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
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Type 'q()' to quit R.
> x <- array(list(11
+ ,0
+ ,8
+ ,17
+ ,2
+ ,6
+ ,10
+ ,-2
+ ,3
+ ,23
+ ,3
+ ,7
+ ,9
+ ,-4
+ ,3
+ ,24
+ ,1
+ ,4
+ ,8
+ ,-4
+ ,7
+ ,27
+ ,1
+ ,3
+ ,7
+ ,-7
+ ,4
+ ,31
+ ,0
+ ,0
+ ,6
+ ,-9
+ ,-4
+ ,40
+ ,1
+ ,6
+ ,5
+ ,-13
+ ,-6
+ ,47
+ ,-1
+ ,3
+ ,4
+ ,-8
+ ,8
+ ,43
+ ,2
+ ,1
+ ,3
+ ,-13
+ ,2
+ ,60
+ ,2
+ ,6
+ ,2
+ ,-15
+ ,-1
+ ,64
+ ,0
+ ,5
+ ,1
+ ,-15
+ ,-2
+ ,65
+ ,1
+ ,7
+ ,12
+ ,-15
+ ,0
+ ,65
+ ,1
+ ,4
+ ,11
+ ,-10
+ ,10
+ ,55
+ ,3
+ ,3
+ ,10
+ ,-12
+ ,3
+ ,57
+ ,3
+ ,6
+ ,9
+ ,-11
+ ,6
+ ,57
+ ,1
+ ,6
+ ,8
+ ,-11
+ ,7
+ ,57
+ ,1
+ ,5
+ ,7
+ ,-17
+ ,-4
+ ,65
+ ,-2
+ ,2
+ ,6
+ ,-18
+ ,-5
+ ,69
+ ,1
+ ,3
+ ,5
+ ,-19
+ ,-7
+ ,70
+ ,1
+ ,-2
+ ,4
+ ,-22
+ ,-10
+ ,71
+ ,-1
+ ,-4
+ ,3
+ ,-24
+ ,-21
+ ,71
+ ,-4
+ ,0
+ ,2
+ ,-24
+ ,-22
+ ,73
+ ,-2
+ ,1
+ ,1
+ ,-20
+ ,-16
+ ,68
+ ,-1
+ ,4
+ ,12
+ ,-25
+ ,-25
+ ,65
+ ,-5
+ ,-3
+ ,11
+ ,-22
+ ,-22
+ ,57
+ ,-4
+ ,-3
+ ,10
+ ,-17
+ ,-22
+ ,41
+ ,-5
+ ,0
+ ,9
+ ,-9
+ ,-19
+ ,21
+ ,0
+ ,6
+ ,8
+ ,-11
+ ,-21
+ ,21
+ ,-2
+ ,-1
+ ,7
+ ,-13
+ ,-31
+ ,17
+ ,-4
+ ,0
+ ,6
+ ,-11
+ ,-28
+ ,9
+ ,-6
+ ,-1
+ ,5
+ ,-9
+ ,-23
+ ,11
+ ,-2
+ ,1
+ ,4
+ ,-7
+ ,-17
+ ,6
+ ,-2
+ ,-4
+ ,3
+ ,-3
+ ,-12
+ ,-2
+ ,-2
+ ,-1
+ ,2
+ ,-3
+ ,-14
+ ,0
+ ,1
+ ,-1
+ ,1
+ ,-6
+ ,-18
+ ,5
+ ,-2
+ ,0
+ ,12
+ ,-4
+ ,-16
+ ,3
+ ,0
+ ,3
+ ,11
+ ,-8
+ ,-22
+ ,7
+ ,-1
+ ,0
+ ,10
+ ,-1
+ ,-9
+ ,4
+ ,2
+ ,8
+ ,9
+ ,-2
+ ,-10
+ ,8
+ ,3
+ ,8
+ ,8
+ ,-2
+ ,-10
+ ,9
+ ,2
+ ,8
+ ,7
+ ,-1
+ ,0
+ ,14
+ ,3
+ ,8
+ ,6
+ ,1
+ ,3
+ ,12
+ ,4
+ ,11
+ ,5
+ ,2
+ ,2
+ ,12
+ ,5
+ ,13
+ ,4
+ ,2
+ ,4
+ ,7
+ ,5
+ ,5
+ ,3
+ ,-1
+ ,-3
+ ,15
+ ,4
+ ,12
+ ,2
+ ,1
+ ,0
+ ,14
+ ,5
+ ,13
+ ,1
+ ,-1
+ ,-1
+ ,19
+ ,6
+ ,9
+ ,12
+ ,-8
+ ,-7
+ ,39
+ ,4
+ ,11
+ ,11
+ ,1
+ ,2
+ ,12
+ ,6
+ ,7
+ ,10
+ ,2
+ ,3
+ ,11
+ ,6
+ ,12
+ ,9
+ ,-2
+ ,-3
+ ,17
+ ,3
+ ,11
+ ,8
+ ,-2
+ ,-5
+ ,16
+ ,5
+ ,10
+ ,7
+ ,-2
+ ,0
+ ,25
+ ,5
+ ,13
+ ,6
+ ,-2
+ ,-3
+ ,24
+ ,5
+ ,14
+ ,5
+ ,-6
+ ,-7
+ ,28
+ ,3
+ ,10
+ ,4
+ ,-4
+ ,-7
+ ,25
+ ,5
+ ,13
+ ,3
+ ,-5
+ ,-7
+ ,31
+ ,5
+ ,12
+ ,2
+ ,-2
+ ,-4
+ ,24
+ ,6
+ ,13
+ ,1
+ ,-1
+ ,-3
+ ,24
+ ,6
+ ,17
+ ,12
+ ,-5
+ ,-6
+ ,33
+ ,5
+ ,15)
+ ,dim=c(6
+ ,60)
+ ,dimnames=list(c('maand'
+ ,'indicator'
+ ,'economie'
+ ,'werkloosheid'
+ ,'financiën'
+ ,'spaarvermogen')
+ ,1:60))
> y <- array(NA,dim=c(6,60),dimnames=list(c('maand','indicator','economie','werkloosheid','financiën','spaarvermogen'),1:60))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par20 = ''
> par19 = ''
> par18 = ''
> par17 = ''
> par16 = ''
> par15 = ''
> par14 = ''
> par13 = ''
> par12 = ''
> par11 = ''
> par10 = ''
> par9 = ''
> par8 = ''
> par7 = ''
> par6 = ''
> par5 = ''
> par4 = ''
> par3 = 'Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '4'
> 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
werkloosheid maand indicator economie financi\303\253n spaarvermogen t
