R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(104.37,104.89,105.15,105.72,106.38,106.40,106.47,106.59,106.76,107.35,107.81,108.03,109.08,109.86,110.29,110.34,110.59,110.64,110.83,111.51,113.32,115.89,116.51,117.44,118.25,118.65,118.52,119.07,119.12,119.28,119.30,119.44,119.57,119.93,120.03,119.66,119.46,119.48,119.56,119.43,119.57,119.59,119.50,119.54,119.56,119.61,119.64,119.60,119.71,119.72,119.66,119.76,119.80,119.88,119.78,120.08,120.22),dim=c(1,57),dimnames=list(c('Broodprijs'),1:57))
> y <- array(NA,dim=c(1,57),dimnames=list(c('Broodprijs'),1:57))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'Linear Trend'
> par2 = 'Include Monthly 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
Broodprijs M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 104.37 1 0 0 0 0 0 0 0 0 0 0 1
2 104.89 0 1 0 0 0 0 0 0 0 0 0 2
3 105.15 0 0 1 0 0 0 0 0 0 0 0 3
4 105.72 0 0 0 1 0 0 0 0 0 0 0 4
5 106.38 0 0 0 0 1 0 0 0 0 0 0 5
6 106.40 0 0 0 0 0 1 0 0 0 0 0 6
7 106.47 0 0 0 0 0 0 1 0 0 0 0 7
8 106.59 0 0 0 0 0 0 0 1 0 0 0 8
9 106.76 0 0 0 0 0 0 0 0 1 0 0 9
10 107.35 0 0 0 0 0 0 0 0 0 1 0 10
11 107.81 0 0 0 0 0 0 0 0 0 0 1 11
12 108.03 0 0 0 0 0 0 0 0 0 0 0 12
13 109.08 1 0 0 0 0 0 0 0 0 0 0 13
14 109.86 0 1 0 0 0 0 0 0 0 0 0 14
15 110.29 0 0 1 0 0 0 0 0 0 0 0 15
16 110.34 0 0 0 1 0 0 0 0 0 0 0 16
17 110.59 0 0 0 0 1 0 0 0 0 0 0 17
18 110.64 0 0 0 0 0 1 0 0 0 0 0 18
19 110.83 0 0 0 0 0 0 1 0 0 0 0 19
20 111.51 0 0 0 0 0 0 0 1 0 0 0 20
21 113.32 0 0 0 0 0 0 0 0 1 0 0 21
22 115.89 0 0 0 0 0 0 0 0 0 1 0 22
23 116.51 0 0 0 0 0 0 0 0 0 0 1 23
24 117.44 0 0 0 0 0 0 0 0 0 0 0 24
25 118.25 1 0 0 0 0 0 0 0 0 0 0 25
26 118.65 0 1 0 0 0 0 0 0 0 0 0 26
27 118.52 0 0 1 0 0 0 0 0 0 0 0 27
28 119.07 0 0 0 1 0 0 0 0 0 0 0 28
29 119.12 0 0 0 0 1 0 0 0 0 0 0 29
30 119.28 0 0 0 0 0 1 0 0 0 0 0 30
31 119.30 0 0 0 0 0 0 1 0 0 0 0 31
32 119.44 0 0 0 0 0 0 0 1 0 0 0 32
33 119.57 0 0 0 0 0 0 0 0 1 0 0 33
34 119.93 0 0 0 0 0 0 0 0 0 1 0 34
35 120.03 0 0 0 0 0 0 0 0 0 0 1 35
36 119.66 0 0 0 0 0 0 0 0 0 0 0 36
37 119.46 1 0 0 0 0 0 0 0 0 0 0 37
38 119.48 0 1 0 0 0 0 0 0 0 0 0 38
39 119.56 0 0 1 0 0 0 0 0 0 0 0 39
40 119.43 0 0 0 1 0 0 0 0 0 0 0 40
41 119.57 0 0 0 0 1 0 0 0 0 0 0 41
42 119.59 0 0 0 0 0 1 0 0 0 0 0 42
43 119.50 0 0 0 0 0 0 1 0 0 0 0 43
44 119.54 0 0 0 0 0 0 0 1 0 0 0 44
45 119.56 0 0 0 0 0 0 0 0 1 0 0 45
46 119.61 0 0 0 0 0 0 0 0 0 1 0 46
47 119.64 0 0 0 0 0 0 0 0 0 0 1 47
48 119.60 0 0 0 0 0 0 0 0 0 0 0 48
49 119.71 1 0 0 0 0 0 0 0 0 0 0 49
50 119.72 0 1 0 0 0 0 0 0 0 0 0 50
51 119.66 0 0 1 0 0 0 0 0 0 0 0 51
52 119.76 0 0 0 1 0 0 0 0 0 0 0 52
53 119.80 0 0 0 0 1 0 0 0 0 0 0 53
54 119.88 0 0 0 0 0 1 0 0 0 0 0 54
55 119.78 0 0 0 0 0 0 1 0 0 0 0 55
56 120.08 0 0 0 0 0 0 0 1 0 0 0 56
57 120.22 0 0 0 0 0 0 0 0 1 0 0 57
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) M1 M2 M3 M4 M5
106.9118 -0.4634 -0.4264 -0.6194 -0.7005 -0.7815
M6 M7 M8 M9 M10 M11
-1.0245 -1.3155 -1.3685 -1.2236 0.1305 0.1240
t
0.3090
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-3.0826 -2.0694 -0.7937 1.6234 4.2060
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 106.91179 1.48672 71.911 <2e-16 ***
M1 -0.46338 1.79591 -0.258 0.798
