21422.3958 -460.6042 -8928.6042
31 32 33 34 35 36
-5626.6042 -17348.6042 -34529.6042 -40283.6042 -55164.6042 -67540.6042
37 38 39 40 41 42
-10840.6042 -1611.6042 -24545.6042 -39132.6042 -56356.6042 -51944.6042
43 44 45 46 47 48
-49280.6042 -58641.6042 -73580.6042 -75959.6042 -96845.6042 -88622.6042
49 50 51 52 53 54
-9041.6667 -3830.6667 -19475.6667 -31246.6667 -35554.6667 -21279.6667
55 56 57 58 59 60
-9198.6667 -4782.6667 -1098.6667 -885.6667 -13823.6667 -1206.6667
61 62 63
49149.3333 59173.3333 43102.3333
> postscript(file="/var/www/html/rcomp/tmp/6mtwe1258645293.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 = 63
Frequency = 1
lag(myerror, k = 1) myerror
0 27327.3958 NA
1 44740.3958 27327.3958
2 46410.3958 44740.3958
3 45121.3958 46410.3958
4 27964.3958 45121.3958
5 29251.3958 27964.3958
6 24662.3958 29251.3958
7 23176.3958 24662.3958
8 18225.3958 23176.3958
9 6897.3958 18225.3958
10 1253.3958 6897.3958
11 2825.3958 1253.3958
12 54532.3958 2825.3958
13 62681.3958 54532.3958
14 62029.3958 62681.3958
15 45914.3958 62029.3958
16 29201.3958 45914.3958
17 30938.3958 29201.3958
18 27205.3958 30938.3958
19 23869.3958 27205.3958
20 13596.3958 23869.3958
21 8002.3958 13596.3958
22 6572.3958 8002.3958
23 6739.3958 6572.3958
24 53364.3958 6739.3958
25 59606.3958 53364.3958
26 53713.3958 59606.3958
27 21422.3958 53713.3958
28 -460.6042 21422.3958
29 -8928.6042 -460.6042
30 -5626.6042 -8928.6042
31 -17348.6042 -5626.6042
32 -34529.6042 -17348.6042
33 -40283.6042 -34529.6042
34 -55164.6042 -40283.6042
35 -67540.6042 -55164.6042
36 -10840.6042 -67540.6042
37 -1611.6042 -10840.6042
38 -24545.6042 -1611.6042
39 -39132.6042 -24545.6042
40 -56356.6042 -39132.6042
41 -51944.6042 -56356.6042
42 -49280.6042 -51944.6042
43 -58641.6042 -49280.6042
44 -73580.6042 -58641.6042
45 -75959.6042 -73580.6042
46 -96845.6042 -75959.6042
47 -88622.6042 -96845.6042
48 -9041.6667 -88622.6042
49 -3830.6667 -9041.6667
50 -19475.6667 -3830.6667
51 -31246.6667 -19475.6667
52 -35554.6667 -31246.6667
53 -21279.6667 -35554.6667
54 -9198.6667 -21279.6667
55 -4782.6667 -9198.6667
56 -1098.6667 -4782.6667
57 -885.6667 -1098.6667
58 -13823.6667 -885.6667
59 -1206.6667 -13823.6667
60 49149.3333 -1206.6667
61 59173.3333 49149.3333
62 43102.3333 59173.3333
63 NA 43102.3333
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 44740.3958 27327.3958
[2,] 46410.3958 44740.3958
[3,] 45121.3958 46410.3958
[4,] 27964.3958 45121.3958
[5,] 29251.3958 27964.3958
[6,] 24662.3958 29251.3958
[7,] 23176.3958 24662.3958
[8,] 18225.3958 23176.3958
[9,] 6897.3958 18225.3958
[10,] 1253.3958 6897.3958
[11,] 2825.3958 1253.3958
[12,] 54532.3958 2825.3958
[13,] 62681.3958 54532.3958
[14,] 62029.3958 62681.3958
[15,] 45914.3958 62029.3958
[16,] 29201.3958 45914.3958
[17,] 30938.3958 29201.3958
[18,] 27205.3958 30938.3958
[19,] 23869.3958 27205.3958
[20,] 13596.3958 23869.3958
[21,] 8002.3958 13596.3958
[22,] 6572.3958 8002.3958
[23,] 6739.3958 6572.3958
[24,] 53364.3958 6739.3958
[25,] 59606.3958 53364.3958
[26,] 53713.3958 59606.3958
[27,] 21422.3958 53713.3958
[28,] -460.6042 21422.3958
[29,] -8928.6042 -460.6042
[30,] -5626.6042 -8928.6042
[31,] -17348.6042 -5626.6042
[32,] -34529.6042 -17348.6042
[33,] -40283.6042 -34529.6042
[34,] -55164.6042 -40283.6042
[35,] -67540.6042 -55164.6042
[36,] -10840.6042 -67540.6042
[37,] -1611.6042 -10840.6042
[38,] -24545.6042 -1611.6042
[39,] -39132.6042 -24545.6042
[40,] -56356.6042 -39132.6042
[41,] -51944.6042 -56356.6042
[42,] -49280.6042 -51944.6042
[43,] -58641.6042 -49280.6042
[44,] -73580.6042 -58641.6042
