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(286602,0,283042,0,276687,0,277915,0,277128,0,277103,0,275037,0,270150,0,267140,0,264993,0,287259,0,291186,0,292300,0,288186,0,281477,0,282656,0,280190,0,280408,0,276836,0,275216,0,274352,0,271311,0,289802,0,290726,0,292300,0,278506,0,269826,0,265861,0,269034,0,264176,0,255198,0,253353,0,246057,0,235372,0,258556,0,260993,0,254663,0,250643,0,243422,0,247105,0,248541,0,245039,0,237080,0,237085,0,225554,0,226839,1,247934,1,248333,1,246969,1,245098,1,246263,1,255765,1,264319,1,268347,1,273046,1,273963,1,267430,1,271993,1,292710,1,295881,1),dim=c(2,60),dimnames=list(c('nwwmb','dummy_variable'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('nwwmb','dummy_variable'),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
nwwmb dummy_variable
1 286602 0
2 283042 0
3 276687 0
4 277915 0
5 277128 0
6 277103 0
7 275037 0
8 270150 0
9 267140 0
10 264993 0
11 287259 0
12 291186 0
13 292300 0
14 288186 0
15 281477 0
16 282656 0
17 280190 0
18 280408 0
19 276836 0
20 275216 0
21 274352 0
22 271311 0
23 289802 0
24 290726 0
25 292300 0
26 278506 0
27 269826 0
28 265861 0
29 269034 0
30 264176 0
31 255198 0
32 253353 0
33 246057 0
34 235372 0
35 258556 0
36 260993 0
37 254663 0
38 250643 0
39 243422 0
40 247105 0
41 248541 0
42 245039 0
43 237080 0
44 237085 0
45 225554 0
46 226839 1
47 247934 1
48 248333 1
49 246969 1
50 245098 1
51 246263 1
52 255765 1
53 264319 1
54 268347 1
55 273046 1
56 273963 1
57 267430 1
58 271993 1
59 292710 1
60 295881 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) dummy_variable
267913 -6253
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-42359 -13934 3029 12284 34222
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 267913 2672 100.28 <2e-16 ***
dummy_variable -6253 5343 -1.17 0.247
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 17920 on 58 degrees of freedom
Multiple R-squared: 0.02307, Adjusted R-squared: 0.006225
F-statistic: 1.37 on 1 and 58 DF, p-value: 0.2467
> 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,] 2.728951e-02 5.457903e-02 0.9727105
[2,] 7.408117e-03 1.481623e-02 0.9925919
[3,] 2.537023e-03 5.074046e-03 0.9974630
[4,] 2.314437e-03 4.628873e-03 0.9976856
[5,] 2.657268e-03 5.314537e-03 0.9973427
[6,] 2.959502e-03 5.919004e-03 0.9970405
[7,] 3.130453e-03 6.260906e-03 0.9968695
[8,] 5.009179e-03 1.001836e-02 0.9949908
[9,] 7.176212e-03 1.435242e-02 0.9928238
[10,] 5.664211e-03 1.132842e-02 0.9943358
[11,] 2.930321e-03 5.860643e-03 0.9970697
[12,] 1.575665e-03 3.151329e-03 0.9984243
[13,] 7.830873e-04 1.566175e-03 0.9992169
[14,] 3.914015e-04 7.828029e-04 0.9996086
[15,] 1.953145e-04 3.906290e-04 0.9998047
[16,] 1.023789e-04 2.047577e-04 0.9998976
[17,] 5.568540e-05 1.113708e-04 0.9999443
[18,] 3.733137e-05 7.466274e-05 0.9999627
[19,] 6.696547e-05 1.339309e-04 0.9999330
[20,] 1.581683e-04 3.163366e-04 0.9998418
[21,] 6.018688e-04 1.203738e-03 0.9993981
