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(8,0,8.1,0,7.7,0,7.5,0,7.6,0,7.8,0,7.8,0,7.8,0,7.5,0,7.5,0,7.1,0,7.5,0,7.5,0,7.6,0,7.7,0,7.7,0,7.9,0,8.1,0,8.2,0,8.2,0,8.2,0,7.9,0,7.3,0,6.9,0,6.6,0,6.7,0,6.9,0,7,0,7.1,0,7.2,0,7.1,0,6.9,0,7,0,6.8,0,6.4,0,6.7,0,6.6,0,6.4,0,6.3,0,6.2,0,6.5,0,6.8,1,6.8,1,6.4,1,6.1,1,5.8,1,6.1,1,7.2,1,7.3,1,6.9,1,6.1,1,5.8,1,6.2,1,7.1,1,7.7,1,7.9,1,7.7,1,7.4,1,7.5,1,8,1,8.1,1),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 8.0 0
2 8.1 0
3 7.7 0
4 7.5 0
5 7.6 0
6 7.8 0
7 7.8 0
8 7.8 0
9 7.5 0
10 7.5 0
11 7.1 0
12 7.5 0
13 7.5 0
14 7.6 0
15 7.7 0
16 7.7 0
17 7.9 0
18 8.1 0
19 8.2 0
20 8.2 0
21 8.2 0
22 7.9 0
23 7.3 0
24 6.9 0
25 6.6 0
26 6.7 0
27 6.9 0
28 7.0 0
29 7.1 0
30 7.2 0
31 7.1 0
32 6.9 0
33 7.0 0
34 6.8 0
35 6.4 0
36 6.7 0
37 6.6 0
38 6.4 0
39 6.3 0
40 6.2 0
41 6.5 0
42 6.8 1
43 6.8 1
44 6.4 1
45 6.1 1
46 5.8 1
47 6.1 1
48 7.2 1
49 7.3 1
50 6.9 1
51 6.1 1
52 5.8 1
53 6.2 1
54 7.1 1
55 7.7 1
56 7.9 1
57 7.7 1
58 7.4 1
59 7.5 1
60 8.0 1
61 8.1 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
7.3049 -0.3599
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.1450 -0.5450 0.1550 0.4951 1.1550
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 7.3049 0.1009 72.396 <2e-16 ***
X -0.3599 0.1762 -2.042 0.0456 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.6461 on 59 degrees of freedom
Multiple R-squared: 0.06602, Adjusted R-squared: 0.05019
F-statistic: 4.171 on 1 and 59 DF, p-value: 0.04561
> 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,] 1.103023e-01 2.206045e-01 0.88969773
[2,] 4.067792e-02 8.135584e-02 0.95932208
[3,] 1.376282e-02 2.752563e-02 0.98623718
[4,] 4.339764e-03 8.679528e-03 0.99566024
[5,] 2.678576e-03 5.357152e-03 0.99732142
[6,] 1.428889e-03 2.857778e-03 0.99857111
[7,] 5.325053e-03 1.065011e-02 0.99467495
[8,] 2.439586e-03 4.879172e-03 0.99756041
[9,] 1.070129e-03 2.140258e-03 0.99892987
[10,] 4.117614e-04 8.235229e-04 0.99958824
[11,] 1.591844e-04 3.183688e-04 0.99984082
[12,] 6.029702e-05 1.205940e-04 0.99993970
[13,] 3.813288e-05 7.626577e-05 0.99996187
[14,] 6.571238e-05 1.314248e-04 0.99993429
[15,] 1.778078e-04 3.556156e-04 0.99982219
[16,] 4.196872e-04 8.393744e-04 0.99958031
[17,] 9.950125e-04 1.990025e-03 0.99900499
[18,] 9.450056e-04 1.890011e-03 0.99905499
[19,] 1.190692e-03 2.381384e-03 0.99880931
[20,] 4.858506e-03 9.717012e-03 0.99514149
[21,] 2.707697e-02 5.415394e-02 0.97292303
[22,] 5.357501e-02 1.071500e-01 0.94642499
[23,] 6.113946e-02 1.222789e-01 0.93886054
[24,] 5.935735e-02 1.187147e-01 0.94064265
[25,] 5.275536e-02 1.055107e-01 0.94724464
[26,] 4.547989e-02 9.095977e-02 0.95452011
[27,] 4.066860e-02 8.133720e-02 0.95933140
[28,] 4.032605e-02 8.065209e-02 0.95967395
[29,] 3.738452e-02 7.476903e-02 0.96261548
[30,] 3.853904e-02 7.707808e-02 0.96146096
[31,] 5.747965e-02 1.149593e-01 0.94252035
[32,] 5.670603e-02 1.134121e-01 0.94329397
[33,] 5.789744e-02 1.157949e-01 0.94210256
[34,] 6.583039e-02 1.316608e-01 0.93416961
