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(100.6,71.7,104.3,77.5,120.4,89.8,107.5,80.3,102.9,78.7,125.6,93.8,107.5,57.6,108.8,60.6,128.4,91,121.1,85.3,119.5,77.4,128.7,77.3,108.7,68.3,105.5,69.9,119.8,81.7,111.3,75.1,110.6,69.9,120.1,84,97.5,54.3,107.7,60,127.3,89.9,117.2,77,119.8,85.3,116.2,77.6,111,69.2,112.4,75.5,130.6,85.7,109.1,72.2,118.8,79.9,123.9,85.3,101.6,52.2,112.8,61.2,128,82.4,129.6,85.4,125.8,78.2,119.5,70.2,115.7,70.2,113.6,69.3,129.7,77.5,112,66.1,116.8,69,127,79.2,112.1,56.2,114.2,63.3,121.1,77.8,131.6,92,125,78.1,120.4,65.1,117.7,71.1,117.5,70.9,120.6,72,127.5,81.9,112.3,70.6,124.5,72.5,115.2,65.1,104.7,54.9,130.9,80,129.2,77.4,113.5,59.6,125.6,57.4,107.6,50.8),dim=c(2,61),dimnames=list(c('Y','X'),1:61))
> y <- array(NA,dim=c(2,61),dimnames=list(c('Y','X'),1:61))
> 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
Y X
1 100.6 71.7
2 104.3 77.5
3 120.4 89.8
4 107.5 80.3
5 102.9 78.7
6 125.6 93.8
7 107.5 57.6
8 108.8 60.6
9 128.4 91.0
10 121.1 85.3
11 119.5 77.4
12 128.7 77.3
13 108.7 68.3
14 105.5 69.9
15 119.8 81.7
16 111.3 75.1
17 110.6 69.9
18 120.1 84.0
19 97.5 54.3
20 107.7 60.0
21 127.3 89.9
22 117.2 77.0
23 119.8 85.3
24 116.2 77.6
25 111.0 69.2
26 112.4 75.5
27 130.6 85.7
28 109.1 72.2
29 118.8 79.9
30 123.9 85.3
31 101.6 52.2
32 112.8 61.2
33 128.0 82.4
34 129.6 85.4
35 125.8 78.2
36 119.5 70.2
37 115.7 70.2
38 113.6 69.3
39 129.7 77.5
40 112.0 66.1
41 116.8 69.0
42 127.0 79.2
43 112.1 56.2
44 114.2 63.3
45 121.1 77.8
46 131.6 92.0
47 125.0 78.1
48 120.4 65.1
49 117.7 71.1
50 117.5 70.9
51 120.6 72.0
52 127.5 81.9
53 112.3 70.6
54 124.5 72.5
55 115.2 65.1
56 104.7 54.9
57 130.9 80.0
58 129.2 77.4
59 113.5 59.6
60 125.6 57.4
61 107.6 50.8
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
77.4030 0.5413
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-17.1001 -3.3159 0.3006 4.2782 17.1287
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 77.40302 6.11374 12.660 < 2e-16 ***
X 0.54126 0.08243 6.566 1.46e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.718 on 59 degrees of freedom
Multiple R-squared: 0.4222, Adjusted R-squared: 0.4124
F-statistic: 43.12 on 1 and 59 DF, p-value: 1.460e-08
> 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,] 0.11800871 0.23601742 0.88199129
[2,] 0.05342006 0.10684012 0.94657994
[3,] 0.87356149 0.25287702 0.12643851
[4,] 0.87612169 0.24775661 0.12387831
[5,] 0.92870334 0.14259331 0.07129666
[6,] 0.90976547 0.18046906 0.09023453
[7,] 0.90537408 0.18925184 0.09462592
[8,] 0.97835554 0.04328891 0.02164446
[9,] 0.96901392 0.06197215 0.03098608
[10,] 0.97228353 0.05543294 0.02771647
[11,] 0.96149303 0.07701393 0.03850697
[12,] 0.95678324 0.08643351 0.04321676
[13,] 0.94495748 0.11008504 0.05504252
[14,] 0.93095397 0.13809206 0.06904603
[15,] 0.93994142 0.12011717 0.06005858
[16,] 0.92748910 0.14502179 0.07251090
[17,] 0.91305263 0.17389474 0.08694737
[18,] 0.89434628 0.21130743 0.10565372