[22,] 5.953514e-04 1.190703e-03 0.9994046
[23,] 7.425658e-04 1.485132e-03 0.9992574
[24,] 1.215656e-03 2.431313e-03 0.9987843
[25,] 1.604137e-03 3.208274e-03 0.9983959
[26,] 2.751997e-03 5.503995e-03 0.9972480
[27,] 8.522470e-03 1.704494e-02 0.9914775
[28,] 2.011969e-02 4.023938e-02 0.9798803
[29,] 5.618469e-02 1.123694e-01 0.9438153
[30,] 1.901133e-01 3.802267e-01 0.8098867
[31,] 1.889390e-01 3.778780e-01 0.8110610
[32,] 1.918364e-01 3.836728e-01 0.8081636
[33,] 1.982246e-01 3.964492e-01 0.8017754
[34,] 2.092776e-01 4.185551e-01 0.7907224
[35,] 2.376764e-01 4.753529e-01 0.7623236
[36,] 2.424010e-01 4.848020e-01 0.7575990
[37,] 2.427432e-01 4.854863e-01 0.7572568
[38,] 2.476897e-01 4.953793e-01 0.7523103
[39,] 2.654179e-01 5.308358e-01 0.7345821
[40,] 2.761077e-01 5.522155e-01 0.7238923
[41,] 3.145047e-01 6.290094e-01 0.6854953
[42,] 4.837178e-01 9.674355e-01 0.5162822
[43,] 4.692650e-01 9.385300e-01 0.5307350
[44,] 4.546767e-01 9.093533e-01 0.5453233
[45,] 4.709182e-01 9.418365e-01 0.5290818
[46,] 5.547706e-01 8.904588e-01 0.4452294
[47,] 6.994233e-01 6.011534e-01 0.3005767
[48,] 7.504145e-01 4.991711e-01 0.2495855
[49,] 7.180675e-01 5.638650e-01 0.2819325
[50,] 6.450791e-01 7.098417e-01 0.3549209
[51,] 5.136394e-01 9.727213e-01 0.4863606
> postscript(file="/var/www/html/rcomp/tmp/12ark1258740167.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2uliy1258740167.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/326351258740167.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4fzbm1258740167.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5v38q1258740167.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
18689.4222 15129.4222 8774.4222 10002.4222 9215.4222 9190.4222
7 8 9 10 11 12
7124.4222 2237.4222 -772.5778 -2919.5778 19346.4222 23273.4222
13 14 15 16 17 18
24387.4222 20273.4222 13564.4222 14743.4222 12277.4222 12495.4222
19 20 21 22 23 24
8923.4222 7303.4222 6439.4222 3398.4222 21889.4222 22813.4222
25 26 27 28 29 30
24387.4222 10593.4222 1913.4222 -2051.5778 1121.4222 -3736.5778
31 32 33 34 35 36
-12714.5778 -14559.5778 -21855.5778 -32540.5778 -9356.5778 -6919.5778
37 38 39 40 41 42
-13249.5778 -17269.5778 -24490.5778 -20807.5778 -19371.5778 -22873.5778
43 44 45 46 47 48
-30832.5778 -30827.5778 -42358.5778 -34820.3333 -13725.3333 -13326.3333
49 50 51 52 53 54
-14690.3333 -16561.3333 -15396.3333 -5894.3333 2659.6667 6687.6667
55 56 57 58 59 60
11386.6667 12303.6667 5770.6667 10333.6667 31050.6667 34221.6667
> postscript(file="/var/www/html/rcomp/tmp/69unh1258740167.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 18689.4222 NA
1 15129.4222 18689.4222
2 8774.4222 15129.4222
3 10002.4222 8774.4222
4 9215.4222 10002.4222
5 9190.4222 9215.4222
6 7124.4222 9190.4222
7 2237.4222 7124.4222
8 -772.5778 2237.4222
9 -2919.5778 -772.5778
10 19346.4222 -2919.5778
11 23273.4222 19346.4222
12 24387.4222 23273.4222
13 20273.4222 24387.4222
14 13564.4222 20273.4222
