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.
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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(101.82
+ ,107.34
+ ,93.63
+ ,101.76
+ ,101.68
+ ,107.34
+ ,93.63
+ ,102.37
+ ,101.68
+ ,107.34
+ ,93.63
+ ,102.38
+ ,102.45
+ ,107.34
+ ,96.13
+ ,102.86
+ ,102.45
+ ,107.34
+ ,96.13
+ ,102.87
+ ,102.45
+ ,107.34
+ ,96.13
+ ,102.92
+ ,102.45
+ ,107.34
+ ,96.13
+ ,102.95
+ ,102.45
+ ,107.34
+ ,96.13
+ ,103.02
+ ,102.45
+ ,112.60
+ ,96.13
+ ,104.08
+ ,102.52
+ ,112.60
+ ,96.13
+ ,104.16
+ ,102.52
+ ,112.60
+ ,96.13
+ ,104.24
+ ,102.85
+ ,112.60
+ ,96.13
+ ,104.33
+ ,102.85
+ ,112.61
+ ,96.13
+ ,104.73
+ ,102.85
+ ,112.61
+ ,96.13
+ ,104.86
+ ,103.25
+ ,112.61
+ ,96.13
+ ,105.03
+ ,103.25
+ ,112.61
+ ,98.73
+ ,105.62
+ ,103.25
+ ,112.61
+ ,98.73
+ ,105.63
+ ,103.25
+ ,112.61
+ ,98.73
+ ,105.63
+ ,104.45
+ ,112.61
+ ,98.73
+ ,105.94
+ ,104.45
+ ,112.61
+ ,98.73
+ ,106.61
+ ,104.45
+ ,118.65
+ ,98.73
+ ,107.69
+ ,104.80
+ ,118.65
+ ,98.73
+ ,107.78
+ ,104.80
+ ,118.65
+ ,98.73
+ ,107.93
+ ,105.29
+ ,118.65
+ ,98.73
+ ,108.48
+ ,105.29
+ ,114.29
+ ,98.73
+ ,108.14
+ ,105.29
+ ,114.29
+ ,98.73
+ ,108.48
+ ,105.29
+ ,114.29
+ ,98.73
+ ,108.48
+ ,106.04
+ ,114.29
+ ,101.67
+ ,108.89
+ ,105.94
+ ,114.29
+ ,101.67
+ ,108.93
+ ,105.94
+ ,114.29
+ ,101.67
+ ,109.21
+ ,105.94
+ ,114.29
+ ,101.67
+ ,109.47
+ ,106.28
+ ,114.29
+ ,101.67
+ ,109.80
+ ,106.48
+ ,123.33
+ ,101.67
+ ,111.73
+ ,107.19
+ ,123.33
+ ,101.67
+ ,111.85
+ ,108.14
+ ,123.33
+ ,101.67
+ ,112.12
+ ,108.22
+ ,123.33
+ ,101.67
+ ,112.15
+ ,108.22
+ ,123.33
+ ,101.67
+ ,112.17
+ ,108.61
+ ,123.33
+ ,101.67
+ ,112.67
+ ,108.61
+ ,123.33
+ ,101.67
+ ,112.80
+ ,108.61
+ ,123.33
+ ,107.94
+ ,113.44
+ ,108.61
+ ,123.33
+ ,107.94
+ ,113.53
+ ,109.06
+ ,123.33
+ ,107.94
+ ,114.53
+ ,109.06
+ ,123.33
+ ,107.94
+ ,114.51
+ ,112.93
+ ,123.33
+ ,107.94
+ ,115.05
+ ,115.84
+ ,129.03
+ ,107.94
+ ,116.67
+ ,118.57
+ ,128.76
+ ,107.94
+ ,117.07
+ ,118.57
+ ,128.76
+ ,107.94
+ ,116.92
+ ,118.86
+ ,128.76
+ ,107.94
+ ,117.00
+ ,118.98
+ ,128.76
+ ,107.94
+ ,117.02
+ ,119.27
+ ,128.76
+ ,107.94
+ ,117.35
+ ,119.39
+ ,128.76
+ ,107.94
+ ,117.36
+ ,119.49
+ ,128.76
+ ,110.30
+ ,117.82
+ ,119.59
+ ,128.76
+ ,110.30
+ ,117.88
+ ,120.12
+ ,128.76
+ ,110.30
+ ,118.24
+ ,120.14
+ ,128.76
+ ,110.30
+ ,118.50
+ ,120.14
+ ,128.76
+ ,110.30
+ ,118.80
+ ,120.14
+ ,132.63
+ ,110.30
+ ,119.76
+ ,120.14
+ ,132.63
+ ,110.30
+ ,120.09)
+ ,dim=c(4
+ ,58)
+ ,dimnames=list(c('Bioscoop'
+ ,'Schouwburgabonnement'
+ ,'Daguitstap'
+ ,'Cultuuruitgaven')
+ ,1:58))
> y <- array(NA,dim=c(4,58),dimnames=list(c('Bioscoop','Schouwburgabonnement','Daguitstap','Cultuuruitgaven'),1:58))
> 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 = '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
Cultuuruitgaven Bioscoop Schouwburgabonnement Daguitstap t
1 101.76 101.82 107.34 93.63 1
2 102.37 101.68 107.34 93.63 2
3 102.38 101.68 107.34 93.63 3
4 102.86 102.45 107.34 96.13 4
5 102.87 102.45 107.34 96.13 5
6 102.92 102.45 107.34 96.13 6
7 102.95 102.45 107.34 96.13 7
8 103.02 102.45 107.34 96.13 8
9 104.08 102.45 112.60 96.13 9
10 104.16 102.52 112.60 96.13 10
11 104.24 102.52 112.60 96.13 11
12 104.33 102.85 112.60 96.13 12
13 104.73 102.85 112.61 96.13 13
