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(17823.2,0,17872,0,17420.4,0,16704.4,0,15991.2,0,15583.6,0,19123.5,0,17838.7,0,17209.4,0,18586.5,0,16258.1,0,15141.6,0,19202.1,0,17746.5,0,19090.1,1,18040.3,1,17515.5,1,17751.8,1,21072.4,1,17170,1,19439.5,1,19795.4,1,17574.9,1,16165.4,1,19464.6,1,19932.1,1,19961.2,1,17343.4,1,18924.2,1,18574.1,1,21350.6,1,18594.6,1,19832.1,1,20844.4,1,19640.2,1,17735.4,1,19813.6,1,22160,1,20664.3,1,17877.4,1,20906.5,1,21164.1,1,21374.4,1,22952.3,1,21343.5,1,23899.3,1,22392.9,1,18274.1,1,22786.7,1,22321.5,1,17842.2,1,16373.5,1,15933.8,0,16446.1,0,17729,0,16643,0,16196.7,0,18252.1,0,17570.4,0,15836.8,0),dim=c(2,60),dimnames=list(c('Y','X'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Y','X'),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
Y X
1 17823.2 0
2 17872.0 0
3 17420.4 0
4 16704.4 0
5 15991.2 0
6 15583.6 0
7 19123.5 0
8 17838.7 0
9 17209.4 0
10 18586.5 0
11 16258.1 0
12 15141.6 0
13 19202.1 0
14 17746.5 0
15 19090.1 1
16 18040.3 1
17 17515.5 1
18 17751.8 1
19 21072.4 1
20 17170.0 1
21 19439.5 1
22 19795.4 1
23 17574.9 1
24 16165.4 1
25 19464.6 1
26 19932.1 1
27 19961.2 1
28 17343.4 1
29 18924.2 1
30 18574.1 1
31 21350.6 1
32 18594.6 1
33 19832.1 1
34 20844.4 1
35 19640.2 1
36 17735.4 1
37 19813.6 1
38 22160.0 1
39 20664.3 1
40 17877.4 1
41 20906.5 1
42 21164.1 1
43 21374.4 1
44 22952.3 1
45 21343.5 1
46 23899.3 1
47 22392.9 1
48 18274.1 1
49 22786.7 1
50 22321.5 1
51 17842.2 1
52 16373.5 1
53 15933.8 0
54 16446.1 0
55 17729.0 0
56 16643.0 0
57 16196.7 0
58 18252.1 0
59 17570.4 0
60 15836.8 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
17141 2542
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-3517.72 -1231.77 90.18 1176.81 4216.18
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 17141.3 364.0 47.088 < 2e-16 ***
X 2541.8 457.4 5.557 7.24e-07 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1707 on 58 degrees of freedom
Multiple R-squared: 0.3474, Adjusted R-squared: 0.3362
F-statistic: 30.88 on 1 and 58 DF, p-value: 7.238e-07
> 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,] 0.15656741 0.31313481 0.84343259
[2,] 0.17101242 0.34202484 0.82898758
[3,] 0.27542546 0.55085092 0.72457454
[4,] 0.18202787 0.36405573 0.81797213
[5,] 0.10593615 0.21187230 0.89406385
[6,] 0.09185928 0.18371857 0.90814072
[7,] 0.07131831 0.14263662 0.92868169
[8,] 0.11271624 0.22543248 0.88728376
[9,] 0.14947666 0.29895333 0.85052334
[10,] 0.10248078 0.20496157 0.89751922
[11,] 0.06520547 0.13041094 0.93479453
[12,] 0.04767529 0.09535058 0.95232471
[13,] 0.03862796 0.07725592 0.96137204
[14,] 0.02742389 0.05484779 0.97257611
[15,] 0.06219848 0.12439695 0.93780152
[16,] 0.06821322 0.13642643 0.93178678
[17,] 0.05071372 0.10142744 0.94928628
[18,] 0.03930611 0.07861222 0.96069389
[19,] 0.03778312 0.07556623 0.96221688
[20,] 0.09519014 0.19038027 0.90480986
[21,] 0.07617400 0.15234800 0.92382600
[22,] 0.06529916 0.13059832 0.93470084
[23,] 0.05390047 0.10780094 0.94609953
[24,] 0.06726237 0.13452473 0.93273763
[25,] 0.05143989 0.10287977 0.94856011
[26,] 0.04179605 0.08359211 0.95820395
[27,] 0.06241504 0.12483007 0.93758496
[28,] 0.05236424 0.10472848 0.94763576
[29,] 0.04023067 0.08046134 0.95976933
[30,] 0.03938942 0.07877884 0.96061058
[31,] 0.02852717 0.05705434 0.97147283
[32,] 0.03986297 0.07972594 0.96013703
[33,] 0.03013811 0.06027621 0.96986189
[34,] 0.05343939 0.10687878 0.94656061
[35,] 0.04257553 0.08515105 0.95742447
[36,] 0.06269820 0.12539640 0.93730180
[37,] 0.05190373 0.10380746 0.94809627
[38,] 0.04413669 0.08827337 0.95586331
[39,] 0.03842539 0.07685078 0.96157461
[40,] 0.07453422 0.14906844 0.92546578
[41,] 0.06064719 0.12129438 0.93935281
[42,] 0.21727974 0.43455948 0.78272026
[43,] 0.30155548 0.60311095 0.69844452
[44,] 0.26755636 0.53511272 0.73244364
[45,] 0.51099558 0.97800884 0.48900442
[46,] 0.96986588 0.06026824 0.03013412
