R version 2.13.0 (2011-04-13)
Copyright (C) 2011 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
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(200
+ ,10
+ ,30000
+ ,14
+ ,200000
+ ,150
+ ,8
+ ,25000
+ ,12
+ ,150000
+ ,350
+ ,15
+ ,40000
+ ,15
+ ,300000
+ ,550
+ ,20
+ ,60000
+ ,16
+ ,500000
+ ,200
+ ,10
+ ,350000
+ ,15
+ ,250000
+ ,550
+ ,22
+ ,70000
+ ,18
+ ,600000
+ ,95
+ ,6
+ ,180000
+ ,10
+ ,100000
+ ,200
+ ,10
+ ,30000
+ ,14
+ ,200000
+ ,150
+ ,8
+ ,25000
+ ,12
+ ,150000
+ ,350
+ ,15
+ ,40000
+ ,15
+ ,300000
+ ,550
+ ,20
+ ,60000
+ ,16
+ ,500000
+ ,200
+ ,10
+ ,30000
+ ,14
+ ,200000
+ ,150
+ ,8
+ ,25000
+ ,12
+ ,150000
+ ,350
+ ,15
+ ,40000
+ ,15
+ ,300000
+ ,550
+ ,20
+ ,60000
+ ,16
+ ,500000
+ ,200
+ ,10
+ ,30000
+ ,14
+ ,200000
+ ,150
+ ,8
+ ,25000
+ ,12
+ ,150000
+ ,350
+ ,15
+ ,40000
+ ,15
+ ,300000
+ ,550
+ ,20
+ ,60000
+ ,16
+ ,500000
+ ,200
+ ,10
+ ,350000
+ ,15
+ ,250000
+ ,550
+ ,22
+ ,70000
+ ,18
+ ,600000
+ ,95
+ ,6
+ ,180000
+ ,10
+ ,100000
+ ,200
+ ,10
+ ,30000
+ ,14
+ ,200000
+ ,150
+ ,8
+ ,25000
+ ,12
+ ,150000
+ ,350
+ ,15
+ ,40000
+ ,15
+ ,300000
+ ,550
+ ,20
+ ,60000
+ ,16
+ ,500000
+ ,200
+ ,10
+ ,350000
+ ,15
+ ,250000
+ ,550
+ ,22
+ ,70000
+ ,18
+ ,600000
+ ,95
+ ,6
+ ,180000
+ ,10
+ ,100000
+ ,200
+ ,10
+ ,30000
+ ,14
+ ,200000
+ ,150
+ ,8
+ ,25000
+ ,12
+ ,150000
+ ,350
+ ,15
+ ,40000
+ ,15
+ ,300000
+ ,550
+ ,20
+ ,60000
+ ,16
+ ,500000
+ ,200
+ ,10
+ ,350000
+ ,15
+ ,250000
+ ,550
+ ,22
+ ,70000
+ ,18
+ ,600000
+ ,95
+ ,6
+ ,180000
+ ,10
+ ,100000
+ ,200
+ ,10
+ ,30000
+ ,14
+ ,200000
+ ,150
+ ,8
+ ,25000
+ ,12
+ ,150000
+ ,350
+ ,15
+ ,40000
+ ,15
+ ,300000
+ ,550
+ ,20
+ ,60000
+ ,16
+ ,500000
+ ,200
+ ,10
+ ,30000
+ ,14
+ ,200000
+ ,150
+ ,8
+ ,25000
+ ,12
+ ,150000
+ ,350
+ ,15
+ ,40000
+ ,15
+ ,300000
+ ,550
+ ,20
+ ,60000
+ ,16
+ ,500000
+ ,200
+ ,10
+ ,30000
+ ,14
+ ,200000
+ ,150
+ ,8
+ ,25000
+ ,12
+ ,150000
+ ,350
+ ,15
+ ,40000
+ ,15
+ ,300000
+ ,550
+ ,20
+ ,60000
+ ,16
+ ,500000
+ ,200
+ ,10
+ ,350000
+ ,15
+ ,250000
+ ,550
+ ,22
+ ,70000
+ ,18
+ ,600000
+ ,95
+ ,6
+ ,180000
+ ,10
+ ,100000
+ ,200
+ ,10
+ ,30000
+ ,14
+ ,200000
+ ,150
+ ,8
+ ,25000
+ ,12
+ ,150000
+ ,350
+ ,15
+ ,40000
+ ,15
+ ,300000
+ ,550
+ ,20
+ ,60000
+ ,16
+ ,500000
+ ,200
+ ,10
+ ,350000
+ ,15
+ ,250000
+ ,550
+ ,22
+ ,70000
+ ,18
+ ,600000
+ ,95
+ ,6
+ ,180000
+ ,10
+ ,100000
+ ,550
+ ,20
+ ,60000
+ ,16
+ ,500000
+ ,200
+ ,10
+ ,350000
+ ,15
+ ,250000
+ ,550
+ ,22
+ ,70000
+ ,18
+ ,600000
+ ,95
+ ,6
+ ,180000
+ ,10
+ ,100000
+ ,200
+ ,10
+ ,30000
+ ,14
+ ,200000)
+ ,dim=c(5
+ ,63)
+ ,dimnames=list(c('mē'
+ ,'kamers'
+ ,'inkomens'
+ ,'aantrekkelijkheid'
+ ,'prijs')
+ ,1:63))
> y <- array(NA,dim=c(5,63),dimnames=list(c('mē','kamers','inkomens','aantrekkelijkheid','prijs'),1:63))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '5'
> 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
prijs m\262 kamers inkomens aantrekkelijkheid
1 200000 200 10 30000 14
2 150000 150 8 25000 12
3 300000 350 15 40000 15
4 500000 550 20 60000 16
5 250000 200 10 350000 15
6 600000 550 22 70000 18