[35,] 7.573682e-02 1.514736e-01 0.92426318
[36,] 8.899844e-02 1.779969e-01 0.91100156
[37,] 7.826484e-02 1.565297e-01 0.92173516
[38,] 5.349422e-02 1.069884e-01 0.94650578
[39,] 3.527602e-02 7.055204e-02 0.96472398
[40,] 2.784235e-02 5.568471e-02 0.97215765
[41,] 3.111138e-02 6.222276e-02 0.96888862
[42,] 6.228617e-02 1.245723e-01 0.93771383
[43,] 8.481042e-02 1.696208e-01 0.91518958
[44,] 6.707008e-02 1.341402e-01 0.93292992
[45,] 5.109074e-02 1.021815e-01 0.94890926
[46,] 3.393659e-02 6.787319e-02 0.96606341
[47,] 6.276074e-02 1.255215e-01 0.93723926
[48,] 3.421558e-01 6.843115e-01 0.65784425
[49,] 8.799235e-01 2.401531e-01 0.12007653
[50,] 9.423715e-01 1.152569e-01 0.05762846
[51,] 8.880376e-01 2.239248e-01 0.11196241
[52,] 8.007276e-01 3.985449e-01 0.19927244
> postscript(file="/var/www/html/rcomp/tmp/1y3xk1258894959.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2p8ka1258894959.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ireq1258894959.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4xfef1258894959.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/574m51258894959.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
0.695121951 0.795121951 0.395121951 0.195121951 0.295121951 0.495121951
7 8 9 10 11 12
0.495121951 0.495121951 0.195121951 0.195121951 -0.204878049 0.195121951
13 14 15 16 17 18
0.195121951 0.295121951 0.395121951 0.395121951 0.595121951 0.795121951
19 20 21 22 23 24
0.895121951 0.895121951 0.895121951 0.595121951 -0.004878049 -0.404878049
25 26 27 28 29 30
-0.704878049 -0.604878049 -0.404878049 -0.304878049 -0.204878049 -0.104878049
31 32 33 34 35 36
-0.204878049 -0.404878049 -0.304878049 -0.504878049 -0.904878049 -0.604878049
37 38 39 40 41 42
-0.704878049 -0.904878049 -1.004878049 -1.104878049 -0.804878049 -0.145000000
43 44 45 46 47 48
-0.145000000 -0.545000000 -0.845000000 -1.145000000 -0.845000000 0.255000000
49 50 51 52 53 54
0.355000000 -0.045000000 -0.845000000 -1.145000000 -0.745000000 0.155000000
55 56 57 58 59 60
0.755000000 0.955000000 0.755000000 0.455000000 0.555000000 1.055000000
61
1.155000000
> postscript(file="/var/www/html/rcomp/tmp/6f2fw1258894959.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 0.695121951 NA
1 0.795121951 0.695121951
2 0.395121951 0.795121951
3 0.195121951 0.395121951
4 0.295121951 0.195121951
5 0.495121951 0.295121951
6 0.495121951 0.495121951
7 0.495121951 0.495121951
8 0.195121951 0.495121951
9 0.195121951 0.195121951
10 -0.204878049 0.195121951
11 0.195121951 -0.204878049
12 0.195121951 0.195121951
13 0.295121951 0.195121951
14 0.395121951 0.295121951
15 0.395121951 0.395121951
16 0.595121951 0.395121951
17 0.795121951 0.595121951
18 0.895121951 0.795121951
19 0.895121951 0.895121951
20 0.895121951 0.895121951
21 0.595121951 0.895121951
22 -0.004878049 0.595121951
23 -0.404878049 -0.004878049
24 -0.704878049 -0.404878049
25 -0.604878049 -0.704878049
26 -0.404878049 -0.604878049
27 -0.304878049 -0.404878049
28 -0.204878049 -0.304878049
29 -0.104878049 -0.204878049
