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(1.43,0.51,1.43,0.51,1.43,0.51,1.43,0.51,1.43,0.52,1.43,0.52,1.44,0.52,1.48,0.53,1.48,0.53,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.52,1.48,0.53,1.48,0.53,1.48,0.53,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.54,1.48,0.53,1.48,0.53,1.48,0.53,1.48,0.53,1.48,0.53,1.57,0.54,1.58,0.55,1.58,0.55,1.58,0.55,1.58,0.55,1.59,0.55,1.6,0.55,1.6,0.55,1.61,0.55,1.61,0.56,1.61,0.56,1.62,0.56,1.63,0.56,1.63,0.56,1.64,0.55,1.64,0.56,1.64,0.55,1.64,0.55,1.64,0.56,1.65,0.55,1.65,0.55,1.65,0.55,1.65,0.55),dim=c(2,60),dimnames=list(c('Broodprijs','Bakmeelprijs'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Broodprijs','Bakmeelprijs'),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 = '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
Broodprijs Bakmeelprijs t
1 1.43 0.51 1
2 1.43 0.51 2
3 1.43 0.51 3
4 1.43 0.51 4
5 1.43 0.52 5
6 1.43 0.52 6
7 1.44 0.52 7
8 1.48 0.53 8
9 1.48 0.53 9
10 1.48 0.52 10
11 1.48 0.52 11
12 1.48 0.52 12
13 1.48 0.52 13
14 1.48 0.52 14
15 1.48 0.52 15
16 1.48 0.52 16
17 1.48 0.52 17
18 1.48 0.52 18
19 1.48 0.52 19
20 1.48 0.53 20
21 1.48 0.53 21
22 1.48 0.53 22
23 1.48 0.54 23
24 1.48 0.54 24
25 1.48 0.54 25
26 1.48 0.54 26
27 1.48 0.54 27
28 1.48 0.54 28
29 1.48 0.54 29
30 1.48 0.54 30
31 1.48 0.54 31
32 1.48 0.54 32
33 1.48 0.53 33
34 1.48 0.53 34
35 1.48 0.53 35
36 1.48 0.53 36
37 1.48 0.53 37
38 1.57 0.54 38
39 1.58 0.55 39
40 1.58 0.55 40
41 1.58 0.55 41
42 1.58 0.55 42
43 1.59 0.55 43
44 1.60 0.55 44
45 1.60 0.55 45
46 1.61 0.55 46
47 1.61 0.56 47
48 1.61 0.56 48
49 1.62 0.56 49
50 1.63 0.56 50
51 1.63 0.56 51
52 1.64 0.55 52
53 1.64 0.56 53
54 1.64 0.55 54
55 1.64 0.55 55
56 1.64 0.56 56
57 1.65 0.55 57
58 1.65 0.55 58
59 1.65 0.55 59
60 1.65 0.55 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Bakmeelprijs t
0.864897 1.054890 0.003136
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.06001 -0.01639 0.01042 0.02010 0.03520
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.8648973 0.3008914 2.874 0.00568 **
Bakmeelprijs 1.0548898 0.5864515 1.799 0.07735 .