1 17 11 0 8 2 6 1
2 23 10 -2 3 3 7 2
3 24 9 -4 3 1 4 3
4 27 8 -4 7 1 3 4
5 31 7 -7 4 0 0 5
6 40 6 -9 -4 1 6 6
7 47 5 -13 -6 -1 3 7
8 43 4 -8 8 2 1 8
9 60 3 -13 2 2 6 9
10 64 2 -15 -1 0 5 10
11 65 1 -15 -2 1 7 11
12 65 12 -15 0 1 4 12
13 55 11 -10 10 3 3 13
14 57 10 -12 3 3 6 14
15 57 9 -11 6 1 6 15
16 57 8 -11 7 1 5 16
17 65 7 -17 -4 -2 2 17
18 69 6 -18 -5 1 3 18
19 70 5 -19 -7 1 -2 19
20 71 4 -22 -10 -1 -4 20
21 71 3 -24 -21 -4 0 21
22 73 2 -24 -22 -2 1 22
23 68 1 -20 -16 -1 4 23
24 65 12 -25 -25 -5 -3 24
25 57 11 -22 -22 -4 -3 25
26 41 10 -17 -22 -5 0 26
27 21 9 -9 -19 0 6 27
28 21 8 -11 -21 -2 -1 28
29 17 7 -13 -31 -4 0 29
30 9 6 -11 -28 -6 -1 30
31 11 5 -9 -23 -2 1 31
32 6 4 -7 -17 -2 -4 32
33 -2 3 -3 -12 -2 -1 33
34 0 2 -3 -14 1 -1 34
35 5 1 -6 -18 -2 0 35
36 3 12 -4 -16 0 3 36
37 7 11 -8 -22 -1 0 37
38 4 10 -1 -9 2 8 38
39 8 9 -2 -10 3 8 39
40 9 8 -2 -10 2 8 40
41 14 7 -1 0 3 8 41
42 12 6 1 3 4 11 42
43 12 5 2 2 5 13 43
44 7 4 2 4 5 5 44
45 15 3 -1 -3 4 12 45
46 14 2 1 0 5 13 46
47 19 1 -1 -1 6 9 47
48 39 12 -8 -7 4 11 48
49 12 11 1 2 6 7 49
50 11 10 2 3 6 12 50
51 17 9 -2 -3 3 11 51
52 16 8 -2 -5 5 10 52
53 25 7 -2 0 5 13 53
54 24 6 -2 -3 5 14 54
55 28 5 -6 -7 3 10 55
56 25 4 -4 -7 5 13 56
57 31 3 -5 -7 5 12 57
58 24 2 -2 -4 6 13 58
59 24 1 -1 -3 6 17 59
60 33 12 -5 -6 5 15 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) maand indicator economie
1.85424 -0.11454 -3.92323 0.97321
`financi\303\253n` spaarvermogen t
1.09728 0.90802 -0.02216
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-2.1369 -0.9040 0.1640 0.9198 2.1294
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.85424 0.62094 2.986 0.00427 **
maand -0.11454 0.04435 -2.583 0.01260 *
indicator -3.92323 0.03081 -127.321 < 2e-16 ***
economie 0.97321 0.03735 26.056 < 2e-16 ***
`financi\303\253n` 1.09728 0.15584 7.041 3.87e-09 ***
spaarvermogen 0.90802 0.05791 15.680 < 2e-16 ***
t -0.02216 0.01922 -1.153 0.25414
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.168 on 53 degrees of freedom
Multiple R-squared: 0.9977, Adjusted R-squared: 0.9974
F-statistic: 3839 on 6 and 53 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,] 0.3232722 0.6465444 0.67672780
[2,] 0.3800068 0.7600136 0.61999321
[3,] 0.2544043 0.5088087 0.74559567
[4,] 0.3066190 0.6132380 0.69338098
[5,] 0.6290597 0.7418806 0.37094030
[6,] 0.6159222 0.7681557 0.38407783
[7,] 0.5352091 0.9295818 0.46479090
[8,] 0.5939627 0.8120745 0.40603726
[9,] 0.5366593 0.9266814 0.46334071
[10,] 0.8275315 0.3449370 0.17246850
[11,] 0.9135910 0.1728179 0.08640897
[12,] 0.8820513 0.2358975 0.11794873
[13,] 0.8349322 0.3301356 0.16506778
[14,] 0.8074462 0.3851077 0.19255384
[15,] 0.8309574 0.3380853 0.16904263
[16,] 0.8609577 0.2780847 0.13904234
[17,] 0.8471780 0.3056440 0.15282202
[18,] 0.9023119 0.1953761 0.09768806
[19,] 0.8965242 0.2069515 0.10347577
[20,] 0.8602464 0.2795073 0.13975364
[21,] 0.8383278 0.3233443 0.16167216
