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(101.09,0,102.71,0,102.11,0,101.68,0,101.7,0,101.53,0,101.76,0,101.15,0,100.92,0,100.73,0,100.55,0,102.15,0,100.79,0,99.93,0,100.03,0,100.25,0,99.6,0,100.16,0,100.49,0,99.72,0,100.14,0,98.48,0,100.38,0,101.45,0,98.42,0,98.6,0,100.06,0,98.62,0,100.84,0,100.02,0,97.95,0,98.32,0,98.27,0,97.22,0,99.28,0,100.38,0,99.02,0,100.32,0,99.81,0,100.6,0,101.19,0,100.47,0,101.77,0,102.32,0,102.39,0,101.16,0,100.63,0,101.48,0,101.44,1,100.09,1,100.7,1,100.78,1,99.81,1,98.45,1,98.49,1,97.48,1,97.91,1,96.94,1,98.53,1,96.82,1,95.76,1),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
1 101.09 0
2 102.71 0
3 102.11 0
4 101.68 0
5 101.70 0
6 101.53 0
7 101.76 0
8 101.15 0
9 100.92 0
10 100.73 0
11 100.55 0
12 102.15 0
13 100.79 0
14 99.93 0
15 100.03 0
16 100.25 0
17 99.60 0
18 100.16 0
19 100.49 0
20 99.72 0
21 100.14 0
22 98.48 0
23 100.38 0
24 101.45 0
25 98.42 0
26 98.60 0
27 100.06 0
28 98.62 0
29 100.84 0
30 100.02 0
31 97.95 0
32 98.32 0
33 98.27 0
34 97.22 0
35 99.28 0
36 100.38 0
37 99.02 0
38 100.32 0
39 99.81 0
40 100.60 0
41 101.19 0
42 100.47 0
43 101.77 0
44 102.32 0
45 102.39 0
46 101.16 0
47 100.63 0
48 101.48 0
49 101.44 1
50 100.09 1
51 100.70 1
52 100.78 1
53 99.81 1
54 98.45 1
55 98.49 1
56 97.48 1
57 97.91 1
58 96.94 1
59 98.53 1
60 96.82 1
61 95.76 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
100.388 -1.681
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-3.168333 -0.788333 -0.008333 1.091667 2.732308
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 100.3883 0.2002 501.337 < 2e-16 ***
X -1.6806 0.4338 -3.875 0.000270 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.387 on 59 degrees of freedom
Multiple R-squared: 0.2028, Adjusted R-squared: 0.1893
F-statistic: 15.01 on 1 and 59 DF, p-value: 0.0002705
> 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,] 0.144908018 0.28981604 0.8550920
[2,] 0.065817172 0.13163434 0.9341828
[3,] 0.026004185 0.05200837 0.9739958
[4,] 0.016289305 0.03257861 0.9837107
[5,] 0.013018769 0.02603754 0.9869812
[6,] 0.011923516 0.02384703 0.9880765
[7,] 0.011949168 0.02389834 0.9880508
[8,] 0.009448533 0.01889707 0.9905515
[9,] 0.006565247 0.01313049 0.9934348
[10,] 0.014408881 0.02881776 0.9855911
[11,] 0.018008631 0.03601726 0.9819914
[12,] 0.015385735 0.03077147 0.9846143
[13,] 0.023764342 0.04752868 0.9762357
[14,] 0.018623605 0.03724721 0.9813764
[15,] 0.011892770 0.02378554 0.9881072
[16,] 0.012302434 0.02460487 0.9876976
[17,] 0.008690870 0.01738174 0.9913091
[18,] 0.032402801 0.06480560 0.9675972
[19,] 0.021015711 0.04203142 0.9789843
[20,] 0.016351212 0.03270242 0.9836488
[21,] 0.041733596 0.08346719 0.9582664
[22,] 0.066443551 0.13288710 0.9335564
[23,] 0.047058328 0.09411666 0.9529417
[24,] 0.065810245 0.13162049 0.9341898
[25,] 0.046541078 0.09308216 0.9534589
[26,] 0.032009126 0.06401825 0.9679909
[27,] 0.075313470 0.15062694 0.9246865
[28,] 0.112132837 0.22426567 0.8878672
[29,] 0.164875802 0.32975160 0.8351242
[30,] 0.434420923 0.86884185 0.5655791
[31,] 0.424575308 0.84915062 0.5754247
[32,] 0.357103478 0.71420696 0.6428965
