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(10.9,96.8,10,114.1,9.2,110.3,9.2,103.9,9.5,101.6,9.6,94.6,9.5,95.9,9.1,104.7,8.9,102.8,9,98.1,10.1,113.9,10.3,80.9,10.2,95.7,9.6,113.2,9.2,105.9,9.3,108.8,9.4,102.3,9.4,99,9.2,100.7,9,115.5,9,100.7,9,109.9,9.8,114.6,10,85.4,9.8,100.5,9.3,114.8,9,116.5,9,112.9,9.1,102,9.1,106,9.1,105.3,9.2,118.8,8.8,106.1,8.3,109.3,8.4,117.2,8.1,92.5,7.7,104.2,7.9,112.5,7.9,122.4,8,113.3,7.9,100,7.6,110.7,7.1,112.8,6.8,109.8,6.5,117.3,6.9,109.1,8.2,115.9,8.7,96,8.3,99.8,7.9,116.8,7.5,115.7,7.8,99.4,8.3,94.3,8.4,91,8.2,93.2,7.7,103.1,7.2,94.1,7.3,91.8,8.1,102.7,8.5,82.6),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 10.9 96.8
2 10.0 114.1
3 9.2 110.3
4 9.2 103.9
5 9.5 101.6
6 9.6 94.6
7 9.5 95.9
8 9.1 104.7
9 8.9 102.8
10 9.0 98.1
11 10.1 113.9
12 10.3 80.9
13 10.2 95.7
14 9.6 113.2
15 9.2 105.9
16 9.3 108.8
17 9.4 102.3
18 9.4 99.0
19 9.2 100.7
20 9.0 115.5
21 9.0 100.7
22 9.0 109.9
23 9.8 114.6
24 10.0 85.4
25 9.8 100.5
26 9.3 114.8
27 9.0 116.5
28 9.0 112.9
29 9.1 102.0
30 9.1 106.0
31 9.1 105.3
32 9.2 118.8
33 8.8 106.1
34 8.3 109.3
35 8.4 117.2
36 8.1 92.5
37 7.7 104.2
38 7.9 112.5
39 7.9 122.4
40 8.0 113.3
41 7.9 100.0
42 7.6 110.7
43 7.1 112.8
44 6.8 109.8
45 6.5 117.3
46 6.9 109.1
47 8.2 115.9
48 8.7 96.0
49 8.3 99.8
50 7.9 116.8
51 7.5 115.7
52 7.8 99.4
53 8.3 94.3
54 8.4 91.0
55 8.2 93.2
56 7.7 103.1
57 7.2 94.1
58 7.3 91.8
59 8.1 102.7
60 8.5 82.6
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
10.82904 -0.02034
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.9429 -0.6426 0.1930 0.6293 2.0401
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 10.82904 1.35771 7.976 6.72e-11 ***
X -0.02034 0.01292 -1.574 0.121
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.9395 on 58 degrees of freedom
Multiple R-squared: 0.04099, Adjusted R-squared: 0.02445
F-statistic: 2.479 on 1 and 58 DF, p-value: 0.1208
> 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,] 0.431984301 0.86396860 0.568015699
[2,] 0.321057441 0.64211488 0.678942559
[3,] 0.220058191 0.44011638 0.779941809
[4,] 0.165711587 0.33142317 0.834288413
[5,] 0.145678829 0.29135766 0.854321171
[6,] 0.116031976 0.23206395 0.883968024
[7,] 0.116775853 0.23355171 0.883224147
[8,] 0.108543273 0.21708655 0.891456727
[9,] 0.102706646 0.20541329 0.897293354
[10,] 0.076247283 0.15249457 0.923752717
[11,] 0.056759848 0.11351970 0.943240152
[12,] 0.039723230 0.07944646 0.960276770
[13,] 0.028100846 0.05620169 0.971899154
[14,] 0.020308307 0.04061661 0.979691693
[15,] 0.015644040 0.03128808 0.984355960
[16,] 0.011077185 0.02215437 0.988922815
[17,] 0.009817137 0.01963427 0.990182863
[18,] 0.007243892 0.01448778 0.992756108
[19,] 0.011044245 0.02208849 0.988955755
[20,] 0.013615467 0.02723093 0.986384533
[21,] 0.019777336 0.03955467 0.980222664
[22,] 0.020409017 0.04081803 0.979590983
[23,] 0.019792515 0.03958503 0.980207485
[24,] 0.021009557 0.04201911 0.978990443