[47,] 0.96384341 0.07231317 0.03615659
[48,] 0.93614052 0.12771897 0.06385948
[49,] 0.90981168 0.18037664 0.09018832
[50,] 0.83660674 0.32678652 0.16339326
[51,] 0.73545331 0.52909339 0.26454669
> postscript(file="/var/www/html/rcomp/tmp/10pzf1258560166.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2c0k31258560166.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3l2at1258560166.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4aepv1258560166.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5e3u31258560166.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
681.87727 730.67727 279.07727 -436.92273 -1150.12273 -1557.72273
7 8 9 10 11 12
1982.17727 697.37727 68.07727 1445.17727 -883.22273 -1999.72273
13 14 15 16 17 18
2060.77727 605.17727 -593.01842 -1642.81842 -2167.61842 -1931.31842
19 20 21 22 23 24
1389.28158 -2513.11842 -243.61842 112.28158 -2108.21842 -3517.71842
25 26 27 28 29 30
-218.51842 248.98158 278.08158 -2339.71842 -758.91842 -1109.01842
31 32 33 34 35 36
1667.48158 -1088.51842 148.98158 1161.28158 -42.91842 -1947.71842
37 38 39 40 41 42
130.48158 2476.88158 981.18158 -1805.71842 1223.38158 1480.98158
43 44 45 46 47 48
1691.28158 3269.18158 1660.38158 4216.18158 2709.78158 -1409.01842
49 50 51 52 53 54
3103.58158 2638.38158 -1840.91842 -3309.61842 -1207.52273 -695.22273
55 56 57 58 59 60
587.67727 -498.32273 -944.62273 1110.77727 429.07727 -1304.52273
> postscript(file="/var/www/html/rcomp/tmp/6mhuf1258560166.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
0 681.87727 NA
1 730.67727 681.87727
2 279.07727 730.67727
3 -436.92273 279.07727
4 -1150.12273 -436.92273
5 -1557.72273 -1150.12273
6 1982.17727 -1557.72273
7 697.37727 1982.17727
8 68.07727 697.37727
9 1445.17727 68.07727
10 -883.22273 1445.17727
11 -1999.72273 -883.22273
12 2060.77727 -1999.72273
13 605.17727 2060.77727
14 -593.01842 605.17727
15 -1642.81842 -593.01842
16 -2167.61842 -1642.81842
17 -1931.31842 -2167.61842
18 1389.28158 -1931.31842
19 -2513.11842 1389.28158
20 -243.61842 -2513.11842
21 112.28158 -243.61842
22 -2108.21842 112.28158
23 -3517.71842 -2108.21842
24 -218.51842 -3517.71842
25 248.98158 -218.51842
26 278.08158 248.98158
27 -2339.71842 278.08158
28 -758.91842 -2339.71842
29 -1109.01842 -758.91842
30 1667.48158 -1109.01842
31 -1088.51842 1667.48158
32 148.98158 -1088.51842
33 1161.28158 148.98158
34 -42.91842 1161.28158
35 -1947.71842 -42.91842
36 130.48158 -1947.71842
37 2476.88158 130.48158
38 981.18158 2476.88158
39 -1805.71842 981.18158
40 1223.38158 -1805.71842
41 1480.98158 1223.38158
42 1691.28158 1480.98158
43 3269.18158 1691.28158
44 1660.38158 3269.18158
45 4216.18158 1660.38158
46 2709.78158 4216.18158
47 -1409.01842 2709.78158
48 3103.58158 -1409.01842
49 2638.38158 3103.58158
50 -1840.91842 2638.38158
51 -3309.61842 -1840.91842
52 -1207.52273 -3309.61842
53 -695.22273 -1207.52273
54 587.67727 -695.22273
55 -498.32273 587.67727
56 -944.62273 -498.32273
57 1110.77727 -944.62273
58 429.07727 1110.77727
59 -1304.52273 429.07727
60 NA -1304.52273
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 730.67727 681.87727
[2,] 279.07727 730.67727
[3,] -436.92273 279.07727
[4,] -1150.12273 -436.92273
[5,] -1557.72273 -1150.12273
[6,] 1982.17727 -1557.72273
[7,] 697.37727 1982.17727
[8,] 68.07727 697.37727
[9,] 1445.17727 68.07727
[10,] -883.22273 1445.17727
[11,] -1999.72273 -883.22273
[12,] 2060.77727 -1999.72273
[13,] 605.17727 2060.77727
[14,] -593.01842 605.17727
[15,] -1642.81842 -593.01842
[16,] -2167.61842 -1642.81842
[17,] -1931.31842 -2167.61842
[18,] 1389.28158 -1931.31842
[19,] -2513.11842 1389.28158
[20,] -243.61842 -2513.11842
[21,] 112.28158 -243.61842
[22,] -2108.21842 112.28158
[23,] -3517.71842 -2108.21842
[24,] -218.51842 -3517.71842
[25,] 248.98158 -218.51842
[26,] 278.08158 248.98158
[27,] -2339.71842 278.08158