15 14743.4222 13564.4222
16 12277.4222 14743.4222
17 12495.4222 12277.4222
18 8923.4222 12495.4222
19 7303.4222 8923.4222
20 6439.4222 7303.4222
21 3398.4222 6439.4222
22 21889.4222 3398.4222
23 22813.4222 21889.4222
24 24387.4222 22813.4222
25 10593.4222 24387.4222
26 1913.4222 10593.4222
27 -2051.5778 1913.4222
28 1121.4222 -2051.5778
29 -3736.5778 1121.4222
30 -12714.5778 -3736.5778
31 -14559.5778 -12714.5778
32 -21855.5778 -14559.5778
33 -32540.5778 -21855.5778
34 -9356.5778 -32540.5778
35 -6919.5778 -9356.5778
36 -13249.5778 -6919.5778
37 -17269.5778 -13249.5778
38 -24490.5778 -17269.5778
39 -20807.5778 -24490.5778
40 -19371.5778 -20807.5778
41 -22873.5778 -19371.5778
42 -30832.5778 -22873.5778
43 -30827.5778 -30832.5778
44 -42358.5778 -30827.5778
45 -34820.3333 -42358.5778
46 -13725.3333 -34820.3333
47 -13326.3333 -13725.3333
48 -14690.3333 -13326.3333
49 -16561.3333 -14690.3333
50 -15396.3333 -16561.3333
51 -5894.3333 -15396.3333
52 2659.6667 -5894.3333
53 6687.6667 2659.6667
54 11386.6667 6687.6667
55 12303.6667 11386.6667
56 5770.6667 12303.6667
57 10333.6667 5770.6667
58 31050.6667 10333.6667
59 34221.6667 31050.6667
60 NA 34221.6667
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 15129.4222 18689.4222
[2,] 8774.4222 15129.4222
[3,] 10002.4222 8774.4222
[4,] 9215.4222 10002.4222
[5,] 9190.4222 9215.4222
[6,] 7124.4222 9190.4222
[7,] 2237.4222 7124.4222
[8,] -772.5778 2237.4222
[9,] -2919.5778 -772.5778
[10,] 19346.4222 -2919.5778
[11,] 23273.4222 19346.4222
[12,] 24387.4222 23273.4222
[13,] 20273.4222 24387.4222
[14,] 13564.4222 20273.4222
[15,] 14743.4222 13564.4222
[16,] 12277.4222 14743.4222
[17,] 12495.4222 12277.4222
[18,] 8923.4222 12495.4222
[19,] 7303.4222 8923.4222
[20,] 6439.4222 7303.4222
[21,] 3398.4222 6439.4222
[22,] 21889.4222 3398.4222
[23,] 22813.4222 21889.4222
[24,] 24387.4222 22813.4222
[25,] 10593.4222 24387.4222
[26,] 1913.4222 10593.4222
[27,] -2051.5778 1913.4222
[28,] 1121.4222 -2051.5778
[29,] -3736.5778 1121.4222
[30,] -12714.5778 -3736.5778
[31,] -14559.5778 -12714.5778
[32,] -21855.5778 -14559.5778
[33,] -32540.5778 -21855.5778
[34,] -9356.5778 -32540.5778
[35,] -6919.5778 -9356.5778
[36,] -13249.5778 -6919.5778
[37,] -17269.5778 -13249.5778
[38,] -24490.5778 -17269.5778
[39,] -20807.5778 -24490.5778
[40,] -19371.5778 -20807.5778
[41,] -22873.5778 -19371.5778
[42,] -30832.5778 -22873.5778
[43,] -30827.5778 -30832.5778
[44,] -42358.5778 -30827.5778
[45,] -34820.3333 -42358.5778
[46,] -13725.3333 -34820.3333
[47,] -13326.3333 -13725.3333
[48,] -14690.3333 -13326.3333
[49,] -16561.3333 -14690.3333
[50,] -15396.3333 -16561.3333
[51,] -5894.3333 -15396.3333
[52,] 2659.6667 -5894.3333
[53,] 6687.6667 2659.6667
[54,] 11386.6667 6687.6667
[55,] 12303.6667 11386.6667
[56,] 5770.6667 12303.6667
[57,] 10333.6667 5770.6667
[58,] 31050.6667 10333.6667
[59,] 34221.6667 31050.6667
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 15129.4222 18689.4222