t 0.0031356 0.0005079 6.173 7.47e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.02889 on 57 degrees of freedom
Multiple R-squared: 0.8571, Adjusted R-squared: 0.8521
F-statistic: 170.9 on 2 and 57 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,] 3.253350e-43 6.506700e-43 1.000000e+00
[2,] 4.259567e-04 8.519134e-04 9.995740e-01
[3,] 2.783022e-02 5.566045e-02 9.721698e-01
[4,] 1.909243e-02 3.818486e-02 9.809076e-01
[5,] 2.498965e-02 4.997930e-02 9.750103e-01
[6,] 1.358153e-02 2.716306e-02 9.864185e-01
[7,] 7.235415e-03 1.447083e-02 9.927646e-01
[8,] 4.254144e-03 8.508287e-03 9.957459e-01
[9,] 2.893481e-03 5.786961e-03 9.971065e-01
[10,] 2.334189e-03 4.668378e-03 9.976658e-01
[11,] 2.286625e-03 4.573249e-03 9.977134e-01
[12,] 2.833426e-03 5.666853e-03 9.971666e-01
[13,] 4.835820e-03 9.671640e-03 9.951642e-01
[14,] 1.371554e-02 2.743108e-02 9.862845e-01
[15,] 5.410101e-02 1.082020e-01 9.458990e-01
[16,] 1.413981e-01 2.827963e-01 8.586019e-01
[17,] 3.163343e-01 6.326685e-01 6.836657e-01
[18,] 4.118944e-01 8.237888e-01 5.881056e-01
[19,] 4.452376e-01 8.904751e-01 5.547624e-01
[20,] 4.484415e-01 8.968830e-01 5.515585e-01
[21,] 4.332662e-01 8.665323e-01 5.667338e-01
[22,] 4.066421e-01 8.132842e-01 5.933579e-01
[23,] 3.750629e-01 7.501258e-01 6.249371e-01
[24,] 3.460387e-01 6.920773e-01 6.539613e-01
[25,] 3.289633e-01 6.579266e-01 6.710367e-01
[26,] 3.376812e-01 6.753624e-01 6.623188e-01
[27,] 3.995727e-01 7.991454e-01 6.004273e-01
[28,] 3.606188e-01 7.212377e-01 6.393812e-01
[29,] 3.312335e-01 6.624670e-01 6.687665e-01
[30,] 3.425406e-01 6.850811e-01 6.574594e-01
[31,] 5.044390e-01 9.911221e-01 4.955610e-01
[32,] 9.999820e-01 3.600028e-05 1.800014e-05
[33,] 9.999995e-01 1.034278e-06 5.171392e-07
[34,] 9.999999e-01 2.415013e-07 1.207507e-07
[35,] 9.999999e-01 2.290489e-07 1.145244e-07
[36,] 9.999999e-01 2.811248e-07 1.405624e-07
[37,] 9.999999e-01 1.250069e-07 6.250346e-08
[38,] 9.999999e-01 1.443921e-07 7.219605e-08
[39,] 9.999998e-01 3.735378e-07 1.867689e-07
[40,] 9.999998e-01 4.768891e-07 2.384445e-07
[41,] 9.999994e-01 1.232382e-06 6.161912e-07
[42,] 9.999986e-01 2.827275e-06 1.413637e-06
[43,] 9.999998e-01 3.971938e-07 1.985969e-07
[44,] 9.999999e-01 2.043811e-07 1.021906e-07
[45,] 9.999991e-01 1.891610e-06 9.458050e-07
[46,] 9.999957e-01 8.645102e-06 4.322551e-06
[47,] 9.999661e-01 6.787844e-05 3.393922e-05
[48,] 9.998593e-01 2.814971e-04 1.407486e-04
[49,] 9.984721e-01 3.055844e-03 1.527922e-03
> postscript(file="/var/www/html/rcomp/tmp/1dmys1258714571.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/23r091258714571.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3z2ti1258714571.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4dcpg1258714571.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5v1os1258714571.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
0.0239732543 0.0208376483 0.0177020423 0.0145664363 0.0008819319
6 7 8 9 10
-0.0022536741 0.0046107199 0.0309262155 0.0277906095 0.0352039019
11 12 13 14 15
0.0320682959 0.0289326899 0.0257970839 0.0226614779 0.0195258719
16 17 18 19 20
0.0163902659 0.0132546599 0.0101190539 0.0069834479 -0.0067010565
21 22 23 24 25
-0.0098366625 -0.0129722685 -0.0266567729 -0.0297923789 -0.0329279848
26 27 28 29 30
-0.0360635908 -0.0391991968 -0.0423348028 -0.0454704088 -0.0486060148
31 32 33 34 35
-0.0517416208 -0.0548772268 -0.0474639344 -0.0505995404 -0.0537351464
36 37 38 39 40
-0.0568707524 -0.0600063584 0.0163091372 0.0126246328 0.0094890268
41 42 43 44 45
0.0063534208 0.0032178148 0.0100822088 0.0169466028 0.0138109968
46 47 48 49 50
0.0206753908 0.0069908864 0.0038552804 0.0107196744 0.0175840684
