R version 2.8.0 (2008-10-20)
Copyright (C) 2008 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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Natural language support but running in an English locale
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Type 'demo()' for some demos, 'help()' for on-line help, or
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> x <- array(list(0.81,0,0.81,0,0.81,0,0.79,0,0.78,0,0.78,0,0.77,0,0.78,0,0.77,0,0.78,0,0.79,0,0.79,0,0.79,0,0.79,0,0.79,0,0.8,0,0.8,0,0.8,1,0.8,1,0.81,1,0.8,1,0.82,1,0.85,1,0.85,1,0.86,1,0.85,1,0.83,1,0.81,1,0.82,1,0.82,1,0.78,1,0.78,1,0.73,1,0.68,1,0.65,1,0.62,1,0.6,1,0.6,1,0.59,1,0.6,1,0.6,1,0.6,1,0.59,1,0.58,1,0.56,1,0.55,1,0.54,1,0.55,1,0.55,1,0.54,1,0.54,1,0.54,1,0.53,1,0.53,1,0.53,1,0.53,1),dim=c(2,56),dimnames=list(c('Bakmeel','Dummy'),1:56))
> y <- array(NA,dim=c(2,56),dimnames=list(c('Bakmeel','Dummy'),1:56))
> 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
Bakmeel Dummy t
1 0.81 0 1
2 0.81 0 2
3 0.81 0 3
4 0.79 0 4
5 0.78 0 5
6 0.78 0 6
7 0.77 0 7
8 0.78 0 8
9 0.77 0 9
10 0.78 0 10
11 0.79 0 11
12 0.79 0 12
13 0.79 0 13
14 0.79 0 14
15 0.79 0 15
16 0.80 0 16
17 0.80 0 17
18 0.80 1 18
19 0.80 1 19
20 0.81 1 20
21 0.80 1 21
22 0.82 1 22
23 0.85 1 23
24 0.85 1 24
25 0.86 1 25
26 0.85 1 26
27 0.83 1 27
28 0.81 1 28
29 0.82 1 29
30 0.82 1 30
31 0.78 1 31
32 0.78 1 32
33 0.73 1 33
34 0.68 1 34
35 0.65 1 35
36 0.62 1 36
37 0.60 1 37
38 0.60 1 38
39 0.59 1 39
40 0.60 1 40
41 0.60 1 41
42 0.60 1 42
43 0.59 1 43
44 0.58 1 44
45 0.56 1 45
46 0.55 1 46
47 0.54 1 47
48 0.55 1 48
49 0.55 1 49
50 0.54 1 50
51 0.54 1 51
52 0.54 1 52
53 0.53 1 53
54 0.53 1 54
55 0.53 1 55
56 0.53 1 56
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummy t
0.875423 0.147810 -0.009491
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.07205 -0.03747 -0.01315 0.03998 0.08593
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.8754226 0.0126387 69.266 < 2e-16 ***
Dummy 0.1478104 0.0223377 6.617 1.86e-08 ***
t -0.0094914 0.0006354 -14.937 < 2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.04647 on 53 degrees of freedom
Multiple R-squared: 0.8496, Adjusted R-squared: 0.8439
F-statistic: 149.7 on 2 and 53 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,] 6.394678e-03 1.278936e-02 9.936053e-01
[2,] 9.506020e-04 1.901204e-03 9.990494e-01
[3,] 7.163298e-04 1.432660e-03 9.992837e-01
[4,] 1.610575e-04 3.221149e-04 9.998389e-01
[5,] 1.644618e-04 3.289237e-04 9.998355e-01
[6,] 3.371018e-04 6.742036e-04 9.996629e-01
[7,] 2.647953e-04 5.295906e-04 9.997352e-01
[8,] 1.456156e-04 2.912312e-04 9.998544e-01
[9,] 6.549683e-05 1.309937e-04 9.999345e-01
[10,] 2.570189e-05 5.140378e-05 9.999743e-01
[11,] 1.708104e-05 3.416208e-05 9.999829e-01
[12,] 8.260733e-06 1.652147e-05 9.999917e-01
[13,] 3.550818e-06 7.101636e-06 9.999964e-01
[14,] 1.532833e-06 3.065665e-06 9.999985e-01
[15,] 7.050743e-07 1.410149e-06 9.999993e-01
[16,] 2.924794e-07 5.849588e-07 9.999997e-01
[17,] 2.012506e-07 4.025011e-07 9.999998e-01
[18,] 2.714905e-06 5.429809e-06 9.999973e-01
[19,] 6.400926e-06 1.280185e-05 9.999936e-01
[20,] 2.104913e-05 4.209826e-05 9.999790e-01
[21,] 2.305155e-05 4.610309e-05 9.999769e-01
[22,] 1.441824e-05 2.883647e-05 9.999856e-01