[22,] 0.8164013 0.3671973 0.18359867
[23,] 0.7634257 0.4731486 0.23657431
[24,] 0.7190525 0.5618950 0.28094749
[25,] 0.6732832 0.6534336 0.32671679
[26,] 0.6541591 0.6916819 0.34584093
[27,] 0.6400241 0.7199518 0.35997588
[28,] 0.6448121 0.7103759 0.35518795
[29,] 0.5610338 0.8779323 0.43896615
[30,] 0.5234915 0.9530171 0.47650853
[31,] 0.7812789 0.4374423 0.21872114
[32,] 0.7383629 0.5232743 0.26163713
[33,] 0.7258628 0.5482744 0.27413719
[34,] 0.7089159 0.5821682 0.29108408
[35,] 0.6271637 0.7456725 0.37283627
[36,] 0.5530574 0.8938853 0.44694263
[37,] 0.5303814 0.9392371 0.46961856
[38,] 0.4215782 0.8431564 0.57842179
[39,] 0.3732132 0.7464264 0.62678678
[40,] 0.3861060 0.7722120 0.61389401
[41,] 0.2988353 0.5976706 0.70116469
> postscript(file="/var/wessaorg/rcomp/tmp/1yf771322165408.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/21n6e1322165408.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3va8i1322165408.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/45fzl1322165408.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5jx7j1322165408.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 60
Frequency = 1
1 2 3 4 5 6
0.99949712 1.92141486 -0.09880691 -0.17600989 -1.29711364 1.00435878
7 8 9 10 11 12
-0.91590135 -0.49289732 -1.90223583 0.18114322 -0.85133713 1.20836760
13 14 15 16 17 18
-0.28651777 -2.13692587 0.96886373 0.81129234 1.90075144 -1.34151095
19 20 21 22 23 24
2.12938108 -1.80245419 0.62381604 0.40206721 1.34201659 -0.48791439
25 26 27 28 29 30
-0.82751697 1.06949302 -1.49118880 1.06707202 0.14689402 0.08392870
31 32 33 34 35 36
-1.23320701 0.22168989 0.23213367 0.79432689 0.20893986 0.47244396
37 38 39 40 41 42
-1.65225791 -0.48973778 -0.62941706 1.37549056 -0.62304515 -1.60992359
43 44 45 46 47 48
0.28082576 0.50615153 -1.80226394 0.02688839 0.59604093 0.63331277
49 50 51 52 53 54
1.52860290 -1.15383109 -0.89999599 -1.33250352 -0.01497857 0.90426139
55 56 57 58 59 60
-1.16156229 -1.32609300 1.56631643 1.31869846 0.54427986 0.96638689
> postscript(file="/var/wessaorg/rcomp/tmp/6dyd81322165408.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 0.99949712 NA
1 1.92141486 0.99949712
2 -0.09880691 1.92141486
3 -0.17600989 -0.09880691
4 -1.29711364 -0.17600989
5 1.00435878 -1.29711364
6 -0.91590135 1.00435878
7 -0.49289732 -0.91590135
8 -1.90223583 -0.49289732
9 0.18114322 -1.90223583
10 -0.85133713 0.18114322
11 1.20836760 -0.85133713
12 -0.28651777 1.20836760
13 -2.13692587 -0.28651777
14 0.96886373 -2.13692587
15 0.81129234 0.96886373
16 1.90075144 0.81129234
17 -1.34151095 1.90075144
18 2.12938108 -1.34151095
19 -1.80245419 2.12938108
20 0.62381604 -1.80245419
21 0.40206721 0.62381604
22 1.34201659 0.40206721
23 -0.48791439 1.34201659
24 -0.82751697 -0.48791439
25 1.06949302 -0.82751697
26 -1.49118880 1.06949302
27 1.06707202 -1.49118880
28 0.14689402 1.06707202
29 0.08392870 0.14689402
30 -1.23320701 0.08392870
