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
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Type 'q()' to quit R.
> x <- array(list(113,14.3,110,14.2,107,15.9,103,15.3,98,15.5,98,15.1,137,15,148,12.1,147,15.8,139,16.9,130,15.1,128,13.7,127,14.8,123,14.7,118,16,114,15.4,108,15,111,15.5,151,15.1,159,11.7,158,16.3,148,16.7,138,15,137,14.9,136,14.6,133,15.3,126,17.9,120,16.4,114,15.4,116,17.9,153,15.9,162,13.9,161,17.8,149,17.9,139,17.4,135,16.7,130,16,127,16.6,122,19.1,117,17.8,112,17.2,113,18.6,149,16.3,157,15.1,157,19.2,147,17.7,137,19.1,132,18,125,17.5,123,17.8,117,21.1,114,17.2,111,19.4,112,19.8,144,17.6,150,16.2,149,19.5,134,19.9,123,20,116,17.3),dim=c(2,60),dimnames=list(c('WK<25j','ExpBe'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('WK<25j','ExpBe'),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 = '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
WK<25j ExpBe
1 113 14.3
2 110 14.2
3 107 15.9
4 103 15.3
5 98 15.5
6 98 15.1
7 137 15.0
8 148 12.1
9 147 15.8
10 139 16.9
11 130 15.1
12 128 13.7
13 127 14.8
14 123 14.7
15 118 16.0
16 114 15.4
17 108 15.0
18 111 15.5
19 151 15.1
20 159 11.7
21 158 16.3
22 148 16.7
23 138 15.0
24 137 14.9
25 136 14.6
26 133 15.3
27 126 17.9
28 120 16.4
29 114 15.4
30 116 17.9
31 153 15.9
32 162 13.9
33 161 17.8
34 149 17.9
35 139 17.4
36 135 16.7
37 130 16.0
38 127 16.6
39 122 19.1
40 117 17.8
41 112 17.2
42 113 18.6
43 149 16.3
44 157 15.1
45 157 19.2
46 147 17.7
47 137 19.1
48 132 18.0
49 125 17.5
50 123 17.8
51 117 21.1
52 114 17.2
53 111 19.4
54 112 19.8
55 144 17.6
56 150 16.2
57 149 19.5
58 134 19.9
59 123 20.0
60 116 17.3
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) ExpBe
144.9867 -0.8952
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-33.470 -13.941 -2.216 15.115 31.947
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 144.9867 19.3550 7.491 4.38e-10 ***
ExpBe -0.8952 1.1639 -0.769 0.445
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 17.31 on 58 degrees of freedom
Multiple R-squared: 0.0101, Adjusted R-squared: -0.006971
F-statistic: 0.5915 on 1 and 58 DF, p-value: 0.4449
> 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,] 0.03817951 0.07635901 0.96182049
[2,] 0.03100775 0.06201551 0.96899225
[3,] 0.46990888 0.93981775 0.53009112
[4,] 0.38306149 0.76612298 0.61693851
[5,] 0.84426556 0.31146888 0.15573444
[6,] 0.90490758 0.19018485 0.09509242
[7,] 0.86744497 0.26511006 0.13255503
[8,] 0.81445869 0.37108262 0.18554131
[9,] 0.75412106 0.49175788 0.24587894
[10,] 0.69027734 0.61944533 0.30972266
[11,] 0.62870664 0.74258673 0.37129336
[12,] 0.59730211 0.80539578 0.40269789
[13,] 0.64393567 0.71212866 0.35606433
[14,] 0.66006163 0.67987675 0.33993837
[15,] 0.76983121 0.46033757 0.23016879
[16,] 0.77439186 0.45121628 0.22560814
[17,] 0.91755691 0.16488617 0.08244309
[18,] 0.93664806 0.12670389 0.06335194
[19,] 0.91569737 0.16860527 0.08430263
[20,] 0.88822187 0.22355627 0.11177813
[21,] 0.85384228 0.29231544 0.14615772