[23,] 1.407558e-05 2.815116e-05 9.999859e-01
[24,] 2.261189e-05 4.522378e-05 9.999774e-01
[25,] 1.451361e-04 2.902723e-04 9.998549e-01
[26,] 3.477554e-03 6.955107e-03 9.965224e-01
[27,] 1.952214e-01 3.904428e-01 8.047786e-01
[28,] 9.739815e-01 5.203697e-02 2.601848e-02
[29,] 9.999735e-01 5.304369e-05 2.652185e-05
[30,] 9.999999e-01 2.647318e-07 1.323659e-07
[31,] 1.000000e+00 6.137826e-08 3.068913e-08
[32,] 1.000000e+00 4.080843e-08 2.040421e-08
[33,] 1.000000e+00 7.626989e-08 3.813495e-08
[34,] 9.999999e-01 1.415672e-07 7.078359e-08
[35,] 9.999997e-01 5.054721e-07 2.527360e-07
[36,] 9.999993e-01 1.302359e-06 6.511795e-07
[37,] 9.999995e-01 9.741614e-07 4.870807e-07
[38,] 9.999998e-01 4.161804e-07 2.080902e-07
[39,] 1.000000e+00 2.789451e-08 1.394726e-08
[40,] 9.999999e-01 1.179999e-07 5.899996e-08
[41,] 9.999993e-01 1.322288e-06 6.611438e-07
[42,] 9.999994e-01 1.221338e-06 6.106690e-07
[43,] 9.999913e-01 1.745150e-05 8.725748e-06
[44,] 9.999582e-01 8.361945e-05 4.180972e-05
[45,] 9.993545e-01 1.291014e-03 6.455072e-04
> postscript(file="/var/www/html/freestat/rcomp/tmp/11ux01292502559.ps",horizontal=F,onefile=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/21ux01292502559.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/freestat/rcomp/tmp/3u4wk1292502559.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4u4wk1292502559.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5u4wk1292502559.ps",horizontal=F,onefile=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 = 56
Frequency = 1
1 2 3 4 5
-0.0559311892 -0.0464397906 -0.0369483919 -0.0474569933 -0.0479655946
6 7 8 9 10
-0.0384741960 -0.0389827973 -0.0194913987 -0.0200000000 -0.0005086013
11 12 13 14 15
0.0189827973 0.0284741960 0.0379655946 0.0474569933 0.0569483919
16 17 18 19 20
0.0764397906 0.0859311892 -0.0523878565 -0.0428964578 -0.0234050592
21 22 23 24 25
-0.0239136605 0.0055777381 0.0450691368 0.0545605355 0.0740519341
26 27 28 29 30
0.0735433328 0.0630347314 0.0525261301 0.0720175287 0.0815089274
31 32 33 34 35
0.0510003260 0.0604917247 0.0199831233 -0.0205254780 -0.0410340794
36 37 38 39 40
-0.0615426807 -0.0720512821 -0.0625598834 -0.0630684847 -0.0435770861
41 42 43 44 45
-0.0340856874 -0.0245942888 -0.0251028901 -0.0256114915 -0.0361200928
46 47 48 49 50
-0.0366286942 -0.0371372955 -0.0176458969 -0.0081544982 -0.0086630996
51 52 53 54 55
0.0008282991 0.0103196978 0.0098110964 0.0193024951 0.0287938937
56
0.0382852924
> postscript(file="/var/www/html/freestat/rcomp/tmp/65dw51292502559.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 56
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.0559311892 NA
1 -0.0464397906 -0.0559311892
2 -0.0369483919 -0.0464397906
3 -0.0474569933 -0.0369483919
4 -0.0479655946 -0.0474569933
5 -0.0384741960 -0.0479655946
6 -0.0389827973 -0.0384741960
7 -0.0194913987 -0.0389827973
8 -0.0200000000 -0.0194913987
9 -0.0005086013 -0.0200000000
10 0.0189827973 -0.0005086013
11 0.0284741960 0.0189827973
12 0.0379655946 0.0284741960
13 0.0474569933 0.0379655946
14 0.0569483919 0.0474569933
15 0.0764397906 0.0569483919
16 0.0859311892 0.0764397906
17 -0.0523878565 0.0859311892
18 -0.0428964578 -0.0523878565
19 -0.0234050592 -0.0428964578
20 -0.0239136605 -0.0234050592