31 0.22168989 -1.23320701
32 0.23213367 0.22168989
33 0.79432689 0.23213367
34 0.20893986 0.79432689
35 0.47244396 0.20893986
36 -1.65225791 0.47244396
37 -0.48973778 -1.65225791
38 -0.62941706 -0.48973778
39 1.37549056 -0.62941706
40 -0.62304515 1.37549056
41 -1.60992359 -0.62304515
42 0.28082576 -1.60992359
43 0.50615153 0.28082576
44 -1.80226394 0.50615153
45 0.02688839 -1.80226394
46 0.59604093 0.02688839
47 0.63331277 0.59604093
48 1.52860290 0.63331277
49 -1.15383109 1.52860290
50 -0.89999599 -1.15383109
51 -1.33250352 -0.89999599
52 -0.01497857 -1.33250352
53 0.90426139 -0.01497857
54 -1.16156229 0.90426139
55 -1.32609300 -1.16156229
56 1.56631643 -1.32609300
57 1.31869846 1.56631643
58 0.54427986 1.31869846
59 0.96638689 0.54427986
60 NA 0.96638689
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.92141486 0.99949712
[2,] -0.09880691 1.92141486
[3,] -0.17600989 -0.09880691
[4,] -1.29711364 -0.17600989
[5,] 1.00435878 -1.29711364
[6,] -0.91590135 1.00435878
[7,] -0.49289732 -0.91590135
[8,] -1.90223583 -0.49289732
[9,] 0.18114322 -1.90223583
[10,] -0.85133713 0.18114322
[11,] 1.20836760 -0.85133713
[12,] -0.28651777 1.20836760
[13,] -2.13692587 -0.28651777
[14,] 0.96886373 -2.13692587
[15,] 0.81129234 0.96886373
[16,] 1.90075144 0.81129234
[17,] -1.34151095 1.90075144
[18,] 2.12938108 -1.34151095
[19,] -1.80245419 2.12938108
[20,] 0.62381604 -1.80245419
[21,] 0.40206721 0.62381604
[22,] 1.34201659 0.40206721
[23,] -0.48791439 1.34201659
[24,] -0.82751697 -0.48791439
[25,] 1.06949302 -0.82751697
[26,] -1.49118880 1.06949302
[27,] 1.06707202 -1.49118880
[28,] 0.14689402 1.06707202
[29,] 0.08392870 0.14689402
[30,] -1.23320701 0.08392870
[31,] 0.22168989 -1.23320701
[32,] 0.23213367 0.22168989
[33,] 0.79432689 0.23213367
[34,] 0.20893986 0.79432689
[35,] 0.47244396 0.20893986
[36,] -1.65225791 0.47244396
[37,] -0.48973778 -1.65225791
[38,] -0.62941706 -0.48973778
[39,] 1.37549056 -0.62941706
[40,] -0.62304515 1.37549056
[41,] -1.60992359 -0.62304515
[42,] 0.28082576 -1.60992359
[43,] 0.50615153 0.28082576
[44,] -1.80226394 0.50615153
[45,] 0.02688839 -1.80226394
[46,] 0.59604093 0.02688839
[47,] 0.63331277 0.59604093
[48,] 1.52860290 0.63331277
[49,] -1.15383109 1.52860290
[50,] -0.89999599 -1.15383109
[51,] -1.33250352 -0.89999599
[52,] -0.01497857 -1.33250352
[53,] 0.90426139 -0.01497857
[54,] -1.16156229 0.90426139
[55,] -1.32609300 -1.16156229
[56,] 1.56631643 -1.32609300
[57,] 1.31869846 1.56631643
[58,] 0.54427986 1.31869846
[59,] 0.96638689 0.54427986
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.92141486 0.99949712
2 -0.09880691 1.92141486
3 -0.17600989 -0.09880691
4 -1.29711364 -0.17600989
5 1.00435878 -1.29711364
6 -0.91590135 1.00435878
7 -0.49289732 -0.91590135
8 -1.90223583 -0.49289732
9 0.18114322 -1.90223583
10 -0.85133713 0.18114322
11 1.20836760 -0.85133713
12 -0.28651777 1.20836760
13 -2.13692587 -0.28651777