[22,] 0.81316769 0.37366462 0.18683231
[23,] 0.76332611 0.47334778 0.23667389
[24,] 0.73649372 0.52701255 0.26350628
[25,] 0.78767047 0.42465906 0.21232953
[26,] 0.76652254 0.46695493 0.23347746
[27,] 0.79126361 0.41747277 0.20873639
[28,] 0.82676679 0.34646641 0.17323321
[29,] 0.92691165 0.14617669 0.07308835
[30,] 0.93486861 0.13026278 0.06513139
[31,] 0.91248476 0.17503049 0.08751524
[32,] 0.87725501 0.24548998 0.12274499
[33,] 0.83765172 0.32469657 0.16234828
[34,] 0.79482217 0.41035565 0.20517783
[35,] 0.73866202 0.52267596 0.26133798
[36,] 0.71840818 0.56318363 0.28159182
[37,] 0.76834758 0.46330484 0.23165242
[38,] 0.77159809 0.45680381 0.22840191
[39,] 0.73738074 0.52523851 0.26261926
[40,] 0.74433260 0.51133480 0.25566740
[41,] 0.87491999 0.25016001 0.12508001
[42,] 0.87680709 0.24638581 0.12319291
[43,] 0.84520974 0.30958053 0.15479026
[44,] 0.77792350 0.44415300 0.22207650
[45,] 0.69759180 0.60481640 0.30240820
[46,] 0.61058526 0.77882949 0.38941474
[47,] 0.50417270 0.99165461 0.49582730
[48,] 0.53579734 0.92840531 0.46420266
[49,] 0.52940878 0.94118245 0.47059122
[50,] 0.54644533 0.90710935 0.45355467
[51,] 0.40942220 0.81884440 0.59057780
> postscript(file="/var/www/html/rcomp/tmp/11tam1261152735.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2yo6u1261152735.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3i71x1261152735.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/477n51261152735.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5donw1261152735.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
-19.1857814 -22.2752982 -23.7535123 -28.2906132 -33.1115796 -33.4696468
7 8 9 10 11 12
5.4408363 13.8448487 16.1569709 9.1416558 -1.4696468 -4.7228823
13 14 15 16 17 18
-4.7381973 -8.8277141 -12.6639955 -17.2010964 -23.5591637 -20.1115796
19 20 21 22 23 24
19.5303532 24.4867814 27.6045550 17.9626222 6.4408363 5.3513195
25 26 27 28 29 30
4.0827691 1.7093868 -2.9631760 -10.3059282 -17.2010964 -12.9631760
31 32 33 34 35 36
22.2464877 29.4561514 31.9473072 20.0368240 9.5892399 4.9626222
37 38 39 40 41 42
-0.6639955 -3.1268946 -5.8889742 -12.0526928 -17.5897937 -15.3365583
43 44 45 46 47 48
18.6045550 25.5303532 29.2005426 17.8577904 9.1110258 3.1263408
49 50 51 52 53 54
-4.3212433 -6.0526928 -9.0986379 -15.5897937 -16.6204237 -15.2623565
55 56 57 58 59 60
14.7682736 19.5150381 21.4690931 6.8271603 -4.0833228 -13.5002769
> postscript(file="/var/www/html/rcomp/tmp/6cf211261152735.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 -19.1857814 NA
1 -22.2752982 -19.1857814
2 -23.7535123 -22.2752982
3 -28.2906132 -23.7535123
4 -33.1115796 -28.2906132
5 -33.4696468 -33.1115796
6 5.4408363 -33.4696468
7 13.8448487 5.4408363
8 16.1569709 13.8448487
9 9.1416558 16.1569709
10 -1.4696468 9.1416558
11 -4.7228823 -1.4696468
12 -4.7381973 -4.7228823
13 -8.8277141 -4.7381973
14 -12.6639955 -8.8277141
15 -17.2010964 -12.6639955
16 -23.5591637 -17.2010964
17 -20.1115796 -23.5591637
18 19.5303532 -20.1115796
19 24.4867814 19.5303532
