R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(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 = '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 Bakmeelprijs M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 1.43 0.51 1 0 0 0 0 0 0 0 0 0 0 1
2 1.43 0.51 0 1 0 0 0 0 0 0 0 0 0 2
3 1.43 0.51 0 0 1 0 0 0 0 0 0 0 0 3
4 1.43 0.51 0 0 0 1 0 0 0 0 0 0 0 4
5 1.43 0.52 0 0 0 0 1 0 0 0 0 0 0 5
6 1.43 0.52 0 0 0 0 0 1 0 0 0 0 0 6
7 1.44 0.52 0 0 0 0 0 0 1 0 0 0 0 7
8 1.48 0.53 0 0 0 0 0 0 0 1 0 0 0 8
9 1.48 0.53 0 0 0 0 0 0 0 0 1 0 0 9
10 1.48 0.52 0 0 0 0 0 0 0 0 0 1 0 10
11 1.48 0.52 0 0 0 0 0 0 0 0 0 0 1 11
12 1.48 0.52 0 0 0 0 0 0 0 0 0 0 0 12
13 1.48 0.52 1 0 0 0 0 0 0 0 0 0 0 13
14 1.48 0.52 0 1 0 0 0 0 0 0 0 0 0 14
15 1.48 0.52 0 0 1 0 0 0 0 0 0 0 0 15
16 1.48 0.52 0 0 0 1 0 0 0 0 0 0 0 16
17 1.48 0.52 0 0 0 0 1 0 0 0 0 0 0 17
18 1.48 0.52 0 0 0 0 0 1 0 0 0 0 0 18
19 1.48 0.52 0 0 0 0 0 0 1 0 0 0 0 19
20 1.48 0.53 0 0 0 0 0 0 0 1 0 0 0 20
21 1.48 0.53 0 0 0 0 0 0 0 0 1 0 0 21
22 1.48 0.53 0 0 0 0 0 0 0 0 0 1 0 22
23 1.48 0.54 0 0 0 0 0 0 0 0 0 0 1 23
24 1.48 0.54 0 0 0 0 0 0 0 0 0 0 0 24
25 1.48 0.54 1 0 0 0 0 0 0 0 0 0 0 25
26 1.48 0.54 0 1 0 0 0 0 0 0 0 0 0 26
27 1.48 0.54 0 0 1 0 0 0 0 0 0 0 0 27
28 1.48 0.54 0 0 0 1 0 0 0 0 0 0 0 28
29 1.48 0.54 0 0 0 0 1 0 0 0 0 0 0 29
30 1.48 0.54 0 0 0 0 0 1 0 0 0 0 0 30
31 1.48 0.54 0 0 0 0 0 0 1 0 0 0 0 31
32 1.48 0.54 0 0 0 0 0 0 0 1 0 0 0 32
33 1.48 0.53 0 0 0 0 0 0 0 0 1 0 0 33
34 1.48 0.53 0 0 0 0 0 0 0 0 0 1 0 34
35 1.48 0.53 0 0 0 0 0 0 0 0 0 0 1 35
36 1.48 0.53 0 0 0 0 0 0 0 0 0 0 0 36
37 1.48 0.53 1 0 0 0 0 0 0 0 0 0 0 37
38 1.57 0.54 0 1 0 0 0 0 0 0 0 0 0 38
39 1.58 0.55 0 0 1 0 0 0 0 0 0 0 0 39
40 1.58 0.55 0 0 0 1 0 0 0 0 0 0 0 40
41 1.58 0.55 0 0 0 0 1 0 0 0 0 0 0 41
42 1.58 0.55 0 0 0 0 0 1 0 0 0 0 0 42
43 1.59 0.55 0 0 0 0 0 0 1 0 0 0 0 43
44 1.60 0.55 0 0 0 0 0 0 0 1 0 0 0 44
45 1.60 0.55 0 0 0 0 0 0 0 0 1 0 0 45
46 1.61 0.55 0 0 0 0 0 0 0 0 0 1 0 46
47 1.61 0.56 0 0 0 0 0 0 0 0 0 0 1 47
48 1.61 0.56 0 0 0 0 0 0 0 0 0 0 0 48
49 1.62 0.56 1 0 0 0 0 0 0 0 0 0 0 49
50 1.63 0.56 0 1 0 0 0 0 0 0 0 0 0 50
51 1.63 0.56 0 0 1 0 0 0 0 0 0 0 0 51
52 1.64 0.55 0 0 0 1 0 0 0 0 0 0 0 52
53 1.64 0.56 0 0 0 0 1 0 0 0 0 0 0 53
54 1.64 0.55 0 0 0 0 0 1 0 0 0 0 0 54
55 1.64 0.55 0 0 0 0 0 0 1 0 0 0 0 55
56 1.64 0.56 0 0 0 0 0 0 0 1 0 0 0 56
57 1.65 0.55 0 0 0 0 0 0 0 0 1 0 0 57
58 1.65 0.55 0 0 0 0 0 0 0 0 0 1 0 58
59 1.65 0.55 0 0 0 0 0 0 0 0 0 0 1 59
60 1.65 0.55 0 0 0 0 0 0 0 0 0 0 0 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Bakmeelprijs M1 M2 M3
0.865077 1.038462 0.001188 0.015940 0.012692
M4 M5 M6 M7 M8
0.013598 0.006274 0.005179 0.006009 0.006607
M9 M10 M11 t
0.009590 0.010496 0.003171 0.003171
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.053974 -0.017276 0.009115 0.017994 0.036872
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.8650769 0.3452790 2.505 0.0158 *
Bakmeelprijs 1.0384615 0.6742495 1.540 0.1304
M1 0.0011880 0.0202272 0.059 0.9534
M2 0.0159402 0.0202327 0.788 0.4348
M3 0.0126923 0.0202738 0.626 0.5344
M4 0.0135983 0.0201407 0.675 0.5030
M5 0.0062735 0.0202590 0.310 0.7582
M6 0.0051795 0.0201054 0.258 0.7979
M7 0.0060085 0.0200831 0.299 0.7661
M8 0.0066068 0.0203702 0.324 0.7472
M9 0.0095897 0.0200615 0.478 0.6349
M10 0.0104957 0.0201188 0.522 0.6044