[19,] 0.88637951 0.22724098 0.11362049
[20,] 0.87502817 0.24994365 0.12497183
[21,] 0.86597648 0.26804703 0.13402352
[22,] 0.89062179 0.21875642 0.10937821
[23,] 0.91409119 0.17181761 0.08590881
[24,] 0.95263486 0.09473028 0.04736514
[25,] 0.95377582 0.09244837 0.04622418
[26,] 0.95161513 0.09676974 0.04838487
[27,] 0.95352369 0.09295263 0.04647631
[28,] 0.95002931 0.09994138 0.04997069
[29,] 0.95048158 0.09903684 0.04951842
[30,] 0.94611163 0.10777674 0.05388837
[31,] 0.94313109 0.11373781 0.05686891
[32,] 0.93279676 0.13440649 0.06720324
[33,] 0.91949741 0.16100517 0.08050259
[34,] 0.91574572 0.16850855 0.08425428
[35,] 0.94385009 0.11229983 0.05614991
[36,] 0.93973597 0.12052806 0.06026403
[37,] 0.92150170 0.15699660 0.07849830
[38,] 0.90568774 0.18862453 0.09431226
[39,] 0.88064108 0.23871784 0.11935892
[40,] 0.84319742 0.31360516 0.15680258
[41,] 0.80681749 0.38636502 0.19318251
[42,] 0.75413881 0.49172239 0.24586119
[43,] 0.69177201 0.61645597 0.30822799
[44,] 0.66116811 0.67766378 0.33883189
[45,] 0.59400084 0.81199832 0.40599916
[46,] 0.52684864 0.94630273 0.47315136
[47,] 0.43639167 0.87278334 0.56360833
[48,] 0.34849263 0.69698526 0.65150737
[49,] 0.49184923 0.98369847 0.50815077
[50,] 0.38439282 0.76878565 0.61560718
[51,] 0.30554923 0.61109846 0.69445077
[52,] 0.37258091 0.74516182 0.62741909
> postscript(file="/var/www/html/rcomp/tmp/1oxvb1258728545.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2371k1258728545.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3z2n81258728545.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4dyfx1258728545.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/54b5l1258728545.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 = 61
Frequency = 1
1 2 3 4 5 6
-15.6112937 -15.0505964 -5.6080833 -13.3661219 -17.1001073 -2.5731197
7 8 9 10 11 12
-1.0795404 -1.4033177 1.7424058 -2.4724174 0.2035295 9.4576554
13 14 15 16 17 18
-5.6710127 -9.7370273 -1.8238846 -6.7515746 -4.6370273 -2.7687805
19 20 21 22 23 24
-9.2933854 -2.1785623 1.2377908 -1.8799669 -3.7724174 -3.2047223
25 26 27 28 29 30
-3.8581459 -5.8680782 6.8110790 -7.3819232 -1.8496182 0.3275826
31 32 33 34 35 36
-4.0567413 2.2719268 5.9972340 5.9734567 6.0705222 4.1005950
37 38 39 40 41 42
0.3005950 -1.3122718 10.3494036 -1.1802427 2.0501059 6.7292631
43 44 45 46 47 48
4.2782223 2.5352827 1.5870259 4.4011467 5.3246481 7.7610164
49 50 51 52 53 54
1.8134618 1.7217136 4.2263286 5.7678636 -3.3159087 7.8556991
55 56 57 58 59 60
2.5610164 -2.4181409 10.1962558 9.9035295 3.8379414 17.1287114
61
2.7010214
> postscript(file="/var/www/html/rcomp/tmp/6wzlq1258728545.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 = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 -15.6112937 NA
1 -15.0505964 -15.6112937
2 -5.6080833 -15.0505964
3 -13.3661219 -5.6080833
4 -17.1001073 -13.3661219
5 -2.5731197 -17.1001073
6 -1.0795404 -2.5731197
7 -1.4033177 -1.0795404
8 1.7424058 -1.4033177