30 -0.204878049 -0.104878049
31 -0.404878049 -0.204878049
32 -0.304878049 -0.404878049
33 -0.504878049 -0.304878049
34 -0.904878049 -0.504878049
35 -0.604878049 -0.904878049
36 -0.704878049 -0.604878049
37 -0.904878049 -0.704878049
38 -1.004878049 -0.904878049
39 -1.104878049 -1.004878049
40 -0.804878049 -1.104878049
41 -0.145000000 -0.804878049
42 -0.145000000 -0.145000000
43 -0.545000000 -0.145000000
44 -0.845000000 -0.545000000
45 -1.145000000 -0.845000000
46 -0.845000000 -1.145000000
47 0.255000000 -0.845000000
48 0.355000000 0.255000000
49 -0.045000000 0.355000000
50 -0.845000000 -0.045000000
51 -1.145000000 -0.845000000
52 -0.745000000 -1.145000000
53 0.155000000 -0.745000000
54 0.755000000 0.155000000
55 0.955000000 0.755000000
56 0.755000000 0.955000000
57 0.455000000 0.755000000
58 0.555000000 0.455000000
59 1.055000000 0.555000000
60 1.155000000 1.055000000
61 NA 1.155000000
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.795121951 0.695121951
[2,] 0.395121951 0.795121951
[3,] 0.195121951 0.395121951
[4,] 0.295121951 0.195121951
[5,] 0.495121951 0.295121951
[6,] 0.495121951 0.495121951
[7,] 0.495121951 0.495121951
[8,] 0.195121951 0.495121951
[9,] 0.195121951 0.195121951
[10,] -0.204878049 0.195121951
[11,] 0.195121951 -0.204878049
[12,] 0.195121951 0.195121951
[13,] 0.295121951 0.195121951
[14,] 0.395121951 0.295121951
[15,] 0.395121951 0.395121951
[16,] 0.595121951 0.395121951
[17,] 0.795121951 0.595121951
[18,] 0.895121951 0.795121951
[19,] 0.895121951 0.895121951
[20,] 0.895121951 0.895121951
[21,] 0.595121951 0.895121951
[22,] -0.004878049 0.595121951
[23,] -0.404878049 -0.004878049
[24,] -0.704878049 -0.404878049
[25,] -0.604878049 -0.704878049
[26,] -0.404878049 -0.604878049
[27,] -0.304878049 -0.404878049
[28,] -0.204878049 -0.304878049
[29,] -0.104878049 -0.204878049
[30,] -0.204878049 -0.104878049
[31,] -0.404878049 -0.204878049
[32,] -0.304878049 -0.404878049
[33,] -0.504878049 -0.304878049
[34,] -0.904878049 -0.504878049
[35,] -0.604878049 -0.904878049
[36,] -0.704878049 -0.604878049
[37,] -0.904878049 -0.704878049
[38,] -1.004878049 -0.904878049
[39,] -1.104878049 -1.004878049
[40,] -0.804878049 -1.104878049
[41,] -0.145000000 -0.804878049
[42,] -0.145000000 -0.145000000
[43,] -0.545000000 -0.145000000
[44,] -0.845000000 -0.545000000
[45,] -1.145000000 -0.845000000
[46,] -0.845000000 -1.145000000
[47,] 0.255000000 -0.845000000
[48,] 0.355000000 0.255000000
[49,] -0.045000000 0.355000000
[50,] -0.845000000 -0.045000000
[51,] -1.145000000 -0.845000000
[52,] -0.745000000 -1.145000000
[53,] 0.155000000 -0.745000000
[54,] 0.755000000 0.155000000
[55,] 0.955000000 0.755000000
[56,] 0.755000000 0.955000000
[57,] 0.455000000 0.755000000
[58,] 0.555000000 0.455000000
[59,] 1.055000000 0.555000000
[60,] 1.155000000 1.055000000
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.795121951 0.695121951
2 0.395121951 0.795121951
3 0.195121951 0.395121951
4 0.295121951 0.195121951
5 0.495121951 0.295121951