M11 0.0031709 0.0200554 0.158 0.8751
t 0.0031709 0.0005857 5.414 2.17e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.0317 on 46 degrees of freedom
Multiple R-squared: 0.8612, Adjusted R-squared: 0.8219
F-statistic: 21.95 on 13 and 46 DF, p-value: 1.897e-15
> 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,] 4.145112e-43 8.290224e-43 1.0000000000
[2,] 2.564844e-53 5.129688e-53 1.0000000000
[3,] 1.100568e-04 2.201136e-04 0.9998899432
[4,] 1.471558e-01 2.943117e-01 0.8528441678
[5,] 2.876864e-01 5.753727e-01 0.7123136362
[6,] 6.269805e-01 7.460390e-01 0.3730194998
[7,] 7.407198e-01 5.185605e-01 0.2592802344
[8,] 7.757553e-01 4.484893e-01 0.2242446678
[9,] 7.830820e-01 4.338360e-01 0.2169179781
[10,] 7.015595e-01 5.968811e-01 0.2984405355
[11,] 6.060553e-01 7.878893e-01 0.3939446526
[12,] 5.360866e-01 9.278267e-01 0.4639133647
[13,] 4.436243e-01 8.872485e-01 0.5563757284
[14,] 3.909311e-01 7.818623e-01 0.6090688642
[15,] 3.986437e-01 7.972875e-01 0.6013562658
[16,] 5.560341e-01 8.879318e-01 0.4439659145
[17,] 6.301284e-01 7.397431e-01 0.3698715505
[18,] 6.977408e-01 6.045185e-01 0.3022592463
[19,] 6.980995e-01 6.038011e-01 0.3019005308
[20,] 7.613528e-01 4.772943e-01 0.2386471748
[21,] 9.984806e-01 3.038838e-03 0.0015194188
[22,] 9.993373e-01 1.325399e-03 0.0006626995
[23,] 9.991961e-01 1.607788e-03 0.0008038940
[24,] 9.991353e-01 1.729476e-03 0.0008647382
[25,] 9.983948e-01 3.210469e-03 0.0016052345
[26,] 9.991369e-01 1.726122e-03 0.0008630608
[27,] 9.973347e-01 5.330511e-03 0.0026652557
> postscript(file="/var/www/html/rcomp/tmp/1vy0u1258719603.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2g84m1258719603.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3vvff1258719603.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4uncy1258719603.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5t1dc1258719603.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
0.0309487179 0.0130256410 0.0131025641 0.0090256410 0.0027948718
6 7 8 9 10
0.0007179487 0.0067179487 0.0325641026 0.0264102564 0.0327179487
11 12 13 14 15
0.0368717949 0.0368717949 0.0325128205 0.0145897436 0.0146666667
16 17 18 19 20
0.0105897436 0.0147435897 0.0126666667 0.0086666667 -0.0054871795
21 22 23 24 25
-0.0116410256 -0.0157179487 -0.0219487179 -0.0219487179 -0.0263076923
26 27 28 29 30
-0.0442307692 -0.0441538462 -0.0482307692 -0.0440769231 -0.0461538462
31 32 33 34 35
-0.0501538462 -0.0539230769 -0.0496923077 -0.0537692308 -0.0496153846
36 37 38 39 40
-0.0496153846 -0.0539743590 0.0077179487 0.0074102564 0.0033333333
41 42 43 44 45
0.0074871795 0.0054102564 0.0114102564 0.0176410256 0.0114871795
46 47 48 49 50
0.0174102564 0.0111794872 0.0111794872 0.0168205128 0.0088974359
51 52 53 54 55
0.0089743590 0.0252820513 0.0190512821 0.0273589744 0.0233589744
56 57 58 59 60
0.0092051282 0.0234358974 0.0193589744 0.0235128205 0.0235128205
> postscript(file="/var/www/html/rcomp/tmp/6rls51258719603.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 0.0309487179 NA
1 0.0130256410 0.0309487179
2 0.0131025641 0.0130256410
3 0.0090256410 0.0131025641
4 0.0027948718 0.0090256410
5 0.0007179487 0.0027948718
6 0.0067179487 0.0007179487
7 0.0325641026 0.0067179487
8 0.0264102564 0.0325641026
9 0.0327179487 0.0264102564
10 0.0368717949 0.0327179487
11 0.0368717949 0.0368717949