51 52 53 54 55
0.0144484624 0.0318617548 0.0181772504 0.0255905429 0.0224549369
56 57 58 59 60
0.0087704325 0.0261837249 0.0230481189 0.0199125129 0.0167769069
> postscript(file="/var/www/html/rcomp/tmp/63wk41258714571.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 0.0239732543 NA
1 0.0208376483 0.0239732543
2 0.0177020423 0.0208376483
3 0.0145664363 0.0177020423
4 0.0008819319 0.0145664363
5 -0.0022536741 0.0008819319
6 0.0046107199 -0.0022536741
7 0.0309262155 0.0046107199
8 0.0277906095 0.0309262155
9 0.0352039019 0.0277906095
10 0.0320682959 0.0352039019
11 0.0289326899 0.0320682959
12 0.0257970839 0.0289326899
13 0.0226614779 0.0257970839
14 0.0195258719 0.0226614779
15 0.0163902659 0.0195258719
16 0.0132546599 0.0163902659
17 0.0101190539 0.0132546599
18 0.0069834479 0.0101190539
19 -0.0067010565 0.0069834479
20 -0.0098366625 -0.0067010565
21 -0.0129722685 -0.0098366625
22 -0.0266567729 -0.0129722685
23 -0.0297923789 -0.0266567729
24 -0.0329279848 -0.0297923789
25 -0.0360635908 -0.0329279848
26 -0.0391991968 -0.0360635908
27 -0.0423348028 -0.0391991968
28 -0.0454704088 -0.0423348028
29 -0.0486060148 -0.0454704088
30 -0.0517416208 -0.0486060148
31 -0.0548772268 -0.0517416208
32 -0.0474639344 -0.0548772268
33 -0.0505995404 -0.0474639344
34 -0.0537351464 -0.0505995404
35 -0.0568707524 -0.0537351464
36 -0.0600063584 -0.0568707524
37 0.0163091372 -0.0600063584
38 0.0126246328 0.0163091372
39 0.0094890268 0.0126246328
40 0.0063534208 0.0094890268
41 0.0032178148 0.0063534208
42 0.0100822088 0.0032178148
43 0.0169466028 0.0100822088
44 0.0138109968 0.0169466028
45 0.0206753908 0.0138109968
46 0.0069908864 0.0206753908
47 0.0038552804 0.0069908864
48 0.0107196744 0.0038552804
49 0.0175840684 0.0107196744
50 0.0144484624 0.0175840684
51 0.0318617548 0.0144484624
52 0.0181772504 0.0318617548
53 0.0255905429 0.0181772504
54 0.0224549369 0.0255905429
55 0.0087704325 0.0224549369
56 0.0261837249 0.0087704325
57 0.0230481189 0.0261837249
58 0.0199125129 0.0230481189
59 0.0167769069 0.0199125129
60 NA 0.0167769069
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.0208376483 0.0239732543
[2,] 0.0177020423 0.0208376483
[3,] 0.0145664363 0.0177020423
[4,] 0.0008819319 0.0145664363
[5,] -0.0022536741 0.0008819319
[6,] 0.0046107199 -0.0022536741
[7,] 0.0309262155 0.0046107199
[8,] 0.0277906095 0.0309262155
[9,] 0.0352039019 0.0277906095
[10,] 0.0320682959 0.0352039019
[11,] 0.0289326899 0.0320682959
[12,] 0.0257970839 0.0289326899
[13,] 0.0226614779 0.0257970839
[14,] 0.0195258719 0.0226614779
[15,] 0.0163902659 0.0195258719
[16,] 0.0132546599 0.0163902659
[17,] 0.0101190539 0.0132546599
[18,] 0.0069834479 0.0101190539
[19,] -0.0067010565 0.0069834479
[20,] -0.0098366625 -0.0067010565
[21,] -0.0129722685 -0.0098366625
[22,] -0.0266567729 -0.0129722685
[23,] -0.0297923789 -0.0266567729
[24,] -0.0329279848 -0.0297923789
[25,] -0.0360635908 -0.0329279848
[26,] -0.0391991968 -0.0360635908
[27,] -0.0423348028 -0.0391991968
[28,] -0.0454704088 -0.0423348028
[29,] -0.0486060148 -0.0454704088
[30,] -0.0517416208 -0.0486060148
[31,] -0.0548772268 -0.0517416208
[32,] -0.0474639344 -0.0548772268
[33,] -0.0505995404 -0.0474639344
[34,] -0.0537351464 -0.0505995404
[35,] -0.0568707524 -0.0537351464
[36,] -0.0600063584 -0.0568707524
[37,] 0.0163091372 -0.0600063584
[38,] 0.0126246328 0.0163091372
[39,] 0.0094890268 0.0126246328
[40,] 0.0063534208 0.0094890268
[41,] 0.0032178148 0.0063534208
[42,] 0.0100822088 0.0032178148
[43,] 0.0169466028 0.0100822088
[44,] 0.0138109968 0.0169466028
[45,] 0.0206753908 0.0138109968
[46,] 0.0069908864 0.0206753908
[47,] 0.0038552804 0.0069908864
