R version 2.12.1 (2010-12-16)
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.
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Type 'demo()' for some demos, 'help()' for on-line help, or
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Type 'q()' to quit R.
> x <- array(list(101.76,102.37,102.38,102.86,102.87,102.92,102.95,103.02,104.08,104.16,104.24,104.33,104.73,104.86,105.03,105.62,105.63,105.63,105.94,106.61,107.69,107.78,107.93,108.48,108.14,108.48,108.48,108.89,108.93,109.21,109.47,109.80,111.73,111.85,112.12,112.15,112.17,112.67,112.80,113.44,113.53,114.53,114.51,115.05,116.67,117.07,116.92,117.00,117.02,117.35,117.36,117.82,117.88,118.24,118.50,118.80,119.76,120.09),dim=c(1,58),dimnames=list(c('vrijetijdsbesteding'),1:58))
> y <- array(NA,dim=c(1,58),dimnames=list(c('vrijetijdsbesteding'),1:58))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par20 = ''
> par19 = ''
> par18 = ''
> par17 = ''
> par16 = ''
> par15 = ''
> par14 = ''
> par13 = ''
> par12 = ''
> par11 = ''
> par10 = ''
> par9 = ''
> par8 = ''
> par7 = ''
> par6 = ''
> par5 = ''
> par4 = ''
> par3 = 'Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> 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
vrijetijdsbesteding M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 101.76 1 0 0 0 0 0 0 0 0 0 0 1
2 102.37 0 1 0 0 0 0 0 0 0 0 0 2
3 102.38 0 0 1 0 0 0 0 0 0 0 0 3
4 102.86 0 0 0 1 0 0 0 0 0 0 0 4
5 102.87 0 0 0 0 1 0 0 0 0 0 0 5
6 102.92 0 0 0 0 0 1 0 0 0 0 0 6
7 102.95 0 0 0 0 0 0 1 0 0 0 0 7
8 103.02 0 0 0 0 0 0 0 1 0 0 0 8
9 104.08 0 0 0 0 0 0 0 0 1 0 0 9
10 104.16 0 0 0 0 0 0 0 0 0 1 0 10
11 104.24 0 0 0 0 0 0 0 0 0 0 1 11
12 104.33 0 0 0 0 0 0 0 0 0 0 0 12
13 104.73 1 0 0 0 0 0 0 0 0 0 0 13
14 104.86 0 1 0 0 0 0 0 0 0 0 0 14
15 105.03 0 0 1 0 0 0 0 0 0 0 0 15
16 105.62 0 0 0 1 0 0 0 0 0 0 0 16
17 105.63 0 0 0 0 1 0 0 0 0 0 0 17
18 105.63 0 0 0 0 0 1 0 0 0 0 0 18
19 105.94 0 0 0 0 0 0 1 0 0 0 0 19
20 106.61 0 0 0 0 0 0 0 1 0 0 0 20
21 107.69 0 0 0 0 0 0 0 0 1 0 0 21
22 107.78 0 0 0 0 0 0 0 0 0 1 0 22
23 107.93 0 0 0 0 0 0 0 0 0 0 1 23
24 108.48 0 0 0 0 0 0 0 0 0 0 0 24
25 108.14 1 0 0 0 0 0 0 0 0 0 0 25
26 108.48 0 1 0 0 0 0 0 0 0 0 0 26
27 108.48 0 0 1 0 0 0 0 0 0 0 0 27
28 108.89 0 0 0 1 0 0 0 0 0 0 0 28
29 108.93 0 0 0 0 1 0 0 0 0 0 0 29
30 109.21 0 0 0 0 0 1 0 0 0 0 0 30
31 109.47 0 0 0 0 0 0 1 0 0 0 0 31
32 109.80 0 0 0 0 0 0 0 1 0 0 0 32
33 111.73 0 0 0 0 0 0 0 0 1 0 0 33
34 111.85 0 0 0 0 0 0 0 0 0 1 0 34
35 112.12 0 0 0 0 0 0 0 0 0 0 1 35
36 112.15 0 0 0 0 0 0 0 0 0 0 0 36
37 112.17 1 0 0 0 0 0 0 0 0 0 0 37
38 112.67 0 1 0 0 0 0 0 0 0 0 0 38
39 112.80 0 0 1 0 0 0 0 0 0 0 0 39
40 113.44 0 0 0 1 0 0 0 0 0 0 0 40
41 113.53 0 0 0 0 1 0 0 0 0 0 0 41
42 114.53 0 0 0 0 0 1 0 0 0 0 0 42
43 114.51 0 0 0 0 0 0 1 0 0 0 0 43
44 115.05 0 0 0 0 0 0 0 1 0 0 0 44
45 116.67 0 0 0 0 0 0 0 0 1 0 0 45
46 117.07 0 0 0 0 0 0 0 0 0 1 0 46
47 116.92 0 0 0 0 0 0 0 0 0 0 1 47
48 117.00 0 0 0 0 0 0 0 0 0 0 0 48
49 117.02 1 0 0 0 0 0 0 0 0 0 0 49
50 117.35 0 1 0 0 0 0 0 0 0 0 0 50
51 117.36 0 0 1 0 0 0 0 0 0 0 0 51
52 117.82 0 0 0 1 0 0 0 0 0 0 0 52
53 117.88 0 0 0 0 1 0 0 0 0 0 0 53
54 118.24 0 0 0 0 0 1 0 0 0 0 0 54
55 118.50 0 0 0 0 0 0 1 0 0 0 0 55
56 118.80 0 0 0 0 0 0 0 1 0 0 0 56
57 119.76 0 0 0 0 0 0 0 0 1 0 0 57
58 120.09 0 0 0 0 0 0 0 0 0 1 0 58