12 0.0325128205 0.0368717949
13 0.0145897436 0.0325128205
14 0.0146666667 0.0145897436
15 0.0105897436 0.0146666667
16 0.0147435897 0.0105897436
17 0.0126666667 0.0147435897
18 0.0086666667 0.0126666667
19 -0.0054871795 0.0086666667
20 -0.0116410256 -0.0054871795
21 -0.0157179487 -0.0116410256
22 -0.0219487179 -0.0157179487
23 -0.0219487179 -0.0219487179
24 -0.0263076923 -0.0219487179
25 -0.0442307692 -0.0263076923
26 -0.0441538462 -0.0442307692
27 -0.0482307692 -0.0441538462
28 -0.0440769231 -0.0482307692
29 -0.0461538462 -0.0440769231
30 -0.0501538462 -0.0461538462
31 -0.0539230769 -0.0501538462
32 -0.0496923077 -0.0539230769
33 -0.0537692308 -0.0496923077
34 -0.0496153846 -0.0537692308
35 -0.0496153846 -0.0496153846
36 -0.0539743590 -0.0496153846
37 0.0077179487 -0.0539743590
38 0.0074102564 0.0077179487
39 0.0033333333 0.0074102564
40 0.0074871795 0.0033333333
41 0.0054102564 0.0074871795
42 0.0114102564 0.0054102564
43 0.0176410256 0.0114102564
44 0.0114871795 0.0176410256
45 0.0174102564 0.0114871795
46 0.0111794872 0.0174102564
47 0.0111794872 0.0111794872
48 0.0168205128 0.0111794872
49 0.0088974359 0.0168205128
50 0.0089743590 0.0088974359
51 0.0252820513 0.0089743590
52 0.0190512821 0.0252820513
53 0.0273589744 0.0190512821
54 0.0233589744 0.0273589744
55 0.0092051282 0.0233589744
56 0.0234358974 0.0092051282
57 0.0193589744 0.0234358974
58 0.0235128205 0.0193589744
59 0.0235128205 0.0235128205
60 NA 0.0235128205
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.0130256410 0.0309487179
[2,] 0.0131025641 0.0130256410
[3,] 0.0090256410 0.0131025641
[4,] 0.0027948718 0.0090256410
[5,] 0.0007179487 0.0027948718
[6,] 0.0067179487 0.0007179487
[7,] 0.0325641026 0.0067179487
[8,] 0.0264102564 0.0325641026
[9,] 0.0327179487 0.0264102564
[10,] 0.0368717949 0.0327179487
[11,] 0.0368717949 0.0368717949
[12,] 0.0325128205 0.0368717949
[13,] 0.0145897436 0.0325128205
[14,] 0.0146666667 0.0145897436
[15,] 0.0105897436 0.0146666667
[16,] 0.0147435897 0.0105897436
[17,] 0.0126666667 0.0147435897
[18,] 0.0086666667 0.0126666667
[19,] -0.0054871795 0.0086666667
[20,] -0.0116410256 -0.0054871795
[21,] -0.0157179487 -0.0116410256
[22,] -0.0219487179 -0.0157179487
[23,] -0.0219487179 -0.0219487179
[24,] -0.0263076923 -0.0219487179
[25,] -0.0442307692 -0.0263076923
[26,] -0.0441538462 -0.0442307692
[27,] -0.0482307692 -0.0441538462
[28,] -0.0440769231 -0.0482307692
[29,] -0.0461538462 -0.0440769231
[30,] -0.0501538462 -0.0461538462
[31,] -0.0539230769 -0.0501538462
[32,] -0.0496923077 -0.0539230769
[33,] -0.0537692308 -0.0496923077
[34,] -0.0496153846 -0.0537692308
[35,] -0.0496153846 -0.0496153846
[36,] -0.0539743590 -0.0496153846
[37,] 0.0077179487 -0.0539743590
[38,] 0.0074102564 0.0077179487
[39,] 0.0033333333 0.0074102564
[40,] 0.0074871795 0.0033333333
[41,] 0.0054102564 0.0074871795
[42,] 0.0114102564 0.0054102564
[43,] 0.0176410256 0.0114102564
[44,] 0.0114871795 0.0176410256
[45,] 0.0174102564 0.0114871795
[46,] 0.0111794872 0.0174102564
[47,] 0.0111794872 0.0111794872
[48,] 0.0168205128 0.0111794872
[49,] 0.0088974359 0.0168205128
[50,] 0.0089743590 0.0088974359
[51,] 0.0252820513 0.0089743590
[52,] 0.0190512821 0.0252820513
[53,] 0.0273589744 0.0190512821
[54,] 0.0233589744 0.0273589744
[55,] 0.0092051282 0.0233589744
[56,] 0.0234358974 0.0092051282