20 27.6045550 24.4867814
21 17.9626222 27.6045550
22 6.4408363 17.9626222
23 5.3513195 6.4408363
24 4.0827691 5.3513195
25 1.7093868 4.0827691
26 -2.9631760 1.7093868
27 -10.3059282 -2.9631760
28 -17.2010964 -10.3059282
29 -12.9631760 -17.2010964
30 22.2464877 -12.9631760
31 29.4561514 22.2464877
32 31.9473072 29.4561514
33 20.0368240 31.9473072
34 9.5892399 20.0368240
35 4.9626222 9.5892399
36 -0.6639955 4.9626222
37 -3.1268946 -0.6639955
38 -5.8889742 -3.1268946
39 -12.0526928 -5.8889742
40 -17.5897937 -12.0526928
41 -15.3365583 -17.5897937
42 18.6045550 -15.3365583
43 25.5303532 18.6045550
44 29.2005426 25.5303532
45 17.8577904 29.2005426
46 9.1110258 17.8577904
47 3.1263408 9.1110258
48 -4.3212433 3.1263408
49 -6.0526928 -4.3212433
50 -9.0986379 -6.0526928
51 -15.5897937 -9.0986379
52 -16.6204237 -15.5897937
53 -15.2623565 -16.6204237
54 14.7682736 -15.2623565
55 19.5150381 14.7682736
56 21.4690931 19.5150381
57 6.8271603 21.4690931
58 -4.0833228 6.8271603
59 -13.5002769 -4.0833228
60 NA -13.5002769
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -22.2752982 -19.1857814
[2,] -23.7535123 -22.2752982
[3,] -28.2906132 -23.7535123
[4,] -33.1115796 -28.2906132
[5,] -33.4696468 -33.1115796
[6,] 5.4408363 -33.4696468
[7,] 13.8448487 5.4408363
[8,] 16.1569709 13.8448487
[9,] 9.1416558 16.1569709
[10,] -1.4696468 9.1416558
[11,] -4.7228823 -1.4696468
[12,] -4.7381973 -4.7228823
[13,] -8.8277141 -4.7381973
[14,] -12.6639955 -8.8277141
[15,] -17.2010964 -12.6639955
[16,] -23.5591637 -17.2010964
[17,] -20.1115796 -23.5591637
[18,] 19.5303532 -20.1115796
[19,] 24.4867814 19.5303532
[20,] 27.6045550 24.4867814
[21,] 17.9626222 27.6045550
[22,] 6.4408363 17.9626222
[23,] 5.3513195 6.4408363
[24,] 4.0827691 5.3513195
[25,] 1.7093868 4.0827691
[26,] -2.9631760 1.7093868
[27,] -10.3059282 -2.9631760
[28,] -17.2010964 -10.3059282
[29,] -12.9631760 -17.2010964
[30,] 22.2464877 -12.9631760
[31,] 29.4561514 22.2464877
[32,] 31.9473072 29.4561514
[33,] 20.0368240 31.9473072
[34,] 9.5892399 20.0368240
[35,] 4.9626222 9.5892399
[36,] -0.6639955 4.9626222
[37,] -3.1268946 -0.6639955
[38,] -5.8889742 -3.1268946
[39,] -12.0526928 -5.8889742
[40,] -17.5897937 -12.0526928
[41,] -15.3365583 -17.5897937
[42,] 18.6045550 -15.3365583
[43,] 25.5303532 18.6045550
[44,] 29.2005426 25.5303532
[45,] 17.8577904 29.2005426
[46,] 9.1110258 17.8577904
[47,] 3.1263408 9.1110258
[48,] -4.3212433 3.1263408
[49,] -6.0526928 -4.3212433
[50,] -9.0986379 -6.0526928
[51,] -15.5897937 -9.0986379
[52,] -16.6204237 -15.5897937
[53,] -15.2623565 -16.6204237
[54,] 14.7682736 -15.2623565
[55,] 19.5150381 14.7682736
[56,] 21.4690931 19.5150381
[57,] 6.8271603 21.4690931
[58,] -4.0833228 6.8271603
[59,] -13.5002769 -4.0833228
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -22.2752982 -19.1857814
2 -23.7535123 -22.2752982
3 -28.2906132 -23.7535123
4 -33.1115796 -28.2906132
5 -33.4696468 -33.1115796
6 5.4408363 -33.4696468
7 13.8448487 5.4408363
8 16.1569709 13.8448487
9 9.1416558 16.1569709