21 0.0055777381 -0.0239136605
22 0.0450691368 0.0055777381
23 0.0545605355 0.0450691368
24 0.0740519341 0.0545605355
25 0.0735433328 0.0740519341
26 0.0630347314 0.0735433328
27 0.0525261301 0.0630347314
28 0.0720175287 0.0525261301
29 0.0815089274 0.0720175287
30 0.0510003260 0.0815089274
31 0.0604917247 0.0510003260
32 0.0199831233 0.0604917247
33 -0.0205254780 0.0199831233
34 -0.0410340794 -0.0205254780
35 -0.0615426807 -0.0410340794
36 -0.0720512821 -0.0615426807
37 -0.0625598834 -0.0720512821
38 -0.0630684847 -0.0625598834
39 -0.0435770861 -0.0630684847
40 -0.0340856874 -0.0435770861
41 -0.0245942888 -0.0340856874
42 -0.0251028901 -0.0245942888
43 -0.0256114915 -0.0251028901
44 -0.0361200928 -0.0256114915
45 -0.0366286942 -0.0361200928
46 -0.0371372955 -0.0366286942
47 -0.0176458969 -0.0371372955
48 -0.0081544982 -0.0176458969
49 -0.0086630996 -0.0081544982
50 0.0008282991 -0.0086630996
51 0.0103196978 0.0008282991
52 0.0098110964 0.0103196978
53 0.0193024951 0.0098110964
54 0.0287938937 0.0193024951
55 0.0382852924 0.0287938937
56 NA 0.0382852924
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.0464397906 -0.0559311892
[2,] -0.0369483919 -0.0464397906
[3,] -0.0474569933 -0.0369483919
[4,] -0.0479655946 -0.0474569933
[5,] -0.0384741960 -0.0479655946
[6,] -0.0389827973 -0.0384741960
[7,] -0.0194913987 -0.0389827973
[8,] -0.0200000000 -0.0194913987
[9,] -0.0005086013 -0.0200000000
[10,] 0.0189827973 -0.0005086013
[11,] 0.0284741960 0.0189827973
[12,] 0.0379655946 0.0284741960
[13,] 0.0474569933 0.0379655946
[14,] 0.0569483919 0.0474569933
[15,] 0.0764397906 0.0569483919
[16,] 0.0859311892 0.0764397906
[17,] -0.0523878565 0.0859311892
[18,] -0.0428964578 -0.0523878565
[19,] -0.0234050592 -0.0428964578
[20,] -0.0239136605 -0.0234050592
[21,] 0.0055777381 -0.0239136605
[22,] 0.0450691368 0.0055777381
[23,] 0.0545605355 0.0450691368
[24,] 0.0740519341 0.0545605355
[25,] 0.0735433328 0.0740519341
[26,] 0.0630347314 0.0735433328
[27,] 0.0525261301 0.0630347314
[28,] 0.0720175287 0.0525261301
[29,] 0.0815089274 0.0720175287
[30,] 0.0510003260 0.0815089274
[31,] 0.0604917247 0.0510003260
[32,] 0.0199831233 0.0604917247
[33,] -0.0205254780 0.0199831233
[34,] -0.0410340794 -0.0205254780
[35,] -0.0615426807 -0.0410340794
[36,] -0.0720512821 -0.0615426807
[37,] -0.0625598834 -0.0720512821
[38,] -0.0630684847 -0.0625598834
[39,] -0.0435770861 -0.0630684847
[40,] -0.0340856874 -0.0435770861
[41,] -0.0245942888 -0.0340856874
[42,] -0.0251028901 -0.0245942888
[43,] -0.0256114915 -0.0251028901
[44,] -0.0361200928 -0.0256114915
[45,] -0.0366286942 -0.0361200928
[46,] -0.0371372955 -0.0366286942
[47,] -0.0176458969 -0.0371372955
[48,] -0.0081544982 -0.0176458969
[49,] -0.0086630996 -0.0081544982
[50,] 0.0008282991 -0.0086630996
[51,] 0.0103196978 0.0008282991
[52,] 0.0098110964 0.0103196978
[53,] 0.0193024951 0.0098110964
[54,] 0.0287938937 0.0193024951
[55,] 0.0382852924 0.0287938937
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.0464397906 -0.0559311892
2 -0.0369483919 -0.0464397906
3 -0.0474569933 -0.0369483919
4 -0.0479655946 -0.0474569933
5 -0.0384741960 -0.0479655946
6 -0.0389827973 -0.0384741960
7 -0.0194913987 -0.0389827973
8 -0.0200000000 -0.0194913987