9 -2.4724174 1.7424058
10 0.2035295 -2.4724174
11 9.4576554 0.2035295
12 -5.6710127 9.4576554
13 -9.7370273 -5.6710127
14 -1.8238846 -9.7370273
15 -6.7515746 -1.8238846
16 -4.6370273 -6.7515746
17 -2.7687805 -4.6370273
18 -9.2933854 -2.7687805
19 -2.1785623 -9.2933854
20 1.2377908 -2.1785623
21 -1.8799669 1.2377908
22 -3.7724174 -1.8799669
23 -3.2047223 -3.7724174
24 -3.8581459 -3.2047223
25 -5.8680782 -3.8581459
26 6.8110790 -5.8680782
27 -7.3819232 6.8110790
28 -1.8496182 -7.3819232
29 0.3275826 -1.8496182
30 -4.0567413 0.3275826
31 2.2719268 -4.0567413
32 5.9972340 2.2719268
33 5.9734567 5.9972340
34 6.0705222 5.9734567
35 4.1005950 6.0705222
36 0.3005950 4.1005950
37 -1.3122718 0.3005950
38 10.3494036 -1.3122718
39 -1.1802427 10.3494036
40 2.0501059 -1.1802427
41 6.7292631 2.0501059
42 4.2782223 6.7292631
43 2.5352827 4.2782223
44 1.5870259 2.5352827
45 4.4011467 1.5870259
46 5.3246481 4.4011467
47 7.7610164 5.3246481
48 1.8134618 7.7610164
49 1.7217136 1.8134618
50 4.2263286 1.7217136
51 5.7678636 4.2263286
52 -3.3159087 5.7678636
53 7.8556991 -3.3159087
54 2.5610164 7.8556991
55 -2.4181409 2.5610164
56 10.1962558 -2.4181409
57 9.9035295 10.1962558
58 3.8379414 9.9035295
59 17.1287114 3.8379414
60 2.7010214 17.1287114
61 NA 2.7010214
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -15.0505964 -15.6112937
[2,] -5.6080833 -15.0505964
[3,] -13.3661219 -5.6080833
[4,] -17.1001073 -13.3661219
[5,] -2.5731197 -17.1001073
[6,] -1.0795404 -2.5731197
[7,] -1.4033177 -1.0795404
[8,] 1.7424058 -1.4033177
[9,] -2.4724174 1.7424058
[10,] 0.2035295 -2.4724174
[11,] 9.4576554 0.2035295
[12,] -5.6710127 9.4576554
[13,] -9.7370273 -5.6710127
[14,] -1.8238846 -9.7370273
[15,] -6.7515746 -1.8238846
[16,] -4.6370273 -6.7515746
[17,] -2.7687805 -4.6370273
[18,] -9.2933854 -2.7687805
[19,] -2.1785623 -9.2933854
[20,] 1.2377908 -2.1785623
[21,] -1.8799669 1.2377908
[22,] -3.7724174 -1.8799669
[23,] -3.2047223 -3.7724174
[24,] -3.8581459 -3.2047223
[25,] -5.8680782 -3.8581459
[26,] 6.8110790 -5.8680782
[27,] -7.3819232 6.8110790
[28,] -1.8496182 -7.3819232
[29,] 0.3275826 -1.8496182
[30,] -4.0567413 0.3275826
[31,] 2.2719268 -4.0567413
[32,] 5.9972340 2.2719268
[33,] 5.9734567 5.9972340
[34,] 6.0705222 5.9734567
[35,] 4.1005950 6.0705222
[36,] 0.3005950 4.1005950
[37,] -1.3122718 0.3005950
[38,] 10.3494036 -1.3122718
[39,] -1.1802427 10.3494036
[40,] 2.0501059 -1.1802427
[41,] 6.7292631 2.0501059
[42,] 4.2782223 6.7292631
[43,] 2.5352827 4.2782223
[44,] 1.5870259 2.5352827
[45,] 4.4011467 1.5870259
[46,] 5.3246481 4.4011467
[47,] 7.7610164 5.3246481
[48,] 1.8134618 7.7610164
[49,] 1.7217136 1.8134618
[50,] 4.2263286 1.7217136
[51,] 5.7678636 4.2263286
[52,] -3.3159087 5.7678636
[53,] 7.8556991 -3.3159087
[54,] 2.5610164 7.8556991
[55,] -2.4181409 2.5610164
[56,] 10.1962558 -2.4181409
[57,] 9.9035295 10.1962558
[58,] 3.8379414 9.9035295
[59,] 17.1287114 3.8379414
[60,] 2.7010214 17.1287114