M2 -0.42640 1.79473 -0.238 0.813
M3 -0.61943 1.79381 -0.345 0.732
M4 -0.70045 1.79315 -0.391 0.698
M5 -0.78148 1.79275 -0.436 0.665
M6 -1.02450 1.79262 -0.572 0.571
M7 -1.31552 1.79275 -0.734 0.467
M8 -1.36855 1.79315 -0.763 0.449
M9 -1.22357 1.79381 -0.682 0.499
M10 0.13055 1.89009 0.069 0.945
M11 0.12402 1.88972 0.066 0.948
t 0.30902 0.02173 14.220 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.672 on 44 degrees of freedom
Multiple R-squared: 0.8233, Adjusted R-squared: 0.7751
F-statistic: 17.08 on 12 and 44 DF, p-value: 8.832e-13
> 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,] 0.0007117584 1.423517e-03 9.992882e-01
[2,] 0.0005487511 1.097502e-03 9.994512e-01
[3,] 0.0002408235 4.816470e-04 9.997592e-01
[4,] 0.0001203519 2.407038e-04 9.998796e-01
[5,] 0.0002016795 4.033590e-04 9.997983e-01
[6,] 0.1159643278 2.319287e-01 8.840357e-01
[7,] 0.9677391569 6.452169e-02 3.226084e-02
[8,] 0.9999843533 3.129335e-05 1.564667e-05
[9,] 0.9999999963 7.386137e-09 3.693068e-09
[10,] 0.9999999998 3.783378e-10 1.891689e-10
[11,] 0.9999999999 2.922552e-10 1.461276e-10
[12,] 1.0000000000 4.880490e-11 2.440245e-11
[13,] 0.9999999999 2.304655e-10 1.152328e-10
[14,] 0.9999999995 1.016734e-09 5.083669e-10
[15,] 0.9999999971 5.742749e-09 2.871375e-09
[16,] 0.9999999812 3.758430e-08 1.879215e-08
[17,] 0.9999998848 2.303223e-07 1.151611e-07
[18,] 0.9999993404 1.319199e-06 6.595996e-07
[19,] 0.9999993513 1.297375e-06 6.486877e-07
[20,] 0.9999998979 2.041538e-07 1.020769e-07
[21,] 0.9999999124 1.752510e-07 8.762550e-08
[22,] 0.9999996088 7.823805e-07 3.911903e-07
[23,] 0.9999977932 4.413628e-06 2.206814e-06
[24,] 0.9999930033 1.399346e-05 6.996728e-06
[25,] 0.9999274761 1.450478e-04 7.252389e-05
[26,] 0.9994456118 1.108776e-03 5.543882e-04
> postscript(file="/var/www/html/rcomp/tmp/1c8e61292352578.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2c8e61292352578.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/html/rcomp/tmp/3c8e61292352578.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4mzv91292352578.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5mzv91292352578.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 = 57
Frequency = 1
1 2 3 4 5 6
-2.38742857 -2.21342857 -2.06942857 -1.72742857 -1.29542857 -1.34142857
7 8 9 10 11 12
-1.28942857 -1.42542857 -1.70942857 -2.78257143 -2.62507143 -2.59007143
13 14 15 16 17 18
-1.38571429 -0.95171429 -0.63771429 -0.81571429 -0.79371429 -0.80971429
19 20 21 22 23 24
-0.63771429 -0.21371429 1.14228571 2.04914286 2.36664286 3.11164286
25 26 27 28 29 30
4.07600000 4.13000000 3.88400000 4.20600000 4.02800000 4.12200000
31 32 33 34 35 36
4.12400000 4.00800000 3.68400000 2.38085714 2.17835714 1.62335714
37 38 39 40 41 42
1.57771429 1.25171429 1.21571429 0.85771429 0.76971429 0.72371429
43 44 45 46 47 48
0.61571429 0.39971429 -0.03428571 -1.64742857 -1.91992857 -2.14492857
49 50 51 52 53 54
-1.88057143 -2.21657143 -2.39257143 -2.52057143 -2.70857143 -2.69457143
55 56 57
-2.81257143 -2.76857143 -3.08257143
> postscript(file="/var/www/html/rcomp/tmp/6mzv91292352578.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 = 57
Frequency = 1
lag(myerror, k = 1) myerror
0 -2.38742857 NA
1 -2.21342857 -2.38742857