10 -1.4696468 9.1416558
11 -4.7228823 -1.4696468
12 -4.7381973 -4.7228823
13 -8.8277141 -4.7381973
14 -12.6639955 -8.8277141
15 -17.2010964 -12.6639955
16 -23.5591637 -17.2010964
17 -20.1115796 -23.5591637
18 19.5303532 -20.1115796
19 24.4867814 19.5303532
20 27.6045550 24.4867814
21 17.9626222 27.6045550
22 6.4408363 17.9626222
23 5.3513195 6.4408363
24 4.0827691 5.3513195
25 1.7093868 4.0827691
26 -2.9631760 1.7093868
27 -10.3059282 -2.9631760
28 -17.2010964 -10.3059282
29 -12.9631760 -17.2010964
30 22.2464877 -12.9631760
31 29.4561514 22.2464877
32 31.9473072 29.4561514
33 20.0368240 31.9473072
34 9.5892399 20.0368240
35 4.9626222 9.5892399
36 -0.6639955 4.9626222
37 -3.1268946 -0.6639955
38 -5.8889742 -3.1268946
39 -12.0526928 -5.8889742
40 -17.5897937 -12.0526928
41 -15.3365583 -17.5897937
42 18.6045550 -15.3365583
43 25.5303532 18.6045550
44 29.2005426 25.5303532
45 17.8577904 29.2005426
46 9.1110258 17.8577904
47 3.1263408 9.1110258
48 -4.3212433 3.1263408
49 -6.0526928 -4.3212433
50 -9.0986379 -6.0526928
51 -15.5897937 -9.0986379
52 -16.6204237 -15.5897937
53 -15.2623565 -16.6204237
54 14.7682736 -15.2623565
55 19.5150381 14.7682736
56 21.4690931 19.5150381
57 6.8271603 21.4690931
58 -4.0833228 6.8271603
59 -13.5002769 -4.0833228
> 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/7e0sy1261152735.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8f61d1261152735.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9pk2f1261152735.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10p5xm1261152735.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11elf71261152735.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/12lgmr1261152735.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/13u7oh1261152735.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/14wj321261152735.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/15b6yn1261152735.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/16jawx1261152735.tab")
+ }
>
> try(system("convert tmp/11tam1261152735.ps tmp/11tam1261152735.png",intern=TRUE))
character(0)
> try(system("convert tmp/2yo6u1261152735.ps tmp/2yo6u1261152735.png",intern=TRUE))
character(0)
> try(system("convert tmp/3i71x1261152735.ps tmp/3i71x1261152735.png",intern=TRUE))
character(0)
> try(system("convert tmp/477n51261152735.ps tmp/477n51261152735.png",intern=TRUE))
character(0)
> try(system("convert tmp/5donw1261152735.ps tmp/5donw1261152735.png",intern=TRUE))
character(0)
> try(system("convert tmp/6cf211261152735.ps tmp/6cf211261152735.png",intern=TRUE))
character(0)
> try(system("convert tmp/7e0sy1261152735.ps tmp/7e0sy1261152735.png",intern=TRUE))
character(0)
> try(system("convert tmp/8f61d1261152735.ps tmp/8f61d1261152735.png",intern=TRUE))
character(0)
> try(system("convert tmp/9pk2f1261152735.ps tmp/9pk2f1261152735.png",intern=TRUE))
character(0)
> try(system("convert tmp/10p5xm1261152735.ps tmp/10p5xm1261152735.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.476 1.570 4.665