R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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(3494.17,0,3667.03,0,3813.06,0,3917.96,0,3895.51,0,3801.06,0,3570.12,0,3701.61,0,3862.27,0,3970.1,0,4138.52,0,4199.75,0,4290.89,0,4443.91,0,4502.64,0,4356.98,0,4591.27,0,4696.96,0,4621.4,0,4562.84,0,4202.52,0,4296.49,0,4435.23,0,4105.18,0,4116.68,0,3844.49,0,3720.98,0,3674.4,0,3857.62,0,3801.06,0,3504.37,0,3032.6,0,3047.03,0,2962.34,1,2197.82,1,2014.45,1,1862.83,1,1905.41,1,1810.99,1,1670.07,1,1864.44,1,2052.02,1,2029.6,1,2070.83,1,2293.41,1,2443.27,1,2513.17,1,2466.92,1,2502.66,1,2539.91,1,2482.6,1,2626.15,1,2656.32,1,2446.66,1,2467.38,1,2462.32,1,2504.58,1,2579.39,1,2649.24,1,2636.87,1),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
> 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 3494.17 0
2 3667.03 0
3 3813.06 0
4 3917.96 0
5 3895.51 0
6 3801.06 0
7 3570.12 0
8 3701.61 0
9 3862.27 0
10 3970.10 0
11 4138.52 0
12 4199.75 0
13 4290.89 0
14 4443.91 0
15 4502.64 0
16 4356.98 0
17 4591.27 0
18 4696.96 0
19 4621.40 0
20 4562.84 0
21 4202.52 0
22 4296.49 0
23 4435.23 0
24 4105.18 0
25 4116.68 0
26 3844.49 0
27 3720.98 0
28 3674.40 0
29 3857.62 0
30 3801.06 0
31 3504.37 0
32 3032.60 0
33 3047.03 0
34 2962.34 1
35 2197.82 1
36 2014.45 1
37 1862.83 1
38 1905.41 1
39 1810.99 1
40 1670.07 1
41 1864.44 1
42 2052.02 1
43 2029.60 1
44 2070.83 1
45 2293.41 1
46 2443.27 1
47 2513.17 1
48 2466.92 1
49 2502.66 1
50 2539.91 1
51 2482.60 1
52 2626.15 1
53 2656.32 1
54 2446.66 1
55 2467.38 1
56 2462.32 1
57 2504.58 1
58 2579.39 1
59 2649.24 1
60 2636.87 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
3992 -1669
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-959.4 -275.9 116.9 267.3 704.9
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3992.02 66.55 59.98 <2e-16 ***
X -1669.37 99.21 -16.83 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 382.3 on 58 degrees of freedom
Multiple R-squared: 0.83, Adjusted R-squared: 0.8271
F-statistic: 283.1 on 1 and 58 DF, p-value: < 2.2e-16
> 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,] 0.157540946 3.150819e-01 8.424591e-01
[2,] 0.066645454 1.332909e-01 9.333545e-01
[3,] 0.043305276 8.661055e-02 9.566947e-01
[4,] 0.017849064 3.569813e-02 9.821509e-01
[5,] 0.008648991 1.729798e-02 9.913510e-01
[6,] 0.006747343 1.349469e-02 9.932527e-01
[7,] 0.013142257 2.628451e-02 9.868577e-01
[8,] 0.022010133 4.402027e-02 9.779899e-01
[9,] 0.039432318 7.886464e-02 9.605677e-01
[10,] 0.091626512 1.832530e-01 9.083735e-01
[11,] 0.166641531 3.332831e-01 8.333585e-01
[12,] 0.173066273 3.461325e-01 8.269337e-01
[13,] 0.278165953 5.563319e-01 7.218340e-01
[14,] 0.456468869 9.129377e-01 5.435311e-01
[15,] 0.579194065 8.416119e-01 4.208059e-01
[16,] 0.668411832 6.631763e-01 3.315882e-01
[17,] 0.626009514 7.479810e-01 3.739905e-01
[18,] 0.618583596 7.628328e-01 3.814164e-01
[19,] 0.692539776 6.149204e-01 3.074602e-01
[20,] 0.671596217 6.568076e-01 3.284038e-01
[21,] 0.670683184 6.586336e-01 3.293168e-01