2 -2.06942857 -2.21342857
3 -1.72742857 -2.06942857
4 -1.29542857 -1.72742857
5 -1.34142857 -1.29542857
6 -1.28942857 -1.34142857
7 -1.42542857 -1.28942857
8 -1.70942857 -1.42542857
9 -2.78257143 -1.70942857
10 -2.62507143 -2.78257143
11 -2.59007143 -2.62507143
12 -1.38571429 -2.59007143
13 -0.95171429 -1.38571429
14 -0.63771429 -0.95171429
15 -0.81571429 -0.63771429
16 -0.79371429 -0.81571429
17 -0.80971429 -0.79371429
18 -0.63771429 -0.80971429
19 -0.21371429 -0.63771429
20 1.14228571 -0.21371429
21 2.04914286 1.14228571
22 2.36664286 2.04914286
23 3.11164286 2.36664286
24 4.07600000 3.11164286
25 4.13000000 4.07600000
26 3.88400000 4.13000000
27 4.20600000 3.88400000
28 4.02800000 4.20600000
29 4.12200000 4.02800000
30 4.12400000 4.12200000
31 4.00800000 4.12400000
32 3.68400000 4.00800000
33 2.38085714 3.68400000
34 2.17835714 2.38085714
35 1.62335714 2.17835714
36 1.57771429 1.62335714
37 1.25171429 1.57771429
38 1.21571429 1.25171429
39 0.85771429 1.21571429
40 0.76971429 0.85771429
41 0.72371429 0.76971429
42 0.61571429 0.72371429
43 0.39971429 0.61571429
44 -0.03428571 0.39971429
45 -1.64742857 -0.03428571
46 -1.91992857 -1.64742857
47 -2.14492857 -1.91992857
48 -1.88057143 -2.14492857
49 -2.21657143 -1.88057143
50 -2.39257143 -2.21657143
51 -2.52057143 -2.39257143
52 -2.70857143 -2.52057143
53 -2.69457143 -2.70857143
54 -2.81257143 -2.69457143
55 -2.76857143 -2.81257143
56 -3.08257143 -2.76857143
57 NA -3.08257143
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -2.21342857 -2.38742857
[2,] -2.06942857 -2.21342857
[3,] -1.72742857 -2.06942857
[4,] -1.29542857 -1.72742857
[5,] -1.34142857 -1.29542857
[6,] -1.28942857 -1.34142857
[7,] -1.42542857 -1.28942857
[8,] -1.70942857 -1.42542857
[9,] -2.78257143 -1.70942857
[10,] -2.62507143 -2.78257143
[11,] -2.59007143 -2.62507143
[12,] -1.38571429 -2.59007143
[13,] -0.95171429 -1.38571429
[14,] -0.63771429 -0.95171429
[15,] -0.81571429 -0.63771429
[16,] -0.79371429 -0.81571429
[17,] -0.80971429 -0.79371429
[18,] -0.63771429 -0.80971429
[19,] -0.21371429 -0.63771429
[20,] 1.14228571 -0.21371429
[21,] 2.04914286 1.14228571
[22,] 2.36664286 2.04914286
[23,] 3.11164286 2.36664286
[24,] 4.07600000 3.11164286
[25,] 4.13000000 4.07600000
[26,] 3.88400000 4.13000000
[27,] 4.20600000 3.88400000
[28,] 4.02800000 4.20600000
[29,] 4.12200000 4.02800000
[30,] 4.12400000 4.12200000
[31,] 4.00800000 4.12400000
[32,] 3.68400000 4.00800000
[33,] 2.38085714 3.68400000
[34,] 2.17835714 2.38085714
[35,] 1.62335714 2.17835714
[36,] 1.57771429 1.62335714
[37,] 1.25171429 1.57771429
[38,] 1.21571429 1.25171429
[39,] 0.85771429 1.21571429
[40,] 0.76971429 0.85771429
[41,] 0.72371429 0.76971429
[42,] 0.61571429 0.72371429
[43,] 0.39971429 0.61571429
[44,] -0.03428571 0.39971429
[45,] -1.64742857 -0.03428571
[46,] -1.91992857 -1.64742857
[47,] -2.14492857 -1.91992857
[48,] -1.88057143 -2.14492857
[49,] -2.21657143 -1.88057143
[50,] -2.39257143 -2.21657143
[51,] -2.52057143 -2.39257143
[52,] -2.70857143 -2.52057143
[53,] -2.69457143 -2.70857143
[54,] -2.81257143 -2.69457143
[55,] -2.76857143 -2.81257143
[56,] -3.08257143 -2.76857143
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -2.21342857 -2.38742857