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) M1 M2 M3 M4 M5
100.67693 -0.09049 -0.03559 -0.29869 -0.10980 -0.39490
M6 M7 M8 M9 M10 M11
-0.38400 -0.54310 -0.48820 0.51469 0.39159 0.13960
t
0.32710
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.8960 -0.3683 -0.1329 0.3700 1.0744
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 100.676932 0.337006 298.739 <2e-16 ***
M1 -0.090489 0.408850 -0.221 0.826
M2 -0.035591 0.408592 -0.087 0.931
M3 -0.298693 0.408392 -0.731 0.468
M4 -0.109795 0.408249 -0.269 0.789
M5 -0.394898 0.408163 -0.967 0.338
M6 -0.384000 0.408135 -0.941 0.352
M7 -0.543102 0.408163 -1.331 0.190
M8 -0.488205 0.408249 -1.196 0.238
M9 0.514693 0.408392 1.260 0.214
M10 0.391591 0.408592 0.958 0.343
M11 0.139602 0.430239 0.324 0.747
t 0.327102 0.004834 67.665 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.6084 on 45 degrees of freedom
Multiple R-squared: 0.9906, Adjusted R-squared: 0.9881
F-statistic: 395.1 on 12 and 45 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)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.057706321 0.115412642 0.9422937
[2,] 0.019739303 0.039478605 0.9802607
[3,] 0.005350631 0.010701263 0.9946494
[4,] 0.004268996 0.008537992 0.9957310
[5,] 0.101377248 0.202754496 0.8986228
[6,] 0.193496469 0.386992938 0.8065035
[7,] 0.235644735 0.471289471 0.7643553
[8,] 0.260027383 0.520054766 0.7399726
[9,] 0.459618448 0.919236895 0.5403816
[10,] 0.364204098 0.728408196 0.6357959
[11,] 0.272759828 0.545519657 0.7272402
[12,] 0.192915890 0.385831780 0.8070841
[13,] 0.133282102 0.266564203 0.8667179
[14,] 0.087544387 0.175088773 0.9124556
[15,] 0.073584559 0.147169117 0.9264154
[16,] 0.061271736 0.122543472 0.9387283
[17,] 0.061846277 0.123692555 0.9381537
[18,] 0.124886854 0.249773708 0.8751131
[19,] 0.191697033 0.383394066 0.8083030
[20,] 0.293236428 0.586472856 0.7067636
[21,] 0.347076714 0.694153429 0.6529233
[22,] 0.415023206 0.830046412 0.5849768
[23,] 0.481716329 0.963432659 0.5182837
[24,] 0.554444444 0.891111113 0.4455556
[25,] 0.612593155 0.774813690 0.3874068
[26,] 0.743354510 0.513290981 0.2566455
[27,] 0.698178696 0.603642607 0.3018213
> postscript(file="/var/www/rcomp/tmp/119ka1322606267.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/208301322606267.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/3ks0j1322606267.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/4cg8a1322606267.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5zzms1322606267.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 58
Frequency = 1
1 2 3 4 5 6
0.84645455 1.07445455 1.02045455 0.98445455 0.95245455 0.66445455
7 8 9 10 11 12
0.52645455 0.21445455 -0.05554545 -0.17954545 -0.17465909 -0.27215909
13 14 15 16 17 18
-0.10877273 -0.36077273 -0.25477273 -0.18077273 -0.21277273 -0.55077273
19 20 21 22 23 24
-0.40877273 -0.12077273 -0.37077273 -0.48477273 -0.40988636 -0.04738636
25 26 27 28 29 30
-0.62400000 -0.66600000 -0.73000000 -0.83600000 -0.83800000 -0.89600000
31 32 33 34 35 36
-0.80400000 -0.85600000 -0.25600000 -0.34000000 -0.14511364 -0.30261364
37 38 39 40 41 42
-0.51922727 -0.40122727 -0.33522727 -0.21122727 -0.16322727 0.49877273
43 44 45 46 47 48
0.31077273 0.46877273 0.75877273 0.95477273 0.72965909 0.62215909
49 50 51 52 53 54
0.40554545 0.35354545 0.29954545 0.24354545 0.26154545 0.28354545
55 56 57 58