[57,] 0.0193589744 0.0234358974
[58,] 0.0235128205 0.0193589744
[59,] 0.0235128205 0.0235128205
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.0130256410 0.0309487179
2 0.0131025641 0.0130256410
3 0.0090256410 0.0131025641
4 0.0027948718 0.0090256410
5 0.0007179487 0.0027948718
6 0.0067179487 0.0007179487
7 0.0325641026 0.0067179487
8 0.0264102564 0.0325641026
9 0.0327179487 0.0264102564
10 0.0368717949 0.0327179487
11 0.0368717949 0.0368717949
12 0.0325128205 0.0368717949
13 0.0145897436 0.0325128205
14 0.0146666667 0.0145897436
15 0.0105897436 0.0146666667
16 0.0147435897 0.0105897436
17 0.0126666667 0.0147435897
18 0.0086666667 0.0126666667
19 -0.0054871795 0.0086666667
20 -0.0116410256 -0.0054871795
21 -0.0157179487 -0.0116410256
22 -0.0219487179 -0.0157179487
23 -0.0219487179 -0.0219487179
24 -0.0263076923 -0.0219487179
25 -0.0442307692 -0.0263076923
26 -0.0441538462 -0.0442307692
27 -0.0482307692 -0.0441538462
28 -0.0440769231 -0.0482307692
29 -0.0461538462 -0.0440769231
30 -0.0501538462 -0.0461538462
31 -0.0539230769 -0.0501538462
32 -0.0496923077 -0.0539230769
33 -0.0537692308 -0.0496923077
34 -0.0496153846 -0.0537692308
35 -0.0496153846 -0.0496153846
36 -0.0539743590 -0.0496153846
37 0.0077179487 -0.0539743590
38 0.0074102564 0.0077179487
39 0.0033333333 0.0074102564
40 0.0074871795 0.0033333333
41 0.0054102564 0.0074871795
42 0.0114102564 0.0054102564
43 0.0176410256 0.0114102564
44 0.0114871795 0.0176410256
45 0.0174102564 0.0114871795
46 0.0111794872 0.0174102564
47 0.0111794872 0.0111794872
48 0.0168205128 0.0111794872
49 0.0088974359 0.0168205128
50 0.0089743590 0.0088974359
51 0.0252820513 0.0089743590
52 0.0190512821 0.0252820513
53 0.0273589744 0.0190512821
54 0.0233589744 0.0273589744
55 0.0092051282 0.0233589744
56 0.0234358974 0.0092051282
57 0.0193589744 0.0234358974
58 0.0235128205 0.0193589744
59 0.0235128205 0.0235128205
> 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/7f8ri1258719603.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/88u491258719603.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9u6zw1258719603.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10j45m1258719603.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11wgb21258719603.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/12lbmt1258719603.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/13014h1258719603.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/14shiv1258719603.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/15zfq11258719603.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/16mx391258719603.tab")
+ }
>
> system("convert tmp/1vy0u1258719603.ps tmp/1vy0u1258719603.png")
> system("convert tmp/2g84m1258719603.ps tmp/2g84m1258719603.png")
> system("convert tmp/3vvff1258719603.ps tmp/3vvff1258719603.png")
> system("convert tmp/4uncy1258719603.ps tmp/4uncy1258719603.png")
> system("convert tmp/5t1dc1258719603.ps tmp/5t1dc1258719603.png")
> system("convert tmp/6rls51258719603.ps tmp/6rls51258719603.png")
> system("convert tmp/7f8ri1258719603.ps tmp/7f8ri1258719603.png")
> system("convert tmp/88u491258719603.ps tmp/88u491258719603.png")
> system("convert tmp/9u6zw1258719603.ps tmp/9u6zw1258719603.png")
> system("convert tmp/10j45m1258719603.ps tmp/10j45m1258719603.png")
>
>
> proc.time()
user system elapsed
2.393 1.556 3.739