2 8774.4222 15129.4222
3 10002.4222 8774.4222
4 9215.4222 10002.4222
5 9190.4222 9215.4222
6 7124.4222 9190.4222
7 2237.4222 7124.4222
8 -772.5778 2237.4222
9 -2919.5778 -772.5778
10 19346.4222 -2919.5778
11 23273.4222 19346.4222
12 24387.4222 23273.4222
13 20273.4222 24387.4222
14 13564.4222 20273.4222
15 14743.4222 13564.4222
16 12277.4222 14743.4222
17 12495.4222 12277.4222
18 8923.4222 12495.4222
19 7303.4222 8923.4222
20 6439.4222 7303.4222
21 3398.4222 6439.4222
22 21889.4222 3398.4222
23 22813.4222 21889.4222
24 24387.4222 22813.4222
25 10593.4222 24387.4222
26 1913.4222 10593.4222
27 -2051.5778 1913.4222
28 1121.4222 -2051.5778
29 -3736.5778 1121.4222
30 -12714.5778 -3736.5778
31 -14559.5778 -12714.5778
32 -21855.5778 -14559.5778
33 -32540.5778 -21855.5778
34 -9356.5778 -32540.5778
35 -6919.5778 -9356.5778
36 -13249.5778 -6919.5778
37 -17269.5778 -13249.5778
38 -24490.5778 -17269.5778
39 -20807.5778 -24490.5778
40 -19371.5778 -20807.5778
41 -22873.5778 -19371.5778
42 -30832.5778 -22873.5778
43 -30827.5778 -30832.5778
44 -42358.5778 -30827.5778
45 -34820.3333 -42358.5778
46 -13725.3333 -34820.3333
47 -13326.3333 -13725.3333
48 -14690.3333 -13326.3333
49 -16561.3333 -14690.3333
50 -15396.3333 -16561.3333
51 -5894.3333 -15396.3333
52 2659.6667 -5894.3333
53 6687.6667 2659.6667
54 11386.6667 6687.6667
55 12303.6667 11386.6667
56 5770.6667 12303.6667
57 10333.6667 5770.6667
58 31050.6667 10333.6667
59 34221.6667 31050.6667
> 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/7l5id1258740167.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8pswr1258740167.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/993x21258740167.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10j5ol1258740167.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11r9ki1258740167.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/12bzhj1258740167.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/13gbma1258740167.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/142pmq1258740167.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/154efv1258740167.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/16i6ah1258740167.tab")
+ }
>
> system("convert tmp/12ark1258740167.ps tmp/12ark1258740167.png")
> system("convert tmp/2uliy1258740167.ps tmp/2uliy1258740167.png")
> system("convert tmp/326351258740167.ps tmp/326351258740167.png")
> system("convert tmp/4fzbm1258740167.ps tmp/4fzbm1258740167.png")
> system("convert tmp/5v38q1258740167.ps tmp/5v38q1258740167.png")
> system("convert tmp/69unh1258740167.ps tmp/69unh1258740167.png")
> system("convert tmp/7l5id1258740167.ps tmp/7l5id1258740167.png")
> system("convert tmp/8pswr1258740167.ps tmp/8pswr1258740167.png")
> system("convert tmp/993x21258740167.ps tmp/993x21258740167.png")
> system("convert tmp/10j5ol1258740167.ps tmp/10j5ol1258740167.png")
>
>
> proc.time()
user system elapsed
2.440 1.551 2.849