[25,] 0.025953007 0.05190601 0.974046993
[26,] 0.033871059 0.06774212 0.966128941
[27,] 0.049037607 0.09807521 0.950962393
[28,] 0.115141121 0.23028224 0.884858879
[29,] 0.181935066 0.36387013 0.818064934
[30,] 0.276306838 0.55261368 0.723693162
[31,] 0.374157194 0.74831439 0.625842806
[32,] 0.565099195 0.86980161 0.434900805
[33,] 0.706953429 0.58609314 0.293046571
[34,] 0.742308085 0.51538383 0.257691915
[35,] 0.772654047 0.45469191 0.227345953
[36,] 0.794496837 0.41100633 0.205503163
[37,] 0.812621466 0.37475707 0.187378534
[38,] 0.816613773 0.36677245 0.183386227
[39,] 0.850902296 0.29819541 0.149097704
[40,] 0.923722808 0.15255438 0.076277192
[41,] 0.974916565 0.05016687 0.025083435
[42,] 0.991822487 0.01635503 0.008177513
[43,] 0.987654031 0.02469194 0.012345969
[44,] 0.989923761 0.02015248 0.010076239
[45,] 0.985192060 0.02961588 0.014807940
[46,] 0.975495461 0.04900908 0.024504539
[47,] 0.951960869 0.09607826 0.048039131
[48,] 0.914162031 0.17167594 0.085837969
[49,] 0.868272750 0.26345450 0.131727250
[50,] 0.812498210 0.37500358 0.187501790
[51,] 0.709722347 0.58055531 0.290277653
> postscript(file="/var/www/html/rcomp/tmp/1b1jk1258643665.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2hjkr1258643665.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3y2tn1258643665.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/44hbs1258643665.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/55pr01258643665.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
2.04007710 1.49199563 0.61469560 0.48450609 0.73771924 0.69532446
7 8 9 10 11 12
0.62176920 0.40077978 0.16212977 0.16652185 1.58792720 1.11663753
13 14 15 16 17 18
1.31770078 1.07368773 0.52519031 0.68418244 0.65195871 0.58482975
19 20 21 22 23 24
0.41941134 0.52047458 0.21941134 0.40655876 1.30216668 0.90817703
25 26 27 28 29 30
1.01534291 0.80623510 0.54081669 0.46758509 0.34585608 0.42722453
31 32 33 34 35 36
0.41298505 0.78760355 0.12925874 -0.30564651 -0.04494383 -0.84739398
37 38 39 40 41 42
-1.00939127 -0.64055175 -0.43916485 -0.52427806 -0.89482814 -0.97716755
43 44 45 46 47 48
-1.43444912 -1.79547545 -1.94290962 -1.70971493 -0.27138857 -0.17619659
49 50 51 52 53 54
-0.49889656 -0.55308067 -0.97545700 -1.00703341 -0.61077818 -0.57790714
55 56 57 58 59 60
-0.73315450 -1.03176760 -1.71484660 -1.66163345 -0.63990444 -0.64878088
> postscript(file="/var/www/html/rcomp/tmp/6p2hz1258643665.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 2.04007710 NA
1 1.49199563 2.04007710
2 0.61469560 1.49199563
3 0.48450609 0.61469560
4 0.73771924 0.48450609
5 0.69532446 0.73771924
6 0.62176920 0.69532446
7 0.40077978 0.62176920
8 0.16212977 0.40077978
9 0.16652185 0.16212977
10 1.58792720 0.16652185
11 1.11663753 1.58792720
12 1.31770078 1.11663753
13 1.07368773 1.31770078
14 0.52519031 1.07368773
15 0.68418244 0.52519031
16 0.65195871 0.68418244
17 0.58482975 0.65195871
18 0.41941134 0.58482975