2 -2.06942857 -2.21342857
3 -1.72742857 -2.06942857
4 -1.29542857 -1.72742857
5 -1.34142857 -1.29542857
6 -1.28942857 -1.34142857
7 -1.42542857 -1.28942857
8 -1.70942857 -1.42542857
9 -2.78257143 -1.70942857
10 -2.62507143 -2.78257143
11 -2.59007143 -2.62507143
12 -1.38571429 -2.59007143
13 -0.95171429 -1.38571429
14 -0.63771429 -0.95171429
15 -0.81571429 -0.63771429
16 -0.79371429 -0.81571429
17 -0.80971429 -0.79371429
18 -0.63771429 -0.80971429
19 -0.21371429 -0.63771429
20 1.14228571 -0.21371429
21 2.04914286 1.14228571
22 2.36664286 2.04914286
23 3.11164286 2.36664286
24 4.07600000 3.11164286
25 4.13000000 4.07600000
26 3.88400000 4.13000000
27 4.20600000 3.88400000
28 4.02800000 4.20600000
29 4.12200000 4.02800000
30 4.12400000 4.12200000
31 4.00800000 4.12400000
32 3.68400000 4.00800000
33 2.38085714 3.68400000
34 2.17835714 2.38085714
35 1.62335714 2.17835714
36 1.57771429 1.62335714
37 1.25171429 1.57771429
38 1.21571429 1.25171429
39 0.85771429 1.21571429
40 0.76971429 0.85771429
41 0.72371429 0.76971429
42 0.61571429 0.72371429
43 0.39971429 0.61571429
44 -0.03428571 0.39971429
45 -1.64742857 -0.03428571
46 -1.91992857 -1.64742857
47 -2.14492857 -1.91992857
48 -1.88057143 -2.14492857
49 -2.21657143 -1.88057143
50 -2.39257143 -2.21657143
51 -2.52057143 -2.39257143
52 -2.70857143 -2.52057143
53 -2.69457143 -2.70857143
54 -2.81257143 -2.69457143
55 -2.76857143 -2.81257143
56 -3.08257143 -2.76857143
> 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/7x8du1292352578.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8piux1292352578.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9piux1292352578.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10piux1292352578.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11lran1292352578.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/127aqb1292352578.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/133k621292352578.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/14wbn51292352578.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/15zu4t1292352578.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/16dl1k1292352578.tab")
+ }
>
> try(system("convert tmp/1c8e61292352578.ps tmp/1c8e61292352578.png",intern=TRUE))
character(0)
> try(system("convert tmp/2c8e61292352578.ps tmp/2c8e61292352578.png",intern=TRUE))
character(0)
> try(system("convert tmp/3c8e61292352578.ps tmp/3c8e61292352578.png",intern=TRUE))
character(0)
> try(system("convert tmp/4mzv91292352578.ps tmp/4mzv91292352578.png",intern=TRUE))
character(0)
> try(system("convert tmp/5mzv91292352578.ps tmp/5mzv91292352578.png",intern=TRUE))
character(0)
> try(system("convert tmp/6mzv91292352578.ps tmp/6mzv91292352578.png",intern=TRUE))
character(0)
> try(system("convert tmp/7x8du1292352578.ps tmp/7x8du1292352578.png",intern=TRUE))
character(0)
> try(system("convert tmp/8piux1292352578.ps tmp/8piux1292352578.png",intern=TRUE))
character(0)
> try(system("convert tmp/9piux1292352578.ps tmp/9piux1292352578.png",intern=TRUE))
character(0)
> try(system("convert tmp/10piux1292352578.ps tmp/10piux1292352578.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.396 1.599 5.926