[22,] 0.649861596 7.002768e-01 3.501384e-01
[23,] 0.639455770 7.210885e-01 3.605442e-01
[24,] 0.633418439 7.331631e-01 3.665816e-01
[25,] 0.639049247 7.219015e-01 3.609508e-01
[26,] 0.676924181 6.461516e-01 3.230758e-01
[27,] 0.733666799 5.326664e-01 2.663332e-01
[28,] 0.851560793 2.968784e-01 1.484392e-01
[29,] 0.902486204 1.950276e-01 9.751380e-02
[30,] 0.935157440 1.296851e-01 6.484256e-02
[31,] 0.926490046 1.470199e-01 7.350995e-02
[32,] 0.923011790 1.539764e-01 7.698821e-02
[33,] 0.938022635 1.239547e-01 6.197737e-02
[34,] 0.945040532 1.099189e-01 5.495947e-02
[35,] 0.967246084 6.550783e-02 3.275392e-02
[36,] 0.994964302 1.007140e-02 5.035698e-03
[37,] 0.999006681 1.986639e-03 9.933193e-04
[38,] 0.999572242 8.555165e-04 4.277582e-04
[39,] 0.999946349 1.073011e-04 5.365053e-05
[40,] 0.999999288 1.424570e-06 7.122851e-07
[41,] 0.999999859 2.814404e-07 1.407202e-07
[42,] 0.999999646 7.072613e-07 3.536307e-07
[43,] 0.999998450 3.099907e-06 1.549953e-06
[44,] 0.999995088 9.824775e-06 4.912388e-06
[45,] 0.999980041 3.991706e-05 1.995853e-05
[46,] 0.999911273 1.774548e-04 8.872742e-05
[47,] 0.999703916 5.921689e-04 2.960845e-04
[48,] 0.999039483 1.921034e-03 9.605171e-04
[49,] 0.997871045 4.257910e-03 2.128955e-03
[50,] 0.993924601 1.215080e-02 6.075399e-03
[51,] 0.981360921 3.727816e-02 1.863908e-02
> postscript(file="/var/www/rcomp/tmp/1xi7y1292765146.ps",horizontal=F,onefile=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/27a6j1292765146.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/rcomp/tmp/37a6j1292765146.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/47a6j1292765146.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/50j541292765146.ps",horizontal=F,onefile=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 7
-497.85121 -324.99121 -178.96121 -74.06121 -96.51121 -190.96121 -421.90121
8 9 10 11 12 13 14
-290.41121 -129.75121 -21.92121 146.49879 207.72879 298.86879 451.88879
15 16 17 18 19 20 21
510.61879 364.95879 599.24879 704.93879 629.37879 570.81879 210.49879
22 23 24 25 26 27 28
304.46879 443.20879 113.15879 124.65879 -147.53121 -271.04121 -317.62121
29 30 31 32 33 34 35
-134.40121 -190.96121 -487.65121 -959.42121 -944.99121 639.68630 -124.83370
36 37 38 39 40 41 42
-308.20370 -459.82370 -417.24370 -511.66370 -652.58370 -458.21370 -270.63370
43 44 45 46 47 48 49
-293.05370 -251.82370 -29.24370 120.61630 190.51630 144.26630 180.00630
50 51 52 53 54 55 56
217.25630 159.94630 303.49630 333.66630 124.00630 144.72630 139.66630
57 58 59 60
181.92630 256.73630 326.58630 314.21630
> postscript(file="/var/www/rcomp/tmp/60j541292765146.ps",horizontal=F,onefile=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 -497.85121 NA
1 -324.99121 -497.85121
2 -178.96121 -324.99121
3 -74.06121 -178.96121
4 -96.51121 -74.06121
5 -190.96121 -96.51121
6 -421.90121 -190.96121
7 -290.41121 -421.90121
8 -129.75121 -290.41121
9 -21.92121 -129.75121
10 146.49879 -21.92121
11 207.72879 146.49879
12 298.86879 207.72879