9 -0.0005086013 -0.0200000000
10 0.0189827973 -0.0005086013
11 0.0284741960 0.0189827973
12 0.0379655946 0.0284741960
13 0.0474569933 0.0379655946
14 0.0569483919 0.0474569933
15 0.0764397906 0.0569483919
16 0.0859311892 0.0764397906
17 -0.0523878565 0.0859311892
18 -0.0428964578 -0.0523878565
19 -0.0234050592 -0.0428964578
20 -0.0239136605 -0.0234050592
21 0.0055777381 -0.0239136605
22 0.0450691368 0.0055777381
23 0.0545605355 0.0450691368
24 0.0740519341 0.0545605355
25 0.0735433328 0.0740519341
26 0.0630347314 0.0735433328
27 0.0525261301 0.0630347314
28 0.0720175287 0.0525261301
29 0.0815089274 0.0720175287
30 0.0510003260 0.0815089274
31 0.0604917247 0.0510003260
32 0.0199831233 0.0604917247
33 -0.0205254780 0.0199831233
34 -0.0410340794 -0.0205254780
35 -0.0615426807 -0.0410340794
36 -0.0720512821 -0.0615426807
37 -0.0625598834 -0.0720512821
38 -0.0630684847 -0.0625598834
39 -0.0435770861 -0.0630684847
40 -0.0340856874 -0.0435770861
41 -0.0245942888 -0.0340856874
42 -0.0251028901 -0.0245942888
43 -0.0256114915 -0.0251028901
44 -0.0361200928 -0.0256114915
45 -0.0366286942 -0.0361200928
46 -0.0371372955 -0.0366286942
47 -0.0176458969 -0.0371372955
48 -0.0081544982 -0.0176458969
49 -0.0086630996 -0.0081544982
50 0.0008282991 -0.0086630996
51 0.0103196978 0.0008282991
52 0.0098110964 0.0103196978
53 0.0193024951 0.0098110964
54 0.0287938937 0.0193024951
55 0.0382852924 0.0287938937
> 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/freestat/rcomp/tmp/75dw51292502559.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8x4d81292502559.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9x4d81292502559.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/108dut1292502559.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/11cetz1292502559.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/freestat/rcomp/tmp/12fx951292502559.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/freestat/rcomp/tmp/13b6pw1292502559.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/freestat/rcomp/tmp/14wp521292502559.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/freestat/rcomp/tmp/157ynn1292502559.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/freestat/rcomp/tmp/16l8le1292502559.tab")
+ }
>
> try(system("convert tmp/11ux01292502559.ps tmp/11ux01292502559.png",intern=TRUE))
character(0)
> try(system("convert tmp/21ux01292502559.ps tmp/21ux01292502559.png",intern=TRUE))
character(0)
> try(system("convert tmp/3u4wk1292502559.ps tmp/3u4wk1292502559.png",intern=TRUE))
character(0)
> try(system("convert tmp/4u4wk1292502559.ps tmp/4u4wk1292502559.png",intern=TRUE))
character(0)
> try(system("convert tmp/5u4wk1292502559.ps tmp/5u4wk1292502559.png",intern=TRUE))
character(0)
> try(system("convert tmp/65dw51292502559.ps tmp/65dw51292502559.png",intern=TRUE))
character(0)
> try(system("convert tmp/75dw51292502559.ps tmp/75dw51292502559.png",intern=TRUE))
character(0)
> try(system("convert tmp/8x4d81292502559.ps tmp/8x4d81292502559.png",intern=TRUE))
character(0)
> try(system("convert tmp/9x4d81292502559.ps tmp/9x4d81292502559.png",intern=TRUE))
character(0)
> try(system("convert tmp/108dut1292502559.ps tmp/108dut1292502559.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.731 2.439 4.106