7 100000 95 6 180000 10
8 200000 200 10 30000 14
9 150000 150 8 25000 12
10 300000 350 15 40000 15
11 500000 550 20 60000 16
12 200000 200 10 30000 14
13 150000 150 8 25000 12
14 300000 350 15 40000 15
15 500000 550 20 60000 16
16 200000 200 10 30000 14
17 150000 150 8 25000 12
18 300000 350 15 40000 15
19 500000 550 20 60000 16
20 250000 200 10 350000 15
21 600000 550 22 70000 18
22 100000 95 6 180000 10
23 200000 200 10 30000 14
24 150000 150 8 25000 12
25 300000 350 15 40000 15
26 500000 550 20 60000 16
27 250000 200 10 350000 15
28 600000 550 22 70000 18
29 100000 95 6 180000 10
30 200000 200 10 30000 14
31 150000 150 8 25000 12
32 300000 350 15 40000 15
33 500000 550 20 60000 16
34 250000 200 10 350000 15
35 600000 550 22 70000 18
36 100000 95 6 180000 10
37 200000 200 10 30000 14
38 150000 150 8 25000 12
39 300000 350 15 40000 15
40 500000 550 20 60000 16
41 200000 200 10 30000 14
42 150000 150 8 25000 12
43 300000 350 15 40000 15
44 500000 550 20 60000 16
45 200000 200 10 30000 14
46 150000 150 8 25000 12
47 300000 350 15 40000 15
48 500000 550 20 60000 16
49 250000 200 10 350000 15
50 600000 550 22 70000 18
51 100000 95 6 180000 10
52 200000 200 10 30000 14
53 150000 150 8 25000 12
54 300000 350 15 40000 15
55 500000 550 20 60000 16
56 250000 200 10 350000 15
57 600000 550 22 70000 18
58 100000 95 6 180000 10
59 500000 550 20 60000 16
60 250000 200 10 350000 15
61 600000 550 22 70000 18
62 100000 95 6 180000 10
63 200000 200 10 30000 14
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `m\262` kamers inkomens
-1.276e+05 -6.348e+01 3.205e+04 1.799e-01
aantrekkelijkheid
6.461e+02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-47813 -2835 2509 18483 33193
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.276e+05 3.107e+04 -4.108 0.000127 ***
`m\262` -6.348e+01 2.176e+02 -0.292 0.771532
kamers 3.205e+04 7.936e+03 4.039 0.000160 ***
inkomens 1.799e-01 3.469e-02 5.184 2.87e-06 ***
aantrekkelijkheid 6.461e+02 4.327e+03 0.149 0.881821
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 24360 on 58 degrees of freedom
Multiple R-squared: 0.9798, Adjusted R-squared: 0.9784
F-statistic: 702.9 on 4 and 58 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.8774966 2.450068e-01 1.225034e-01
[2,] 0.8120083 3.759834e-01 1.879917e-01
[3,] 0.9263817 1.472366e-01 7.361831e-02
[4,] 0.8733415 2.533169e-01 1.266585e-01
[5,] 0.8046900 3.906201e-01 1.953100e-01
[6,] 0.7503289 4.993422e-01 2.496711e-01
[7,] 0.8567460 2.865081e-01 1.432540e-01
[8,] 0.7926437 4.147126e-01 2.073563e-01
[9,] 0.7184047 5.631906e-01 2.815953e-01
[10,] 0.6655643 6.688715e-01 3.344357e-01
[11,] 0.7772604 4.454792e-01 2.227396e-01
[12,] 0.7052432 5.895135e-01 2.947568e-01
[13,] 0.6265852 7.468296e-01 3.734148e-01
[14,] 0.7842312 4.315377e-01 2.157688e-01
[15,] 0.7187132 5.625735e-01 2.812868e-01
[16,] 0.6474518 7.050964e-01 3.525482e-01
[17,] 0.6059691 7.880618e-01 3.940309e-01
[18,] 0.7613737 4.772525e-01 2.386263e-01
[19,] 0.6947961 6.104079e-01 3.052039e-01
[20,] 0.6224109 7.551783e-01 3.775891e-01
[21,] 0.6976581 6.046838e-01 3.023419e-01