13 451.88879 298.86879
14 510.61879 451.88879
15 364.95879 510.61879
16 599.24879 364.95879
17 704.93879 599.24879
18 629.37879 704.93879
19 570.81879 629.37879
20 210.49879 570.81879
21 304.46879 210.49879
22 443.20879 304.46879
23 113.15879 443.20879
24 124.65879 113.15879
25 -147.53121 124.65879
26 -271.04121 -147.53121
27 -317.62121 -271.04121
28 -134.40121 -317.62121
29 -190.96121 -134.40121
30 -487.65121 -190.96121
31 -959.42121 -487.65121
32 -944.99121 -959.42121
33 639.68630 -944.99121
34 -124.83370 639.68630
35 -308.20370 -124.83370
36 -459.82370 -308.20370
37 -417.24370 -459.82370
38 -511.66370 -417.24370
39 -652.58370 -511.66370
40 -458.21370 -652.58370
41 -270.63370 -458.21370
42 -293.05370 -270.63370
43 -251.82370 -293.05370
44 -29.24370 -251.82370
45 120.61630 -29.24370
46 190.51630 120.61630
47 144.26630 190.51630
48 180.00630 144.26630
49 217.25630 180.00630
50 159.94630 217.25630
51 303.49630 159.94630
52 333.66630 303.49630
53 124.00630 333.66630
54 144.72630 124.00630
55 139.66630 144.72630
56 181.92630 139.66630
57 256.73630 181.92630
58 326.58630 256.73630
59 314.21630 326.58630
60 NA 314.21630
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -324.99121 -497.85121
[2,] -178.96121 -324.99121
[3,] -74.06121 -178.96121
[4,] -96.51121 -74.06121
[5,] -190.96121 -96.51121
[6,] -421.90121 -190.96121
[7,] -290.41121 -421.90121
[8,] -129.75121 -290.41121
[9,] -21.92121 -129.75121
[10,] 146.49879 -21.92121
[11,] 207.72879 146.49879
[12,] 298.86879 207.72879
[13,] 451.88879 298.86879
[14,] 510.61879 451.88879
[15,] 364.95879 510.61879
[16,] 599.24879 364.95879
[17,] 704.93879 599.24879
[18,] 629.37879 704.93879
[19,] 570.81879 629.37879
[20,] 210.49879 570.81879
[21,] 304.46879 210.49879
[22,] 443.20879 304.46879
[23,] 113.15879 443.20879
[24,] 124.65879 113.15879
[25,] -147.53121 124.65879
[26,] -271.04121 -147.53121
[27,] -317.62121 -271.04121
[28,] -134.40121 -317.62121
[29,] -190.96121 -134.40121
[30,] -487.65121 -190.96121
[31,] -959.42121 -487.65121
[32,] -944.99121 -959.42121
[33,] 639.68630 -944.99121
[34,] -124.83370 639.68630
[35,] -308.20370 -124.83370
[36,] -459.82370 -308.20370
[37,] -417.24370 -459.82370
[38,] -511.66370 -417.24370
[39,] -652.58370 -511.66370
[40,] -458.21370 -652.58370
[41,] -270.63370 -458.21370
[42,] -293.05370 -270.63370
[43,] -251.82370 -293.05370
[44,] -29.24370 -251.82370
[45,] 120.61630 -29.24370
[46,] 190.51630 120.61630
[47,] 144.26630 190.51630
[48,] 180.00630 144.26630
[49,] 217.25630 180.00630
[50,] 159.94630 217.25630
[51,] 303.49630 159.94630
[52,] 333.66630 303.49630
[53,] 124.00630 333.66630
[54,] 144.72630 124.00630
[55,] 139.66630 144.72630
[56,] 181.92630 139.66630
[57,] 256.73630 181.92630
[58,] 326.58630 256.73630
[59,] 314.21630 326.58630
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -324.99121 -497.85121
2 -178.96121 -324.99121
3 -74.06121 -178.96121
4 -96.51121 -74.06121
5 -190.96121 -96.51121
6 -421.90121 -190.96121
7 -290.41121 -421.90121
8 -129.75121 -290.41121