14 104.86 102.85 112.61 96.13 14
15 105.03 103.25 112.61 96.13 15
16 105.62 103.25 112.61 98.73 16
17 105.63 103.25 112.61 98.73 17
18 105.63 103.25 112.61 98.73 18
19 105.94 104.45 112.61 98.73 19
20 106.61 104.45 112.61 98.73 20
21 107.69 104.45 118.65 98.73 21
22 107.78 104.80 118.65 98.73 22
23 107.93 104.80 118.65 98.73 23
24 108.48 105.29 118.65 98.73 24
25 108.14 105.29 114.29 98.73 25
26 108.48 105.29 114.29 98.73 26
27 108.48 105.29 114.29 98.73 27
28 108.89 106.04 114.29 101.67 28
29 108.93 105.94 114.29 101.67 29
30 109.21 105.94 114.29 101.67 30
31 109.47 105.94 114.29 101.67 31
32 109.80 106.28 114.29 101.67 32
33 111.73 106.48 123.33 101.67 33
34 111.85 107.19 123.33 101.67 34
35 112.12 108.14 123.33 101.67 35
36 112.15 108.22 123.33 101.67 36
37 112.17 108.22 123.33 101.67 37
38 112.67 108.61 123.33 101.67 38
39 112.80 108.61 123.33 101.67 39
40 113.44 108.61 123.33 107.94 40
41 113.53 108.61 123.33 107.94 41
42 114.53 109.06 123.33 107.94 42
43 114.51 109.06 123.33 107.94 43
44 115.05 112.93 123.33 107.94 44
45 116.67 115.84 129.03 107.94 45
46 117.07 118.57 128.76 107.94 46
47 116.92 118.57 128.76 107.94 47
48 117.00 118.86 128.76 107.94 48
49 117.02 118.98 128.76 107.94 49
50 117.35 119.27 128.76 107.94 50
51 117.36 119.39 128.76 107.94 51
52 117.82 119.49 128.76 110.30 52
53 117.88 119.59 128.76 110.30 53
54 118.24 120.12 128.76 110.30 54
55 118.50 120.14 128.76 110.30 55
56 118.80 120.14 128.76 110.30 56
57 119.76 120.14 132.63 110.30 57
58 120.09 120.14 132.63 110.30 58
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Bioscoop Schouwburgabonnement
61.3523 0.1049 0.1673
Daguitstap t
0.1211 0.1788
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.56488 -0.21654 -0.03583 0.21662 0.69946
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 61.35230 3.41955 17.942 < 2e-16 ***
Bioscoop 0.10486 0.01788 5.866 2.96e-07 ***
Schouwburgabonnement 0.16729 0.01892 8.842 5.19e-12 ***
Daguitstap 0.12113 0.03164 3.828 0.000343 ***
t 0.17877 0.01269 14.086 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.3004 on 53 degrees of freedom
Multiple R-squared: 0.9973, Adjusted R-squared: 0.9971
F-statistic: 4896 on 4 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,] 1.067715e-03 0.0021354308 0.99893228
[2,] 8.291729e-05 0.0001658346 0.99991708
[3,] 2.025769e-02 0.0405153879 0.97974231
[4,] 1.260243e-02 0.0252048682 0.98739757
[5,] 1.090404e-01 0.2180807661 0.89095962
[6,] 1.726171e-01 0.3452341002 0.82738295
[7,] 1.430867e-01 0.2861733531 0.85691332
[8,] 9.792317e-02 0.1958463321 0.90207683
[9,] 1.387264e-01 0.2774528175 0.86127359
[10,] 9.364010e-02 0.1872802066 0.90635990
[11,] 7.756733e-02 0.1551346527 0.92243267
[12,] 6.762135e-02 0.1352426930 0.93237865
[13,] 1.738073e-01 0.3476146040 0.82619270
[14,] 2.342672e-01 0.4685344705 0.76573276
[15,] 2.217361e-01 0.4434722306 0.77826388
[16,] 2.846294e-01 0.5692587577 0.71537062
[17,] 3.315915e-01 0.6631829908 0.66840850
[18,] 4.147600e-01 0.8295199747 0.58524001
[19,] 5.452794e-01 0.9094411021 0.45472055
[20,] 5.040716e-01 0.9918567453 0.49592837
[21,] 4.246314e-01 0.8492627754 0.57536861
[22,] 3.651124e-01 0.7302247991 0.63488760
[23,] 3.055973e-01 0.6111945190 0.69440274
[24,] 2.655129e-01 0.5310258389 0.73448708
[25,] 2.802944e-01 0.5605887357 0.71970563
[26,] 5.306984e-01 0.9386032828 0.46930164