[33,] 0.391972221 0.78394444 0.6080278
[34,] 0.334263184 0.66852637 0.6657368
[35,] 0.311876051 0.62375210 0.6881239
[36,] 0.259953658 0.51990732 0.7400463
[37,] 0.211763628 0.42352726 0.7882364
[38,] 0.176954339 0.35390868 0.8230457
[39,] 0.149218059 0.29843612 0.8507819
[40,] 0.145809260 0.29161852 0.8541907
[41,] 0.148915052 0.29783010 0.8510849
[42,] 0.108113974 0.21622795 0.8918860
[43,] 0.076101429 0.15220286 0.9238986
[44,] 0.052649107 0.10529821 0.9473509
[45,] 0.100649136 0.20129827 0.8993509
[46,] 0.102894367 0.20578873 0.8971056
[47,] 0.172007660 0.34401532 0.8279923
[48,] 0.409841616 0.81968323 0.5901584
[49,] 0.615791615 0.76841677 0.3842084
[50,] 0.587543937 0.82491213 0.4124561
[51,] 0.580779861 0.83844028 0.4192201
[52,] 0.443159490 0.88631898 0.5568405
> postscript(file="/var/www/html/rcomp/tmp/190di1261237463.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/277we1261237463.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/38a811261237463.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4199b1261237463.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5rdr01261237463.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
0.701666667 2.321666667 1.721666667 1.291666667 1.311666667 1.141666667
7 8 9 10 11 12
1.371666667 0.761666667 0.531666667 0.341666667 0.161666667 1.761666667
13 14 15 16 17 18
0.401666667 -0.458333333 -0.358333333 -0.138333333 -0.788333333 -0.228333333
19 20 21 22 23 24
0.101666667 -0.668333333 -0.248333333 -1.908333333 -0.008333333 1.061666667
25 26 27 28 29 30
-1.968333333 -1.788333333 -0.328333333 -1.768333333 0.451666667 -0.368333333
31 32 33 34 35 36
-2.438333333 -2.068333333 -2.118333333 -3.168333333 -1.108333333 -0.008333333
37 38 39 40 41 42
-1.368333333 -0.068333333 -0.578333333 0.211666667 0.801666667 0.081666667
43 44 45 46 47 48
1.381666667 1.931666667 2.001666667 0.771666667 0.241666667 1.091666667
49 50 51 52 53 54
2.732307692 1.382307692 1.992307692 2.072307692 1.102307692 -0.257692308
55 56 57 58 59 60
-0.217692308 -1.227692308 -0.797692308 -1.767692308 -0.177692308 -1.887692308
61
-2.947692308
> postscript(file="/var/www/html/rcomp/tmp/6hljn1261237463.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 0.701666667 NA
1 2.321666667 0.701666667
2 1.721666667 2.321666667
3 1.291666667 1.721666667
4 1.311666667 1.291666667
5 1.141666667 1.311666667
6 1.371666667 1.141666667
7 0.761666667 1.371666667
8 0.531666667 0.761666667
9 0.341666667 0.531666667
10 0.161666667 0.341666667
11 1.761666667 0.161666667
12 0.401666667 1.761666667
13 -0.458333333 0.401666667
14 -0.358333333 -0.458333333
15 -0.138333333 -0.358333333
16 -0.788333333 -0.138333333
17 -0.228333333 -0.788333333
18 0.101666667 -0.228333333
19 -0.668333333 0.101666667
20 -0.248333333 -0.668333333
21 -1.908333333 -0.248333333
22 -0.008333333 -1.908333333
23 1.061666667 -0.008333333
24 -1.968333333 1.061666667
25 -1.788333333 -1.968333333
26 -0.328333333 -1.788333333
27 -1.768333333 -0.328333333
28 0.451666667 -1.768333333
29 -0.368333333 0.451666667
30 -2.438333333 -0.368333333
31 -2.068333333 -2.438333333