[22,] 0.6261217 7.477565e-01 3.738783e-01
[23,] 0.5526367 8.947266e-01 4.473633e-01
[24,] 0.5149979 9.700042e-01 4.850021e-01
[25,] 0.7010278 5.979445e-01 2.989722e-01
[26,] 0.6291381 7.417239e-01 3.708619e-01
[27,] 0.5531844 8.936312e-01 4.468156e-01
[28,] 0.6029238 7.941525e-01 3.970762e-01
[29,] 0.5249813 9.500373e-01 4.750187e-01
[30,] 0.4484169 8.968338e-01 5.515831e-01
[31,] 0.4122963 8.245925e-01 5.877037e-01
[32,] 0.6203901 7.592198e-01 3.796099e-01
[33,] 0.5390321 9.219358e-01 4.609679e-01
[34,] 0.4591405 9.182809e-01 5.408595e-01
[35,] 0.4261195 8.522391e-01 5.738805e-01
[36,] 0.6806431 6.387138e-01 3.193569e-01
[37,] 0.5962494 8.075012e-01 4.037506e-01
[38,] 0.5106126 9.787748e-01 4.893874e-01
[39,] 0.4869470 9.738940e-01 5.130530e-01
[40,] 0.8291570 3.416859e-01 1.708430e-01
[41,] 0.7541250 4.917500e-01 2.458750e-01
[42,] 0.6618447 6.763106e-01 3.381553e-01
[43,] 0.6191814 7.616372e-01 3.808186e-01
[44,] 0.5036072 9.927856e-01 4.963928e-01
[45,] 0.3878905 7.757810e-01 6.121095e-01
[46,] 0.3887985 7.775970e-01 6.112015e-01
[47,] 1.0000000 2.527870e-60 1.263935e-60
[48,] 1.0000000 1.711189e-45 8.555947e-46
> postscript(file="/var/wessaorg/rcomp/tmp/1qaob1321999162.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/wessaorg/rcomp/tmp/2rh2v1321999162.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/35nhl1321999162.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/42mtj1321999162.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5r8qz1321999162.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 63
Frequency = 1
1 2 3 4 5 6
5363.6940 18482.8674 -47813.2732 385.1167 -2834.6330 33192.8256
7 8 9 10 11 12
2508.5418 5363.6940 18482.8674 -47813.2732 385.1167 5363.6940
13 14 15 16 17 18
18482.8674 -47813.2732 385.1167 5363.6940 18482.8674 -47813.2732
19 20 21 22 23 24
385.1167 -2834.6330 33192.8256 2508.5418 5363.6940 18482.8674
25 26 27 28 29 30
-47813.2732 385.1167 -2834.6330 33192.8256 2508.5418 5363.6940
31 32 33 34 35 36
18482.8674 -47813.2732 385.1167 -2834.6330 33192.8256 2508.5418
37 38 39 40 41 42
5363.6940 18482.8674 -47813.2732 385.1167 5363.6940 18482.8674
43 44 45 46 47 48
-47813.2732 385.1167 5363.6940 18482.8674 -47813.2732 385.1167
49 50 51 52 53 54
-2834.6330 33192.8256 2508.5418 5363.6940 18482.8674 -47813.2732
55 56 57 58 59 60
385.1167 -2834.6330 33192.8256 2508.5418 385.1167 -2834.6330
61 62 63
33192.8256 2508.5418 5363.6940
> postscript(file="/var/wessaorg/rcomp/tmp/6uwa71321999162.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 = 63
Frequency = 1
lag(myerror, k = 1) myerror
0 5363.6940 NA
1 18482.8674 5363.6940
2 -47813.2732 18482.8674
3 385.1167 -47813.2732
4 -2834.6330 385.1167
5 33192.8256 -2834.6330
6 2508.5418 33192.8256
7 5363.6940 2508.5418
8 18482.8674 5363.6940
9 -47813.2732 18482.8674
10 385.1167 -47813.2732
11 5363.6940 385.1167
12 18482.8674 5363.6940
13 -47813.2732 18482.8674
14 385.1167 -47813.2732
15 5363.6940 385.1167
16 18482.8674 5363.6940
17 -47813.2732 18482.8674
18 385.1167 -47813.2732
19 -2834.6330 385.1167
20 33192.8256 -2834.6330