9 -21.92121 -129.75121
10 146.49879 -21.92121
11 207.72879 146.49879
12 298.86879 207.72879
13 451.88879 298.86879
14 510.61879 451.88879
15 364.95879 510.61879
16 599.24879 364.95879
17 704.93879 599.24879
18 629.37879 704.93879
19 570.81879 629.37879
20 210.49879 570.81879
21 304.46879 210.49879
22 443.20879 304.46879
23 113.15879 443.20879
24 124.65879 113.15879
25 -147.53121 124.65879
26 -271.04121 -147.53121
27 -317.62121 -271.04121
28 -134.40121 -317.62121
29 -190.96121 -134.40121
30 -487.65121 -190.96121
31 -959.42121 -487.65121
32 -944.99121 -959.42121
33 639.68630 -944.99121
34 -124.83370 639.68630
35 -308.20370 -124.83370
36 -459.82370 -308.20370
37 -417.24370 -459.82370
38 -511.66370 -417.24370
39 -652.58370 -511.66370
40 -458.21370 -652.58370
41 -270.63370 -458.21370
42 -293.05370 -270.63370
43 -251.82370 -293.05370
44 -29.24370 -251.82370
45 120.61630 -29.24370
46 190.51630 120.61630
47 144.26630 190.51630
48 180.00630 144.26630
49 217.25630 180.00630
50 159.94630 217.25630
51 303.49630 159.94630
52 333.66630 303.49630
53 124.00630 333.66630
54 144.72630 124.00630
55 139.66630 144.72630
56 181.92630 139.66630
57 256.73630 181.92630
58 326.58630 256.73630
59 314.21630 326.58630
> 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/rcomp/tmp/7bsn71292765146.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/8bsn71292765146.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9l2ma1292765146.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10l2ma1292765146.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/11723g1292765146.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/rcomp/tmp/12al141292765146.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/rcomp/tmp/13z4yf1292765146.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/rcomp/tmp/149df01292765146.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/rcomp/tmp/15vvwo1292765146.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/rcomp/tmp/16yecc1292765146.tab")
+ }
>
> try(system("convert tmp/1xi7y1292765146.ps tmp/1xi7y1292765146.png",intern=TRUE))
character(0)
> try(system("convert tmp/27a6j1292765146.ps tmp/27a6j1292765146.png",intern=TRUE))
character(0)
> try(system("convert tmp/37a6j1292765146.ps tmp/37a6j1292765146.png",intern=TRUE))
character(0)
> try(system("convert tmp/47a6j1292765146.ps tmp/47a6j1292765146.png",intern=TRUE))
character(0)
> try(system("convert tmp/50j541292765146.ps tmp/50j541292765146.png",intern=TRUE))
character(0)
> try(system("convert tmp/60j541292765146.ps tmp/60j541292765146.png",intern=TRUE))
character(0)
> try(system("convert tmp/7bsn71292765146.ps tmp/7bsn71292765146.png",intern=TRUE))
character(0)
> try(system("convert tmp/8bsn71292765146.ps tmp/8bsn71292765146.png",intern=TRUE))
character(0)
> try(system("convert tmp/9l2ma1292765146.ps tmp/9l2ma1292765146.png",intern=TRUE))
character(0)
> try(system("convert tmp/10l2ma1292765146.ps tmp/10l2ma1292765146.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.180 1.670 4.828