32 -2.118333333 -2.068333333
33 -3.168333333 -2.118333333
34 -1.108333333 -3.168333333
35 -0.008333333 -1.108333333
36 -1.368333333 -0.008333333
37 -0.068333333 -1.368333333
38 -0.578333333 -0.068333333
39 0.211666667 -0.578333333
40 0.801666667 0.211666667
41 0.081666667 0.801666667
42 1.381666667 0.081666667
43 1.931666667 1.381666667
44 2.001666667 1.931666667
45 0.771666667 2.001666667
46 0.241666667 0.771666667
47 1.091666667 0.241666667
48 2.732307692 1.091666667
49 1.382307692 2.732307692
50 1.992307692 1.382307692
51 2.072307692 1.992307692
52 1.102307692 2.072307692
53 -0.257692308 1.102307692
54 -0.217692308 -0.257692308
55 -1.227692308 -0.217692308
56 -0.797692308 -1.227692308
57 -1.767692308 -0.797692308
58 -0.177692308 -1.767692308
59 -1.887692308 -0.177692308
60 -2.947692308 -1.887692308
61 NA -2.947692308
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 2.321666667 0.701666667
[2,] 1.721666667 2.321666667
[3,] 1.291666667 1.721666667
[4,] 1.311666667 1.291666667
[5,] 1.141666667 1.311666667
[6,] 1.371666667 1.141666667
[7,] 0.761666667 1.371666667
[8,] 0.531666667 0.761666667
[9,] 0.341666667 0.531666667
[10,] 0.161666667 0.341666667
[11,] 1.761666667 0.161666667
[12,] 0.401666667 1.761666667
[13,] -0.458333333 0.401666667
[14,] -0.358333333 -0.458333333
[15,] -0.138333333 -0.358333333
[16,] -0.788333333 -0.138333333
[17,] -0.228333333 -0.788333333
[18,] 0.101666667 -0.228333333
[19,] -0.668333333 0.101666667
[20,] -0.248333333 -0.668333333
[21,] -1.908333333 -0.248333333
[22,] -0.008333333 -1.908333333
[23,] 1.061666667 -0.008333333
[24,] -1.968333333 1.061666667
[25,] -1.788333333 -1.968333333
[26,] -0.328333333 -1.788333333
[27,] -1.768333333 -0.328333333
[28,] 0.451666667 -1.768333333
[29,] -0.368333333 0.451666667
[30,] -2.438333333 -0.368333333
[31,] -2.068333333 -2.438333333
[32,] -2.118333333 -2.068333333
[33,] -3.168333333 -2.118333333
[34,] -1.108333333 -3.168333333
[35,] -0.008333333 -1.108333333
[36,] -1.368333333 -0.008333333
[37,] -0.068333333 -1.368333333
[38,] -0.578333333 -0.068333333
[39,] 0.211666667 -0.578333333
[40,] 0.801666667 0.211666667
[41,] 0.081666667 0.801666667
[42,] 1.381666667 0.081666667
[43,] 1.931666667 1.381666667
[44,] 2.001666667 1.931666667
[45,] 0.771666667 2.001666667
[46,] 0.241666667 0.771666667
[47,] 1.091666667 0.241666667
[48,] 2.732307692 1.091666667
[49,] 1.382307692 2.732307692
[50,] 1.992307692 1.382307692
[51,] 2.072307692 1.992307692
[52,] 1.102307692 2.072307692
[53,] -0.257692308 1.102307692
[54,] -0.217692308 -0.257692308
[55,] -1.227692308 -0.217692308
[56,] -0.797692308 -1.227692308
[57,] -1.767692308 -0.797692308
[58,] -0.177692308 -1.767692308
[59,] -1.887692308 -0.177692308
[60,] -2.947692308 -1.887692308
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 2.321666667 0.701666667
2 1.721666667 2.321666667
3 1.291666667 1.721666667
4 1.311666667 1.291666667
5 1.141666667 1.311666667
6 1.371666667 1.141666667
7 0.761666667 1.371666667
8 0.531666667 0.761666667
9 0.341666667 0.531666667
10 0.161666667 0.341666667
11 1.761666667 0.161666667
12 0.401666667 1.761666667