21 2508.5418 33192.8256
22 5363.6940 2508.5418
23 18482.8674 5363.6940
24 -47813.2732 18482.8674
25 385.1167 -47813.2732
26 -2834.6330 385.1167
27 33192.8256 -2834.6330
28 2508.5418 33192.8256
29 5363.6940 2508.5418
30 18482.8674 5363.6940
31 -47813.2732 18482.8674
32 385.1167 -47813.2732
33 -2834.6330 385.1167
34 33192.8256 -2834.6330
35 2508.5418 33192.8256
36 5363.6940 2508.5418
37 18482.8674 5363.6940
38 -47813.2732 18482.8674
39 385.1167 -47813.2732
40 5363.6940 385.1167
41 18482.8674 5363.6940
42 -47813.2732 18482.8674
43 385.1167 -47813.2732
44 5363.6940 385.1167
45 18482.8674 5363.6940
46 -47813.2732 18482.8674
47 385.1167 -47813.2732
48 -2834.6330 385.1167
49 33192.8256 -2834.6330
50 2508.5418 33192.8256
51 5363.6940 2508.5418
52 18482.8674 5363.6940
53 -47813.2732 18482.8674
54 385.1167 -47813.2732
55 -2834.6330 385.1167
56 33192.8256 -2834.6330
57 2508.5418 33192.8256
58 385.1167 2508.5418
59 -2834.6330 385.1167
60 33192.8256 -2834.6330
61 2508.5418 33192.8256
62 5363.6940 2508.5418
63 NA 5363.6940
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 18482.8674 5363.6940
[2,] -47813.2732 18482.8674
[3,] 385.1167 -47813.2732
[4,] -2834.6330 385.1167
[5,] 33192.8256 -2834.6330
[6,] 2508.5418 33192.8256
[7,] 5363.6940 2508.5418
[8,] 18482.8674 5363.6940
[9,] -47813.2732 18482.8674
[10,] 385.1167 -47813.2732
[11,] 5363.6940 385.1167
[12,] 18482.8674 5363.6940
[13,] -47813.2732 18482.8674
[14,] 385.1167 -47813.2732
[15,] 5363.6940 385.1167
[16,] 18482.8674 5363.6940
[17,] -47813.2732 18482.8674
[18,] 385.1167 -47813.2732
[19,] -2834.6330 385.1167
[20,] 33192.8256 -2834.6330
[21,] 2508.5418 33192.8256
[22,] 5363.6940 2508.5418
[23,] 18482.8674 5363.6940
[24,] -47813.2732 18482.8674
[25,] 385.1167 -47813.2732
[26,] -2834.6330 385.1167
[27,] 33192.8256 -2834.6330
[28,] 2508.5418 33192.8256
[29,] 5363.6940 2508.5418
[30,] 18482.8674 5363.6940
[31,] -47813.2732 18482.8674
[32,] 385.1167 -47813.2732
[33,] -2834.6330 385.1167
[34,] 33192.8256 -2834.6330
[35,] 2508.5418 33192.8256
[36,] 5363.6940 2508.5418
[37,] 18482.8674 5363.6940
[38,] -47813.2732 18482.8674
[39,] 385.1167 -47813.2732
[40,] 5363.6940 385.1167
[41,] 18482.8674 5363.6940
[42,] -47813.2732 18482.8674
[43,] 385.1167 -47813.2732
[44,] 5363.6940 385.1167
[45,] 18482.8674 5363.6940
[46,] -47813.2732 18482.8674
[47,] 385.1167 -47813.2732
[48,] -2834.6330 385.1167
[49,] 33192.8256 -2834.6330
[50,] 2508.5418 33192.8256
[51,] 5363.6940 2508.5418
[52,] 18482.8674 5363.6940
[53,] -47813.2732 18482.8674
[54,] 385.1167 -47813.2732
[55,] -2834.6330 385.1167
[56,] 33192.8256 -2834.6330
[57,] 2508.5418 33192.8256
[58,] 385.1167 2508.5418
[59,] -2834.6330 385.1167
[60,] 33192.8256 -2834.6330
[61,] 2508.5418 33192.8256
[62,] 5363.6940 2508.5418
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 18482.8674 5363.6940
2 -47813.2732 18482.8674
3 385.1167 -47813.2732
4 -2834.6330 385.1167
5 33192.8256 -2834.6330
6 2508.5418 33192.8256
7 5363.6940 2508.5418
8 18482.8674 5363.6940
9 -47813.2732 18482.8674
10 385.1167 -47813.2732
11 5363.6940 385.1167
