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(286602,0,283042,0,276687,0,277915,0,277128,0,277103,0,275037,0,270150,0,267140,0,264993,0,287259,0,291186,0,292300,0,288186,0,281477,0,282656,0,280190,0,280408,0,276836,0,275216,0,274352,0,271311,0,289802,0,290726,0,292300,0,278506,0,269826,0,265861,0,269034,0,264176,0,255198,0,253353,0,246057,0,235372,0,258556,0,260993,0,254663,0,250643,0,243422,0,247105,0,248541,0,245039,1,237080,1,237085,1,225554,1,226839,1,247934,1,248333,1,246969,1,245098,1,246263,1,255765,1,264319,1,268347,1,273046,1,273963,1,267430,1,271993,1,292710,1,295881,1),dim=c(2,60),dimnames=list(c('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 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 1
43 237080 1
44 237085 1
45 225554 1
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) X
271008 -14710
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-35636 -11214 1824 11745 39584
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 271008 2615 103.640 < 2e-16 ***
X -14710 4647 -3.166 0.00247 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 16740 on 58 degrees of freedom
Multiple R-squared: 0.1473, Adjusted R-squared: 0.1326
F-statistic: 10.02 on 1 and 58 DF, p-value: 0.002466
> 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,] 3.237215e-02 6.474429e-02 0.9676279
[2,] 9.255015e-03 1.851003e-02 0.9907450
[3,] 3.327274e-03 6.654549e-03 0.9966727
[4,] 3.170822e-03 6.341644e-03 0.9968292
[5,] 3.794698e-03 7.589395e-03 0.9962053
[6,] 4.407133e-03 8.814266e-03 0.9955929
[7,] 4.711717e-03 9.423435e-03 0.9952883
[8,] 7.460744e-03 1.492149e-02 0.9925393
[9,] 1.046773e-02 2.093545e-02 0.9895323
[10,] 8.158824e-03 1.631765e-02 0.9918412
[11,] 4.207004e-03 8.414008e-03 0.9957930
[12,] 2.222220e-03 4.444439e-03 0.9977778
[13,] 1.078601e-03 2.157201e-03 0.9989214
[14,] 5.188971e-04 1.037794e-03 0.9994811
[15,] 2.485583e-04 4.971167e-04 0.9997514
[16,] 1.241109e-04 2.482217e-04 0.9998759
[17,] 6.365295e-05 1.273059e-04 0.9999363
[18,] 4.029626e-05 8.059251e-05 0.9999597
[19,] 5.993998e-05 1.198800e-04 0.9999401
[20,] 1.111807e-04 2.223615e-04 0.9998888
[21,] 3.081689e-04 6.163378e-04 0.9996918
[22,] 2.327752e-04 4.655504e-04 0.9997672
[23,] 2.390957e-04 4.781914e-04 0.9997609
[24,] 3.377043e-04 6.754087e-04 0.9996623
[25,] 3.514002e-04 7.028004e-04 0.9996486
[26,] 5.141430e-04 1.028286e-03 0.9994859
[27,] 1.688874e-03 3.377748e-03 0.9983111
[28,] 4.293686e-03 8.587371e-03 0.9957063
[29,] 1.497575e-02 2.995150e-02 0.9850242
[30,] 7.641567e-02 1.528313e-01 0.9235843
[31,] 6.820435e-02 1.364087e-01 0.9317957
[32,] 5.894586e-02 1.178917e-01 0.9410541
[33,] 5.559887e-02 1.111977e-01 0.9444011
[34,] 5.613315e-02 1.122663e-01 0.9438668
[35,] 6.857615e-02 1.371523e-01 0.9314239
[36,] 6.772523e-02 1.354505e-01 0.9322748
[37,] 6.134062e-02 1.226812e-01 0.9386594
[38,] 4.462835e-02 8.925669e-02 0.9553717
[39,] 4.070066e-02 8.140131e-02 0.9592993
[40,] 3.870434e-02 7.740868e-02 0.9612957
[41,] 8.090463e-02 1.618093e-01 0.9190954
[42,] 1.872544e-01 3.745088e-01 0.8127456
[43,] 1.839875e-01 3.679751e-01 0.8160125
[44,] 1.849633e-01 3.699267e-01 0.8150367
[45,] 2.088667e-01 4.177334e-01 0.7911333
[46,] 2.944413e-01 5.888827e-01 0.7055587
[47,] 4.709546e-01 9.419092e-01 0.5290454
[48,] 5.638973e-01 8.722055e-01 0.4361027
[49,] 5.541080e-01 8.917840e-01 0.4458920
[50,] 4.999659e-01 9.999317e-01 0.5000341
[51,] 3.918607e-01 7.837214e-01 0.6081393
> postscript(file="/var/www/html/rcomp/tmp/1kx001259332650.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/28z961259332650.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/30sfh1259332650.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4o1uk1259332650.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/52zuo1259332650.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