14 0.96886373 -2.13692587
15 0.81129234 0.96886373
16 1.90075144 0.81129234
17 -1.34151095 1.90075144
18 2.12938108 -1.34151095
19 -1.80245419 2.12938108
20 0.62381604 -1.80245419
21 0.40206721 0.62381604
22 1.34201659 0.40206721
23 -0.48791439 1.34201659
24 -0.82751697 -0.48791439
25 1.06949302 -0.82751697
26 -1.49118880 1.06949302
27 1.06707202 -1.49118880
28 0.14689402 1.06707202
29 0.08392870 0.14689402
30 -1.23320701 0.08392870
31 0.22168989 -1.23320701
32 0.23213367 0.22168989
33 0.79432689 0.23213367
34 0.20893986 0.79432689
35 0.47244396 0.20893986
36 -1.65225791 0.47244396
37 -0.48973778 -1.65225791
38 -0.62941706 -0.48973778
39 1.37549056 -0.62941706
40 -0.62304515 1.37549056
41 -1.60992359 -0.62304515
42 0.28082576 -1.60992359
43 0.50615153 0.28082576
44 -1.80226394 0.50615153
45 0.02688839 -1.80226394
46 0.59604093 0.02688839
47 0.63331277 0.59604093
48 1.52860290 0.63331277
49 -1.15383109 1.52860290
50 -0.89999599 -1.15383109
51 -1.33250352 -0.89999599
52 -0.01497857 -1.33250352
53 0.90426139 -0.01497857
54 -1.16156229 0.90426139
55 -1.32609300 -1.16156229
56 1.56631643 -1.32609300
57 1.31869846 1.56631643
58 0.54427986 1.31869846
59 0.96638689 0.54427986
> 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/7p9sh1322165408.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/81pxz1322165408.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/954761322165408.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/10rdln1322165408.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11ou5t1322165408.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12a5ft1322165408.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/132mdg1322165408.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14lroa1322165408.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/150hs21322165408.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/166q2c1322165408.tab")
+ }
>
> try(system("convert tmp/1yf771322165408.ps tmp/1yf771322165408.png",intern=TRUE))
character(0)
> try(system("convert tmp/21n6e1322165408.ps tmp/21n6e1322165408.png",intern=TRUE))
character(0)
> try(system("convert tmp/3va8i1322165408.ps tmp/3va8i1322165408.png",intern=TRUE))
character(0)
> try(system("convert tmp/45fzl1322165408.ps tmp/45fzl1322165408.png",intern=TRUE))
character(0)
> try(system("convert tmp/5jx7j1322165408.ps tmp/5jx7j1322165408.png",intern=TRUE))
character(0)
> try(system("convert tmp/6dyd81322165408.ps tmp/6dyd81322165408.png",intern=TRUE))
character(0)
> try(system("convert tmp/7p9sh1322165408.ps tmp/7p9sh1322165408.png",intern=TRUE))
character(0)
> try(system("convert tmp/81pxz1322165408.ps tmp/81pxz1322165408.png",intern=TRUE))
character(0)
> try(system("convert tmp/954761322165408.ps tmp/954761322165408.png",intern=TRUE))
character(0)
> try(system("convert tmp/10rdln1322165408.ps tmp/10rdln1322165408.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.328 0.493 3.853