0.37554545 0.29354545 -0.07645455 0.04954545
> postscript(file="/var/www/rcomp/tmp/6u3lh1322606267.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 = 58
Frequency = 1
lag(myerror, k = 1) myerror
0 0.84645455 NA
1 1.07445455 0.84645455
2 1.02045455 1.07445455
3 0.98445455 1.02045455
4 0.95245455 0.98445455
5 0.66445455 0.95245455
6 0.52645455 0.66445455
7 0.21445455 0.52645455
8 -0.05554545 0.21445455
9 -0.17954545 -0.05554545
10 -0.17465909 -0.17954545
11 -0.27215909 -0.17465909
12 -0.10877273 -0.27215909
13 -0.36077273 -0.10877273
14 -0.25477273 -0.36077273
15 -0.18077273 -0.25477273
16 -0.21277273 -0.18077273
17 -0.55077273 -0.21277273
18 -0.40877273 -0.55077273
19 -0.12077273 -0.40877273
20 -0.37077273 -0.12077273
21 -0.48477273 -0.37077273
22 -0.40988636 -0.48477273
23 -0.04738636 -0.40988636
24 -0.62400000 -0.04738636
25 -0.66600000 -0.62400000
26 -0.73000000 -0.66600000
27 -0.83600000 -0.73000000
28 -0.83800000 -0.83600000
29 -0.89600000 -0.83800000
30 -0.80400000 -0.89600000
31 -0.85600000 -0.80400000
32 -0.25600000 -0.85600000
33 -0.34000000 -0.25600000
34 -0.14511364 -0.34000000
35 -0.30261364 -0.14511364
36 -0.51922727 -0.30261364
37 -0.40122727 -0.51922727
38 -0.33522727 -0.40122727
39 -0.21122727 -0.33522727
40 -0.16322727 -0.21122727
41 0.49877273 -0.16322727
42 0.31077273 0.49877273
43 0.46877273 0.31077273
44 0.75877273 0.46877273
45 0.95477273 0.75877273
46 0.72965909 0.95477273
47 0.62215909 0.72965909
48 0.40554545 0.62215909
49 0.35354545 0.40554545
50 0.29954545 0.35354545
51 0.24354545 0.29954545
52 0.26154545 0.24354545
53 0.28354545 0.26154545
54 0.37554545 0.28354545
55 0.29354545 0.37554545
56 -0.07645455 0.29354545
57 0.04954545 -0.07645455
58 NA 0.04954545
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.07445455 0.84645455
[2,] 1.02045455 1.07445455
[3,] 0.98445455 1.02045455
[4,] 0.95245455 0.98445455
[5,] 0.66445455 0.95245455
[6,] 0.52645455 0.66445455
[7,] 0.21445455 0.52645455
[8,] -0.05554545 0.21445455
[9,] -0.17954545 -0.05554545
[10,] -0.17465909 -0.17954545
[11,] -0.27215909 -0.17465909
[12,] -0.10877273 -0.27215909
[13,] -0.36077273 -0.10877273
[14,] -0.25477273 -0.36077273
[15,] -0.18077273 -0.25477273
[16,] -0.21277273 -0.18077273
[17,] -0.55077273 -0.21277273
[18,] -0.40877273 -0.55077273
[19,] -0.12077273 -0.40877273
[20,] -0.37077273 -0.12077273
[21,] -0.48477273 -0.37077273
[22,] -0.40988636 -0.48477273
[23,] -0.04738636 -0.40988636
[24,] -0.62400000 -0.04738636
[25,] -0.66600000 -0.62400000
[26,] -0.73000000 -0.66600000
[27,] -0.83600000 -0.73000000
[28,] -0.83800000 -0.83600000
[29,] -0.89600000 -0.83800000
[30,] -0.80400000 -0.89600000
[31,] -0.85600000 -0.80400000
[32,] -0.25600000 -0.85600000
[33,] -0.34000000 -0.25600000
[34,] -0.14511364 -0.34000000
[35,] -0.30261364 -0.14511364
[36,] -0.51922727 -0.30261364
[37,] -0.40122727 -0.51922727
[38,] -0.33522727 -0.40122727
[39,] -0.21122727 -0.33522727
[40,] -0.16322727 -0.21122727
[41,] 0.49877273 -0.16322727
[42,] 0.31077273 0.49877273
[43,] 0.46877273 0.31077273
[44,] 0.75877273 0.46877273
[45,] 0.95477273 0.75877273
[46,] 0.72965909 0.95477273
[47,] 0.62215909 0.72965909
[48,] 0.40554545 0.62215909
[49,] 0.35354545 0.40554545
[50,] 0.29954545 0.35354545
[51,] 0.24354545 0.29954545
[52,] 0.26154545 0.24354545
[53,] 0.28354545 0.26154545
[54,] 0.37554545 0.28354545
[55,] 0.29354545 0.37554545