[48,] 0.0107196744 0.0038552804
[49,] 0.0175840684 0.0107196744
[50,] 0.0144484624 0.0175840684
[51,] 0.0318617548 0.0144484624
[52,] 0.0181772504 0.0318617548
[53,] 0.0255905429 0.0181772504
[54,] 0.0224549369 0.0255905429
[55,] 0.0087704325 0.0224549369
[56,] 0.0261837249 0.0087704325
[57,] 0.0230481189 0.0261837249
[58,] 0.0199125129 0.0230481189
[59,] 0.0167769069 0.0199125129
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.0208376483 0.0239732543
2 0.0177020423 0.0208376483
3 0.0145664363 0.0177020423
4 0.0008819319 0.0145664363
5 -0.0022536741 0.0008819319
6 0.0046107199 -0.0022536741
7 0.0309262155 0.0046107199
8 0.0277906095 0.0309262155
9 0.0352039019 0.0277906095
10 0.0320682959 0.0352039019
11 0.0289326899 0.0320682959
12 0.0257970839 0.0289326899
13 0.0226614779 0.0257970839
14 0.0195258719 0.0226614779
15 0.0163902659 0.0195258719
16 0.0132546599 0.0163902659
17 0.0101190539 0.0132546599
18 0.0069834479 0.0101190539
19 -0.0067010565 0.0069834479
20 -0.0098366625 -0.0067010565
21 -0.0129722685 -0.0098366625
22 -0.0266567729 -0.0129722685
23 -0.0297923789 -0.0266567729
24 -0.0329279848 -0.0297923789
25 -0.0360635908 -0.0329279848
26 -0.0391991968 -0.0360635908
27 -0.0423348028 -0.0391991968
28 -0.0454704088 -0.0423348028
29 -0.0486060148 -0.0454704088
30 -0.0517416208 -0.0486060148
31 -0.0548772268 -0.0517416208
32 -0.0474639344 -0.0548772268
33 -0.0505995404 -0.0474639344
34 -0.0537351464 -0.0505995404
35 -0.0568707524 -0.0537351464
36 -0.0600063584 -0.0568707524
37 0.0163091372 -0.0600063584
38 0.0126246328 0.0163091372
39 0.0094890268 0.0126246328
40 0.0063534208 0.0094890268
41 0.0032178148 0.0063534208
42 0.0100822088 0.0032178148
43 0.0169466028 0.0100822088
44 0.0138109968 0.0169466028
45 0.0206753908 0.0138109968
46 0.0069908864 0.0206753908
47 0.0038552804 0.0069908864
48 0.0107196744 0.0038552804
49 0.0175840684 0.0107196744
50 0.0144484624 0.0175840684
51 0.0318617548 0.0144484624
52 0.0181772504 0.0318617548
53 0.0255905429 0.0181772504
54 0.0224549369 0.0255905429
55 0.0087704325 0.0224549369
56 0.0261837249 0.0087704325
57 0.0230481189 0.0261837249
58 0.0199125129 0.0230481189
59 0.0167769069 0.0199125129
> 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/7cubg1258714571.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8cox71258714571.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9rwsh1258714571.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10l73r1258714571.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11oxh81258714571.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/12iubv1258714571.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/139e731258714571.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/14tgep1258714571.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/151tgt1258714571.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/16pjr71258714571.tab")
+ }
>
> system("convert tmp/1dmys1258714571.ps tmp/1dmys1258714571.png")
> system("convert tmp/23r091258714571.ps tmp/23r091258714571.png")
> system("convert tmp/3z2ti1258714571.ps tmp/3z2ti1258714571.png")
> system("convert tmp/4dcpg1258714571.ps tmp/4dcpg1258714571.png")
> system("convert tmp/5v1os1258714571.ps tmp/5v1os1258714571.png")
> system("convert tmp/63wk41258714571.ps tmp/63wk41258714571.png")
> system("convert tmp/7cubg1258714571.ps tmp/7cubg1258714571.png")
> system("convert tmp/8cox71258714571.ps tmp/8cox71258714571.png")
> system("convert tmp/9rwsh1258714571.ps tmp/9rwsh1258714571.png")
> system("convert tmp/10l73r1258714571.ps tmp/10l73r1258714571.png")
>
>
> proc.time()
user system elapsed
2.375 1.502 2.905