6 0.495121951 0.495121951
7 0.495121951 0.495121951
8 0.195121951 0.495121951
9 0.195121951 0.195121951
10 -0.204878049 0.195121951
11 0.195121951 -0.204878049
12 0.195121951 0.195121951
13 0.295121951 0.195121951
14 0.395121951 0.295121951
15 0.395121951 0.395121951
16 0.595121951 0.395121951
17 0.795121951 0.595121951
18 0.895121951 0.795121951
19 0.895121951 0.895121951
20 0.895121951 0.895121951
21 0.595121951 0.895121951
22 -0.004878049 0.595121951
23 -0.404878049 -0.004878049
24 -0.704878049 -0.404878049
25 -0.604878049 -0.704878049
26 -0.404878049 -0.604878049
27 -0.304878049 -0.404878049
28 -0.204878049 -0.304878049
29 -0.104878049 -0.204878049
30 -0.204878049 -0.104878049
31 -0.404878049 -0.204878049
32 -0.304878049 -0.404878049
33 -0.504878049 -0.304878049
34 -0.904878049 -0.504878049
35 -0.604878049 -0.904878049
36 -0.704878049 -0.604878049
37 -0.904878049 -0.704878049
38 -1.004878049 -0.904878049
39 -1.104878049 -1.004878049
40 -0.804878049 -1.104878049
41 -0.145000000 -0.804878049
42 -0.145000000 -0.145000000
43 -0.545000000 -0.145000000
44 -0.845000000 -0.545000000
45 -1.145000000 -0.845000000
46 -0.845000000 -1.145000000
47 0.255000000 -0.845000000
48 0.355000000 0.255000000
49 -0.045000000 0.355000000
50 -0.845000000 -0.045000000
51 -1.145000000 -0.845000000
52 -0.745000000 -1.145000000
53 0.155000000 -0.745000000
54 0.755000000 0.155000000
55 0.955000000 0.755000000
56 0.755000000 0.955000000
57 0.455000000 0.755000000
58 0.555000000 0.455000000
59 1.055000000 0.555000000
60 1.155000000 1.055000000
> 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/7098r1258894959.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8ggm51258894959.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9qjvw1258894959.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10b0r71258894959.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11a43j1258894959.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/12wmyr1258894959.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/13e1rt1258894959.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/14bt0y1258894959.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/1591ws1258894959.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/16xd6q1258894959.tab")
+ }
>
> system("convert tmp/1y3xk1258894959.ps tmp/1y3xk1258894959.png")
> system("convert tmp/2p8ka1258894959.ps tmp/2p8ka1258894959.png")
> system("convert tmp/3ireq1258894959.ps tmp/3ireq1258894959.png")
> system("convert tmp/4xfef1258894959.ps tmp/4xfef1258894959.png")
> system("convert tmp/574m51258894959.ps tmp/574m51258894959.png")
> system("convert tmp/6f2fw1258894959.ps tmp/6f2fw1258894959.png")
> system("convert tmp/7098r1258894959.ps tmp/7098r1258894959.png")
> system("convert tmp/8ggm51258894959.ps tmp/8ggm51258894959.png")
> system("convert tmp/9qjvw1258894959.ps tmp/9qjvw1258894959.png")
> system("convert tmp/10b0r71258894959.ps tmp/10b0r71258894959.png")
>
>
> proc.time()
user system elapsed
2.449 1.541 3.149