[56,] -0.07645455 0.29354545
[57,] 0.04954545 -0.07645455
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.07445455 0.84645455
2 1.02045455 1.07445455
3 0.98445455 1.02045455
4 0.95245455 0.98445455
5 0.66445455 0.95245455
6 0.52645455 0.66445455
7 0.21445455 0.52645455
8 -0.05554545 0.21445455
9 -0.17954545 -0.05554545
10 -0.17465909 -0.17954545
11 -0.27215909 -0.17465909
12 -0.10877273 -0.27215909
13 -0.36077273 -0.10877273
14 -0.25477273 -0.36077273
15 -0.18077273 -0.25477273
16 -0.21277273 -0.18077273
17 -0.55077273 -0.21277273
18 -0.40877273 -0.55077273
19 -0.12077273 -0.40877273
20 -0.37077273 -0.12077273
21 -0.48477273 -0.37077273
22 -0.40988636 -0.48477273
23 -0.04738636 -0.40988636
24 -0.62400000 -0.04738636
25 -0.66600000 -0.62400000
26 -0.73000000 -0.66600000
27 -0.83600000 -0.73000000
28 -0.83800000 -0.83600000
29 -0.89600000 -0.83800000
30 -0.80400000 -0.89600000
31 -0.85600000 -0.80400000
32 -0.25600000 -0.85600000
33 -0.34000000 -0.25600000
34 -0.14511364 -0.34000000
35 -0.30261364 -0.14511364
36 -0.51922727 -0.30261364
37 -0.40122727 -0.51922727
38 -0.33522727 -0.40122727
39 -0.21122727 -0.33522727
40 -0.16322727 -0.21122727
41 0.49877273 -0.16322727
42 0.31077273 0.49877273
43 0.46877273 0.31077273
44 0.75877273 0.46877273
45 0.95477273 0.75877273
46 0.72965909 0.95477273
47 0.62215909 0.72965909
48 0.40554545 0.62215909
49 0.35354545 0.40554545
50 0.29954545 0.35354545
51 0.24354545 0.29954545
52 0.26154545 0.24354545
53 0.28354545 0.26154545
54 0.37554545 0.28354545
55 0.29354545 0.37554545
56 -0.07645455 0.29354545
57 0.04954545 -0.07645455
> 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/7arpw1322606267.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/8kgjm1322606267.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/9p3wq1322606267.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/10c0qw1322606267.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/11sqg51322606267.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/127og61322606267.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/13o2zj1322606267.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/146l1g1322606267.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/15cqcx1322606267.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/167vkw1322606267.tab")
+ }
>
> try(system("convert tmp/119ka1322606267.ps tmp/119ka1322606267.png",intern=TRUE))
character(0)
> try(system("convert tmp/208301322606267.ps tmp/208301322606267.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ks0j1322606267.ps tmp/3ks0j1322606267.png",intern=TRUE))
character(0)
> try(system("convert tmp/4cg8a1322606267.ps tmp/4cg8a1322606267.png",intern=TRUE))
character(0)
> try(system("convert tmp/5zzms1322606267.ps tmp/5zzms1322606267.png",intern=TRUE))
character(0)
> try(system("convert tmp/6u3lh1322606267.ps tmp/6u3lh1322606267.png",intern=TRUE))
character(0)
> try(system("convert tmp/7arpw1322606267.ps tmp/7arpw1322606267.png",intern=TRUE))
character(0)
> try(system("convert tmp/8kgjm1322606267.ps tmp/8kgjm1322606267.png",intern=TRUE))
character(0)
> try(system("convert tmp/9p3wq1322606267.ps tmp/9p3wq1322606267.png",intern=TRUE))
character(0)
> try(system("convert tmp/10c0qw1322606267.ps tmp/10c0qw1322606267.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.072 0.748 4.800