15594.4878 12034.4878 5679.4878 6907.4878 6120.4878 6095.4878
7 8 9 10 11 12
4029.4878 -857.5122 -3867.5122 -6014.5122 16251.4878 20178.4878
13 14 15 16 17 18
21292.4878 17178.4878 10469.4878 11648.4878 9182.4878 9400.4878
19 20 21 22 23 24
5828.4878 4208.4878 3344.4878 303.4878 18794.4878 19718.4878
25 26 27 28 29 30
21292.4878 7498.4878 -1181.5122 -5146.5122 -1973.5122 -6831.5122
31 32 33 34 35 36
-15809.5122 -17654.5122 -24950.5122 -35635.5122 -12451.5122 -10014.5122
37 38 39 40 41 42
-16344.5122 -20364.5122 -27585.5122 -23902.5122 -22466.5122 -11258.2632
43 44 45 46 47 48
-19217.2632 -19212.2632 -30743.2632 -29458.2632 -8363.2632 -7964.2632
49 50 51 52 53 54
-9328.2632 -11199.2632 -10034.2632 -532.2632 8021.7368 12049.7368
55 56 57 58 59 60
16748.7368 17665.7368 11132.7368 15695.7368 36412.7368 39583.7368
> postscript(file="/var/www/html/rcomp/tmp/69o881259332650.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 15594.4878 NA
1 12034.4878 15594.4878
2 5679.4878 12034.4878
3 6907.4878 5679.4878
4 6120.4878 6907.4878
5 6095.4878 6120.4878
6 4029.4878 6095.4878
7 -857.5122 4029.4878
8 -3867.5122 -857.5122
9 -6014.5122 -3867.5122
10 16251.4878 -6014.5122
11 20178.4878 16251.4878
12 21292.4878 20178.4878
13 17178.4878 21292.4878
14 10469.4878 17178.4878
15 11648.4878 10469.4878
16 9182.4878 11648.4878
17 9400.4878 9182.4878
18 5828.4878 9400.4878
19 4208.4878 5828.4878
20 3344.4878 4208.4878
21 303.4878 3344.4878
22 18794.4878 303.4878
23 19718.4878 18794.4878
24 21292.4878 19718.4878
25 7498.4878 21292.4878
26 -1181.5122 7498.4878
27 -5146.5122 -1181.5122
28 -1973.5122 -5146.5122
29 -6831.5122 -1973.5122
30 -15809.5122 -6831.5122
31 -17654.5122 -15809.5122
32 -24950.5122 -17654.5122
33 -35635.5122 -24950.5122
34 -12451.5122 -35635.5122
35 -10014.5122 -12451.5122
36 -16344.5122 -10014.5122
37 -20364.5122 -16344.5122
38 -27585.5122 -20364.5122
39 -23902.5122 -27585.5122
40 -22466.5122 -23902.5122
41 -11258.2632 -22466.5122
42 -19217.2632 -11258.2632
43 -19212.2632 -19217.2632
44 -30743.2632 -19212.2632
45 -29458.2632 -30743.2632
46 -8363.2632 -29458.2632
47 -7964.2632 -8363.2632
48 -9328.2632 -7964.2632
49 -11199.2632 -9328.2632
50 -10034.2632 -11199.2632
51 -532.2632 -10034.2632
52 8021.7368 -532.2632
53 12049.7368 8021.7368
54 16748.7368 12049.7368
55 17665.7368 16748.7368
56 11132.7368 17665.7368
57 15695.7368 11132.7368
58 36412.7368 15695.7368
59 39583.7368 36412.7368
60 NA 39583.7368
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 12034.4878 15594.4878
[2,] 5679.4878 12034.4878
[3,] 6907.4878 5679.4878
[4,] 6120.4878 6907.4878
[5,] 6095.4878 6120.4878
[6,] 4029.4878 6095.4878
[7,] -857.5122 4029.4878
[8,] -3867.5122 -857.5122
[9,] -6014.5122 -3867.5122
[10,] 16251.4878 -6014.5122
[11,] 20178.4878 16251.4878
[12,] 21292.4878 20178.4878
[13,] 17178.4878 21292.4878
[14,] 10469.4878 17178.4878
[15,] 11648.4878 10469.4878
[16,] 9182.4878 11648.4878
[17,] 9400.4878 9182.4878
[18,] 5828.4878 9400.4878
[19,] 4208.4878 5828.4878
[20,] 3344.4878 4208.4878
[21,] 303.4878 3344.4878
[22,] 18794.4878 303.4878
[23,] 19718.4878 18794.4878
[24,] 21292.4878 19718.4878
[25,] 7498.4878 21292.4878
[26,] -1181.5122 7498.4878
[27,] -5146.5122 -1181.5122
[28,] -1973.5122 -5146.5122
[29,] -6831.5122 -1973.5122
[30,] -15809.5122 -6831.5122
[31,] -17654.5122 -15809.5122
[32,] -24950.5122 -17654.5122
[33,] -35635.5122 -24950.5122
[34,] -12451.5122 -35635.5122
[35,] -10014.5122 -12451.5122
[36,] -16344.5122 -10014.5122