12 18482.8674 5363.6940
13 -47813.2732 18482.8674
14 385.1167 -47813.2732
15 5363.6940 385.1167
16 18482.8674 5363.6940
17 -47813.2732 18482.8674
18 385.1167 -47813.2732
19 -2834.6330 385.1167
20 33192.8256 -2834.6330
21 2508.5418 33192.8256
22 5363.6940 2508.5418
23 18482.8674 5363.6940
24 -47813.2732 18482.8674
25 385.1167 -47813.2732
26 -2834.6330 385.1167
27 33192.8256 -2834.6330
28 2508.5418 33192.8256
29 5363.6940 2508.5418
30 18482.8674 5363.6940
31 -47813.2732 18482.8674
32 385.1167 -47813.2732
33 -2834.6330 385.1167
34 33192.8256 -2834.6330
35 2508.5418 33192.8256
36 5363.6940 2508.5418
37 18482.8674 5363.6940
38 -47813.2732 18482.8674
39 385.1167 -47813.2732
40 5363.6940 385.1167
41 18482.8674 5363.6940
42 -47813.2732 18482.8674
43 385.1167 -47813.2732
44 5363.6940 385.1167
45 18482.8674 5363.6940
46 -47813.2732 18482.8674
47 385.1167 -47813.2732
48 -2834.6330 385.1167
49 33192.8256 -2834.6330
50 2508.5418 33192.8256
51 5363.6940 2508.5418
52 18482.8674 5363.6940
53 -47813.2732 18482.8674
54 385.1167 -47813.2732
55 -2834.6330 385.1167
56 33192.8256 -2834.6330
57 2508.5418 33192.8256
58 385.1167 2508.5418
59 -2834.6330 385.1167
60 33192.8256 -2834.6330
61 2508.5418 33192.8256
62 5363.6940 2508.5418
> 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/wessaorg/rcomp/tmp/7425x1321999162.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/wessaorg/rcomp/tmp/890dz1321999162.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/wessaorg/rcomp/tmp/9b1a31321999162.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/wessaorg/rcomp/tmp/10idyn1321999162.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/111g941321999162.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/1232nu1321999162.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13bdt61321999162.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/1494de1321999162.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/wessaorg/rcomp/tmp/156jcg1321999162.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/wessaorg/rcomp/tmp/16jpgv1321999162.tab")
+ }
>
> try(system("convert tmp/1qaob1321999162.ps tmp/1qaob1321999162.png",intern=TRUE))
character(0)
> try(system("convert tmp/2rh2v1321999162.ps tmp/2rh2v1321999162.png",intern=TRUE))
character(0)
> try(system("convert tmp/35nhl1321999162.ps tmp/35nhl1321999162.png",intern=TRUE))
character(0)
> try(system("convert tmp/42mtj1321999162.ps tmp/42mtj1321999162.png",intern=TRUE))
character(0)
> try(system("convert tmp/5r8qz1321999162.ps tmp/5r8qz1321999162.png",intern=TRUE))
character(0)
> try(system("convert tmp/6uwa71321999162.ps tmp/6uwa71321999162.png",intern=TRUE))
character(0)
> try(system("convert tmp/7425x1321999162.ps tmp/7425x1321999162.png",intern=TRUE))
character(0)
> try(system("convert tmp/890dz1321999162.ps tmp/890dz1321999162.png",intern=TRUE))
character(0)
> try(system("convert tmp/9b1a31321999162.ps tmp/9b1a31321999162.png",intern=TRUE))
character(0)
> try(system("convert tmp/10idyn1321999162.ps tmp/10idyn1321999162.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.525 0.636 4.183