13 -0.458333333 0.401666667
14 -0.358333333 -0.458333333
15 -0.138333333 -0.358333333
16 -0.788333333 -0.138333333
17 -0.228333333 -0.788333333
18 0.101666667 -0.228333333
19 -0.668333333 0.101666667
20 -0.248333333 -0.668333333
21 -1.908333333 -0.248333333
22 -0.008333333 -1.908333333
23 1.061666667 -0.008333333
24 -1.968333333 1.061666667
25 -1.788333333 -1.968333333
26 -0.328333333 -1.788333333
27 -1.768333333 -0.328333333
28 0.451666667 -1.768333333
29 -0.368333333 0.451666667
30 -2.438333333 -0.368333333
31 -2.068333333 -2.438333333
32 -2.118333333 -2.068333333
33 -3.168333333 -2.118333333
34 -1.108333333 -3.168333333
35 -0.008333333 -1.108333333
36 -1.368333333 -0.008333333
37 -0.068333333 -1.368333333
38 -0.578333333 -0.068333333
39 0.211666667 -0.578333333
40 0.801666667 0.211666667
41 0.081666667 0.801666667
42 1.381666667 0.081666667
43 1.931666667 1.381666667
44 2.001666667 1.931666667
45 0.771666667 2.001666667
46 0.241666667 0.771666667
47 1.091666667 0.241666667
48 2.732307692 1.091666667
49 1.382307692 2.732307692
50 1.992307692 1.382307692
51 2.072307692 1.992307692
52 1.102307692 2.072307692
53 -0.257692308 1.102307692
54 -0.217692308 -0.257692308
55 -1.227692308 -0.217692308
56 -0.797692308 -1.227692308
57 -1.767692308 -0.797692308
58 -0.177692308 -1.767692308
59 -1.887692308 -0.177692308
60 -2.947692308 -1.887692308
> 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/7okmn1261237463.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8pfsd1261237463.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9256z1261237463.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/105v0m1261237463.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11m3u61261237463.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/12kcso1261237463.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/13suoi1261237463.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/14cyuk1261237463.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/15qyea1261237463.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/16b04p1261237463.tab")
+ }
>
> try(system("convert tmp/190di1261237463.ps tmp/190di1261237463.png",intern=TRUE))
character(0)
> try(system("convert tmp/277we1261237463.ps tmp/277we1261237463.png",intern=TRUE))
character(0)
> try(system("convert tmp/38a811261237463.ps tmp/38a811261237463.png",intern=TRUE))
character(0)
> try(system("convert tmp/4199b1261237463.ps tmp/4199b1261237463.png",intern=TRUE))
character(0)
> try(system("convert tmp/5rdr01261237463.ps tmp/5rdr01261237463.png",intern=TRUE))
character(0)
> try(system("convert tmp/6hljn1261237463.ps tmp/6hljn1261237463.png",intern=TRUE))
character(0)
> try(system("convert tmp/7okmn1261237463.ps tmp/7okmn1261237463.png",intern=TRUE))
character(0)
> try(system("convert tmp/8pfsd1261237463.ps tmp/8pfsd1261237463.png",intern=TRUE))
character(0)
> try(system("convert tmp/9256z1261237463.ps tmp/9256z1261237463.png",intern=TRUE))
character(0)
> try(system("convert tmp/105v0m1261237463.ps tmp/105v0m1261237463.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.551 1.621 10.310