[37,] -20364.5122 -16344.5122
[38,] -27585.5122 -20364.5122
[39,] -23902.5122 -27585.5122
[40,] -22466.5122 -23902.5122
[41,] -11258.2632 -22466.5122
[42,] -19217.2632 -11258.2632
[43,] -19212.2632 -19217.2632
[44,] -30743.2632 -19212.2632
[45,] -29458.2632 -30743.2632
[46,] -8363.2632 -29458.2632
[47,] -7964.2632 -8363.2632
[48,] -9328.2632 -7964.2632
[49,] -11199.2632 -9328.2632
[50,] -10034.2632 -11199.2632
[51,] -532.2632 -10034.2632
[52,] 8021.7368 -532.2632
[53,] 12049.7368 8021.7368
[54,] 16748.7368 12049.7368
[55,] 17665.7368 16748.7368
[56,] 11132.7368 17665.7368
[57,] 15695.7368 11132.7368
[58,] 36412.7368 15695.7368
[59,] 39583.7368 36412.7368
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 12034.4878 15594.4878
2 5679.4878 12034.4878
3 6907.4878 5679.4878
4 6120.4878 6907.4878
5 6095.4878 6120.4878
6 4029.4878 6095.4878
7 -857.5122 4029.4878
8 -3867.5122 -857.5122
9 -6014.5122 -3867.5122
10 16251.4878 -6014.5122
11 20178.4878 16251.4878
12 21292.4878 20178.4878
13 17178.4878 21292.4878
14 10469.4878 17178.4878
15 11648.4878 10469.4878
16 9182.4878 11648.4878
17 9400.4878 9182.4878
18 5828.4878 9400.4878
19 4208.4878 5828.4878
20 3344.4878 4208.4878
21 303.4878 3344.4878
22 18794.4878 303.4878
23 19718.4878 18794.4878
24 21292.4878 19718.4878
25 7498.4878 21292.4878
26 -1181.5122 7498.4878
27 -5146.5122 -1181.5122
28 -1973.5122 -5146.5122
29 -6831.5122 -1973.5122
30 -15809.5122 -6831.5122
31 -17654.5122 -15809.5122
32 -24950.5122 -17654.5122
33 -35635.5122 -24950.5122
34 -12451.5122 -35635.5122
35 -10014.5122 -12451.5122
36 -16344.5122 -10014.5122
37 -20364.5122 -16344.5122
38 -27585.5122 -20364.5122
39 -23902.5122 -27585.5122
40 -22466.5122 -23902.5122
41 -11258.2632 -22466.5122
42 -19217.2632 -11258.2632
43 -19212.2632 -19217.2632
44 -30743.2632 -19212.2632
45 -29458.2632 -30743.2632
46 -8363.2632 -29458.2632
47 -7964.2632 -8363.2632
48 -9328.2632 -7964.2632
49 -11199.2632 -9328.2632
50 -10034.2632 -11199.2632
51 -532.2632 -10034.2632
52 8021.7368 -532.2632
53 12049.7368 8021.7368
54 16748.7368 12049.7368
55 17665.7368 16748.7368
56 11132.7368 17665.7368
57 15695.7368 11132.7368
58 36412.7368 15695.7368
59 39583.7368 36412.7368
> 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/77t1b1259332650.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8bwtl1259332650.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9d3du1259332650.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/108cjr1259332650.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/117y9x1259332650.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/12wj1c1259332650.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/13lkcg1259332650.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/14989z1259332650.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/15hson1259332650.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/16xnuq1259332650.tab")
+ }
>
> system("convert tmp/1kx001259332650.ps tmp/1kx001259332650.png")
> system("convert tmp/28z961259332650.ps tmp/28z961259332650.png")
> system("convert tmp/30sfh1259332650.ps tmp/30sfh1259332650.png")
> system("convert tmp/4o1uk1259332650.ps tmp/4o1uk1259332650.png")
> system("convert tmp/52zuo1259332650.ps tmp/52zuo1259332650.png")
> system("convert tmp/69o881259332650.ps tmp/69o881259332650.png")
> system("convert tmp/77t1b1259332650.ps tmp/77t1b1259332650.png")
> system("convert tmp/8bwtl1259332650.ps tmp/8bwtl1259332650.png")
> system("convert tmp/9d3du1259332650.ps tmp/9d3du1259332650.png")
> system("convert tmp/108cjr1259332650.ps tmp/108cjr1259332650.png")
>
>
> proc.time()
user system elapsed
2.489 1.578 2.924