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -15.0505964 -15.6112937
2 -5.6080833 -15.0505964
3 -13.3661219 -5.6080833
4 -17.1001073 -13.3661219
5 -2.5731197 -17.1001073
6 -1.0795404 -2.5731197
7 -1.4033177 -1.0795404
8 1.7424058 -1.4033177
9 -2.4724174 1.7424058
10 0.2035295 -2.4724174
11 9.4576554 0.2035295
12 -5.6710127 9.4576554
13 -9.7370273 -5.6710127
14 -1.8238846 -9.7370273
15 -6.7515746 -1.8238846
16 -4.6370273 -6.7515746
17 -2.7687805 -4.6370273
18 -9.2933854 -2.7687805
19 -2.1785623 -9.2933854
20 1.2377908 -2.1785623
21 -1.8799669 1.2377908
22 -3.7724174 -1.8799669
23 -3.2047223 -3.7724174
24 -3.8581459 -3.2047223
25 -5.8680782 -3.8581459
26 6.8110790 -5.8680782
27 -7.3819232 6.8110790
28 -1.8496182 -7.3819232
29 0.3275826 -1.8496182
30 -4.0567413 0.3275826
31 2.2719268 -4.0567413
32 5.9972340 2.2719268
33 5.9734567 5.9972340
34 6.0705222 5.9734567
35 4.1005950 6.0705222
36 0.3005950 4.1005950
37 -1.3122718 0.3005950
38 10.3494036 -1.3122718
39 -1.1802427 10.3494036
40 2.0501059 -1.1802427
41 6.7292631 2.0501059
42 4.2782223 6.7292631
43 2.5352827 4.2782223
44 1.5870259 2.5352827
45 4.4011467 1.5870259
46 5.3246481 4.4011467
47 7.7610164 5.3246481
48 1.8134618 7.7610164
49 1.7217136 1.8134618
50 4.2263286 1.7217136
51 5.7678636 4.2263286
52 -3.3159087 5.7678636
53 7.8556991 -3.3159087
54 2.5610164 7.8556991
55 -2.4181409 2.5610164
56 10.1962558 -2.4181409
57 9.9035295 10.1962558
58 3.8379414 9.9035295
59 17.1287114 3.8379414
60 2.7010214 17.1287114
> 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/7767x1258728545.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/81del1258728545.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9n9zm1258728545.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10wsk41258728545.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11lj9l1258728545.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/12cahz1258728545.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/13la2z1258728545.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/14lymg1258728545.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/15o8ft1258728545.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/16mp501258728545.tab")
+ }
> system("convert tmp/1oxvb1258728545.ps tmp/1oxvb1258728545.png")
> system("convert tmp/2371k1258728545.ps tmp/2371k1258728545.png")
> system("convert tmp/3z2n81258728545.ps tmp/3z2n81258728545.png")
> system("convert tmp/4dyfx1258728545.ps tmp/4dyfx1258728545.png")
> system("convert tmp/54b5l1258728545.ps tmp/54b5l1258728545.png")
> system("convert tmp/6wzlq1258728545.ps tmp/6wzlq1258728545.png")
> system("convert tmp/7767x1258728545.ps tmp/7767x1258728545.png")
> system("convert tmp/81del1258728545.ps tmp/81del1258728545.png")
> system("convert tmp/9n9zm1258728545.ps tmp/9n9zm1258728545.png")
> system("convert tmp/10wsk41258728545.ps tmp/10wsk41258728545.png")
>
>
> proc.time()
user system elapsed
2.484 1.577 2.871