19 0.52047458 0.41941134
20 0.21941134 0.52047458
21 0.40655876 0.21941134
22 1.30216668 0.40655876
23 0.90817703 1.30216668
24 1.01534291 0.90817703
25 0.80623510 1.01534291
26 0.54081669 0.80623510
27 0.46758509 0.54081669
28 0.34585608 0.46758509
29 0.42722453 0.34585608
30 0.41298505 0.42722453
31 0.78760355 0.41298505
32 0.12925874 0.78760355
33 -0.30564651 0.12925874
34 -0.04494383 -0.30564651
35 -0.84739398 -0.04494383
36 -1.00939127 -0.84739398
37 -0.64055175 -1.00939127
38 -0.43916485 -0.64055175
39 -0.52427806 -0.43916485
40 -0.89482814 -0.52427806
41 -0.97716755 -0.89482814
42 -1.43444912 -0.97716755
43 -1.79547545 -1.43444912
44 -1.94290962 -1.79547545
45 -1.70971493 -1.94290962
46 -0.27138857 -1.70971493
47 -0.17619659 -0.27138857
48 -0.49889656 -0.17619659
49 -0.55308067 -0.49889656
50 -0.97545700 -0.55308067
51 -1.00703341 -0.97545700
52 -0.61077818 -1.00703341
53 -0.57790714 -0.61077818
54 -0.73315450 -0.57790714
55 -1.03176760 -0.73315450
56 -1.71484660 -1.03176760
57 -1.66163345 -1.71484660
58 -0.63990444 -1.66163345
59 -0.64878088 -0.63990444
60 NA -0.64878088
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.49199563 2.04007710
[2,] 0.61469560 1.49199563
[3,] 0.48450609 0.61469560
[4,] 0.73771924 0.48450609
[5,] 0.69532446 0.73771924
[6,] 0.62176920 0.69532446
[7,] 0.40077978 0.62176920
[8,] 0.16212977 0.40077978
[9,] 0.16652185 0.16212977
[10,] 1.58792720 0.16652185
[11,] 1.11663753 1.58792720
[12,] 1.31770078 1.11663753
[13,] 1.07368773 1.31770078
[14,] 0.52519031 1.07368773
[15,] 0.68418244 0.52519031
[16,] 0.65195871 0.68418244
[17,] 0.58482975 0.65195871
[18,] 0.41941134 0.58482975
[19,] 0.52047458 0.41941134
[20,] 0.21941134 0.52047458
[21,] 0.40655876 0.21941134
[22,] 1.30216668 0.40655876
[23,] 0.90817703 1.30216668
[24,] 1.01534291 0.90817703
[25,] 0.80623510 1.01534291
[26,] 0.54081669 0.80623510
[27,] 0.46758509 0.54081669
[28,] 0.34585608 0.46758509
[29,] 0.42722453 0.34585608
[30,] 0.41298505 0.42722453
[31,] 0.78760355 0.41298505
[32,] 0.12925874 0.78760355
[33,] -0.30564651 0.12925874
[34,] -0.04494383 -0.30564651
[35,] -0.84739398 -0.04494383
[36,] -1.00939127 -0.84739398
[37,] -0.64055175 -1.00939127
[38,] -0.43916485 -0.64055175
[39,] -0.52427806 -0.43916485
[40,] -0.89482814 -0.52427806
[41,] -0.97716755 -0.89482814
[42,] -1.43444912 -0.97716755
[43,] -1.79547545 -1.43444912
[44,] -1.94290962 -1.79547545
[45,] -1.70971493 -1.94290962
[46,] -0.27138857 -1.70971493
[47,] -0.17619659 -0.27138857
[48,] -0.49889656 -0.17619659
[49,] -0.55308067 -0.49889656
[50,] -0.97545700 -0.55308067
[51,] -1.00703341 -0.97545700
[52,] -0.61077818 -1.00703341
[53,] -0.57790714 -0.61077818
[54,] -0.73315450 -0.57790714
[55,] -1.03176760 -0.73315450
[56,] -1.71484660 -1.03176760
[57,] -1.66163345 -1.71484660
[58,] -0.63990444 -1.66163345
[59,] -0.64878088 -0.63990444
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.49199563 2.04007710
2 0.61469560 1.49199563