[45,] -75959.6042 -73580.6042
[46,] -96845.6042 -75959.6042
[47,] -88622.6042 -96845.6042
[48,] -9041.6667 -88622.6042
[49,] -3830.6667 -9041.6667
[50,] -19475.6667 -3830.6667
[51,] -31246.6667 -19475.6667
[52,] -35554.6667 -31246.6667
[53,] -21279.6667 -35554.6667
[54,] -9198.6667 -21279.6667
[55,] -4782.6667 -9198.6667
[56,] -1098.6667 -4782.6667
[57,] -885.6667 -1098.6667
[58,] -13823.6667 -885.6667
[59,] -1206.6667 -13823.6667
[60,] 49149.3333 -1206.6667
[61,] 59173.3333 49149.3333
[62,] 43102.3333 59173.3333
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 44740.3958 27327.3958
2 46410.3958 44740.3958
3 45121.3958 46410.3958
4 27964.3958 45121.3958
5 29251.3958 27964.3958
6 24662.3958 29251.3958
7 23176.3958 24662.3958
8 18225.3958 23176.3958
9 6897.3958 18225.3958
10 1253.3958 6897.3958
11 2825.3958 1253.3958
12 54532.3958 2825.3958
13 62681.3958 54532.3958
14 62029.3958 62681.3958
15 45914.3958 62029.3958
16 29201.3958 45914.3958
17 30938.3958 29201.3958
18 27205.3958 30938.3958
19 23869.3958 27205.3958
20 13596.3958 23869.3958
21 8002.3958 13596.3958
22 6572.3958 8002.3958
23 6739.3958 6572.3958
24 53364.3958 6739.3958
25 59606.3958 53364.3958
26 53713.3958 59606.3958
27 21422.3958 53713.3958
28 -460.6042 21422.3958
29 -8928.6042 -460.6042
30 -5626.6042 -8928.6042
31 -17348.6042 -5626.6042
32 -34529.6042 -17348.6042
33 -40283.6042 -34529.6042
34 -55164.6042 -40283.6042
35 -67540.6042 -55164.6042
36 -10840.6042 -67540.6042
37 -1611.6042 -10840.6042
38 -24545.6042 -1611.6042
39 -39132.6042 -24545.6042
40 -56356.6042 -39132.6042
41 -51944.6042 -56356.6042
42 -49280.6042 -51944.6042
43 -58641.6042 -49280.6042
44 -73580.6042 -58641.6042
45 -75959.6042 -73580.6042
46 -96845.6042 -75959.6042
47 -88622.6042 -96845.6042
48 -9041.6667 -88622.6042
49 -3830.6667 -9041.6667
50 -19475.6667 -3830.6667
51 -31246.6667 -19475.6667
52 -35554.6667 -31246.6667
53 -21279.6667 -35554.6667
54 -9198.6667 -21279.6667
55 -4782.6667 -9198.6667
56 -1098.6667 -4782.6667
57 -885.6667 -1098.6667
58 -13823.6667 -885.6667
59 -1206.6667 -13823.6667
60 49149.3333 -1206.6667
61 59173.3333 49149.3333
62 43102.3333 59173.3333
> 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/77xxs1258645293.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8d5a01258645293.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/98npo1258645293.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10xhtb1258645293.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11p7ck1258645293.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/12b35g1258645293.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/131xjf1258645293.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/14wdym1258645293.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/15n6hr1258645293.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/16bgow1258645293.tab")
+ }
>
> system("convert tmp/1etdf1258645293.ps tmp/1etdf1258645293.png")
> system("convert tmp/2k4py1258645293.ps tmp/2k4py1258645293.png")
> system("convert tmp/3amto1258645293.ps tmp/3amto1258645293.png")
> system("convert tmp/4weix1258645293.ps tmp/4weix1258645293.png")
> system("convert tmp/5rbmm1258645293.ps tmp/5rbmm1258645293.png")
> system("convert tmp/6mtwe1258645293.ps tmp/6mtwe1258645293.png")
> system("convert tmp/77xxs1258645293.ps tmp/77xxs1258645293.png")
> system("convert tmp/8d5a01258645293.ps tmp/8d5a01258645293.png")
> system("convert tmp/98npo1258645293.ps tmp/98npo1258645293.png")
> system("convert tmp/10xhtb1258645293.ps tmp/10xhtb1258645293.png")
>
>
> proc.time()
user system elapsed
2.458 1.554 2.868