[28,] -758.91842 -2339.71842
[29,] -1109.01842 -758.91842
[30,] 1667.48158 -1109.01842
[31,] -1088.51842 1667.48158
[32,] 148.98158 -1088.51842
[33,] 1161.28158 148.98158
[34,] -42.91842 1161.28158
[35,] -1947.71842 -42.91842
[36,] 130.48158 -1947.71842
[37,] 2476.88158 130.48158
[38,] 981.18158 2476.88158
[39,] -1805.71842 981.18158
[40,] 1223.38158 -1805.71842
[41,] 1480.98158 1223.38158
[42,] 1691.28158 1480.98158
[43,] 3269.18158 1691.28158
[44,] 1660.38158 3269.18158
[45,] 4216.18158 1660.38158
[46,] 2709.78158 4216.18158
[47,] -1409.01842 2709.78158
[48,] 3103.58158 -1409.01842
[49,] 2638.38158 3103.58158
[50,] -1840.91842 2638.38158
[51,] -3309.61842 -1840.91842
[52,] -1207.52273 -3309.61842
[53,] -695.22273 -1207.52273
[54,] 587.67727 -695.22273
[55,] -498.32273 587.67727
[56,] -944.62273 -498.32273
[57,] 1110.77727 -944.62273
[58,] 429.07727 1110.77727
[59,] -1304.52273 429.07727
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 730.67727 681.87727
2 279.07727 730.67727
3 -436.92273 279.07727
4 -1150.12273 -436.92273
5 -1557.72273 -1150.12273
6 1982.17727 -1557.72273
7 697.37727 1982.17727
8 68.07727 697.37727
9 1445.17727 68.07727
10 -883.22273 1445.17727
11 -1999.72273 -883.22273
12 2060.77727 -1999.72273
13 605.17727 2060.77727
14 -593.01842 605.17727
15 -1642.81842 -593.01842
16 -2167.61842 -1642.81842
17 -1931.31842 -2167.61842
18 1389.28158 -1931.31842
19 -2513.11842 1389.28158
20 -243.61842 -2513.11842
21 112.28158 -243.61842
22 -2108.21842 112.28158
23 -3517.71842 -2108.21842
24 -218.51842 -3517.71842
25 248.98158 -218.51842
26 278.08158 248.98158
27 -2339.71842 278.08158
28 -758.91842 -2339.71842
29 -1109.01842 -758.91842
30 1667.48158 -1109.01842
31 -1088.51842 1667.48158
32 148.98158 -1088.51842
33 1161.28158 148.98158
34 -42.91842 1161.28158
35 -1947.71842 -42.91842
36 130.48158 -1947.71842
37 2476.88158 130.48158
38 981.18158 2476.88158
39 -1805.71842 981.18158
40 1223.38158 -1805.71842
41 1480.98158 1223.38158
42 1691.28158 1480.98158
43 3269.18158 1691.28158
44 1660.38158 3269.18158
45 4216.18158 1660.38158
46 2709.78158 4216.18158
47 -1409.01842 2709.78158
48 3103.58158 -1409.01842
49 2638.38158 3103.58158
50 -1840.91842 2638.38158
51 -3309.61842 -1840.91842
52 -1207.52273 -3309.61842
53 -695.22273 -1207.52273
54 587.67727 -695.22273
55 -498.32273 587.67727
56 -944.62273 -498.32273
57 1110.77727 -944.62273
58 429.07727 1110.77727
59 -1304.52273 429.07727
> 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/7pfrf1258560166.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8saxc1258560166.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9cm0y1258560166.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10q14e1258560166.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11bu9y1258560166.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/12k2t81258560166.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/1360sd1258560166.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/14t50m1258560166.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/15qnr11258560166.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/16jpbv1258560166.tab")
+ }
> system("convert tmp/10pzf1258560166.ps tmp/10pzf1258560166.png")
> system("convert tmp/2c0k31258560166.ps tmp/2c0k31258560166.png")
> system("convert tmp/3l2at1258560166.ps tmp/3l2at1258560166.png")
> system("convert tmp/4aepv1258560166.ps tmp/4aepv1258560166.png")
> system("convert tmp/5e3u31258560166.ps tmp/5e3u31258560166.png")
> system("convert tmp/6mhuf1258560166.ps tmp/6mhuf1258560166.png")
> system("convert tmp/7pfrf1258560166.ps tmp/7pfrf1258560166.png")
> system("convert tmp/8saxc1258560166.ps tmp/8saxc1258560166.png")
> system("convert tmp/9cm0y1258560166.ps tmp/9cm0y1258560166.png")
> system("convert tmp/10q14e1258560166.ps tmp/10q14e1258560166.png")
>
>
> proc.time()
user system elapsed
2.498 1.598 3.436