3 0.48450609 0.61469560
4 0.73771924 0.48450609
5 0.69532446 0.73771924
6 0.62176920 0.69532446
7 0.40077978 0.62176920
8 0.16212977 0.40077978
9 0.16652185 0.16212977
10 1.58792720 0.16652185
11 1.11663753 1.58792720
12 1.31770078 1.11663753
13 1.07368773 1.31770078
14 0.52519031 1.07368773
15 0.68418244 0.52519031
16 0.65195871 0.68418244
17 0.58482975 0.65195871
18 0.41941134 0.58482975
19 0.52047458 0.41941134
20 0.21941134 0.52047458
21 0.40655876 0.21941134
22 1.30216668 0.40655876
23 0.90817703 1.30216668
24 1.01534291 0.90817703
25 0.80623510 1.01534291
26 0.54081669 0.80623510
27 0.46758509 0.54081669
28 0.34585608 0.46758509
29 0.42722453 0.34585608
30 0.41298505 0.42722453
31 0.78760355 0.41298505
32 0.12925874 0.78760355
33 -0.30564651 0.12925874
34 -0.04494383 -0.30564651
35 -0.84739398 -0.04494383
36 -1.00939127 -0.84739398
37 -0.64055175 -1.00939127
38 -0.43916485 -0.64055175
39 -0.52427806 -0.43916485
40 -0.89482814 -0.52427806
41 -0.97716755 -0.89482814
42 -1.43444912 -0.97716755
43 -1.79547545 -1.43444912
44 -1.94290962 -1.79547545
45 -1.70971493 -1.94290962
46 -0.27138857 -1.70971493
47 -0.17619659 -0.27138857
48 -0.49889656 -0.17619659
49 -0.55308067 -0.49889656
50 -0.97545700 -0.55308067
51 -1.00703341 -0.97545700
52 -0.61077818 -1.00703341
53 -0.57790714 -0.61077818
54 -0.73315450 -0.57790714
55 -1.03176760 -0.73315450
56 -1.71484660 -1.03176760
57 -1.66163345 -1.71484660
58 -0.63990444 -1.66163345
59 -0.64878088 -0.63990444
> 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/7vppe1258643665.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/86io11258643665.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/99myb1258643665.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10fhfn1258643665.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11b7bq1258643665.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/12smli1258643665.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/13i28s1258643665.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/143yb41258643665.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/15zhdc1258643665.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/16g9dm1258643665.tab")
+ }
>
> system("convert tmp/1b1jk1258643665.ps tmp/1b1jk1258643665.png")
> system("convert tmp/2hjkr1258643665.ps tmp/2hjkr1258643665.png")
> system("convert tmp/3y2tn1258643665.ps tmp/3y2tn1258643665.png")
> system("convert tmp/44hbs1258643665.ps tmp/44hbs1258643665.png")
> system("convert tmp/55pr01258643665.ps tmp/55pr01258643665.png")
> system("convert tmp/6p2hz1258643665.ps tmp/6p2hz1258643665.png")
> system("convert tmp/7vppe1258643665.ps tmp/7vppe1258643665.png")
> system("convert tmp/86io11258643665.ps tmp/86io11258643665.png")
> system("convert tmp/99myb1258643665.ps tmp/99myb1258643665.png")
> system("convert tmp/10fhfn1258643665.ps tmp/10fhfn1258643665.png")
>
>
> proc.time()
user system elapsed
2.512 1.574 3.527