[27,] 4.528629e-01 0.9057257556 0.54713712
[28,] 4.218340e-01 0.8436679807 0.57816601
[29,] 4.012530e-01 0.8025059039 0.59874705
[30,] 4.492862e-01 0.8985723192 0.55071384
[31,] 3.729235e-01 0.7458470100 0.62707650
[32,] 3.329277e-01 0.6658553360 0.66707233
[33,] 4.039516e-01 0.8079032516 0.59604837
[34,] 8.692097e-01 0.2615806095 0.13079030
[35,] 8.708472e-01 0.2583055910 0.12915280
[36,] 8.881108e-01 0.2237784578 0.11188923
[37,] 8.985371e-01 0.2029257877 0.10146289
[38,] 8.582299e-01 0.2835402236 0.14177011
[39,] 9.683574e-01 0.0632852490 0.03164262
[40,] 9.799182e-01 0.0401636505 0.02008183
[41,] 9.857950e-01 0.0284100308 0.01420502
[42,] 9.629507e-01 0.0740986048 0.03704930
[43,] 9.669439e-01 0.0661122263 0.03305611
> postscript(file="/var/wessaorg/rcomp/tmp/1bpmn1321907889.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/26ka91321907889.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3hc9z1321907889.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4znqd1321907889.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5khdp1321907889.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 58
Frequency = 1
1 2 3 4 5 6
0.253553079 0.699463566 0.530693617 0.448359083 0.279589134 0.150819184
7 8 9 10 11 12
0.002049235 -0.106720715 -0.105450881 -0.211561049 -0.310330998 -0.433704835
13 14 15 16 17 18
-0.214147712 -0.262917662 -0.313631716 -0.217336735 -0.386106685 -0.564876634
19 20 21 22 23 24
-0.559478899 -0.068248848 -0.177467411 -0.302938453 -0.331708402 -0.011859880
25 26 27 28 29 30
0.198766852 0.359996902 0.181226952 -0.022307080 -0.150591003 -0.049360953
31 32 33 34 35 36
0.031869098 0.147446659 0.365377593 0.232156857 0.223769658 0.066610888
37 38 39 40 41 42
-0.092159062 0.188175487 0.139405537 -0.158842445 -0.247612395 0.526430538
43 44 45 46 47 48
0.327660588 0.283081424 0.465599055 0.445729651 0.116959701 -0.012219724
49 50 51 52 53 54
-0.183572905 -0.062752331 -0.244105512 -0.259225628 -0.388481604 -0.262827492
55 56 57 58
-0.183694647 -0.062464596 0.071342253 0.222572303
> postscript(file="/var/wessaorg/rcomp/tmp/6cmnc1321907889.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 = 58
Frequency = 1
lag(myerror, k = 1) myerror
0 0.253553079 NA
1 0.699463566 0.253553079
2 0.530693617 0.699463566
3 0.448359083 0.530693617
4 0.279589134 0.448359083
5 0.150819184 0.279589134
6 0.002049235 0.150819184
7 -0.106720715 0.002049235
8 -0.105450881 -0.106720715
9 -0.211561049 -0.105450881
10 -0.310330998 -0.211561049
11 -0.433704835 -0.310330998
12 -0.214147712 -0.433704835
13 -0.262917662 -0.214147712
14 -0.313631716 -0.262917662
15 -0.217336735 -0.313631716
16 -0.386106685 -0.217336735
17 -0.564876634 -0.386106685
18 -0.559478899 -0.564876634
19 -0.068248848 -0.559478899
20 -0.177467411 -0.068248848
21 -0.302938453 -0.177467411
22 -0.331708402 -0.302938453
23 -0.011859880 -0.331708402
24 0.198766852 -0.011859880
25 0.359996902 0.198766852
26 0.181226952 0.359996902
27 -0.022307080 0.181226952
28 -0.150591003 -0.022307080
29 -0.049360953 -0.150591003
30 0.031869098 -0.049360953
31 0.147446659 0.031869098
32 0.365377593 0.147446659
33 0.232156857 0.365377593
34 0.223769658 0.232156857
35 0.066610888 0.223769658
36 -0.092159062 0.066610888
37 0.188175487 -0.092159062
38 0.139405537 0.188175487
39 -0.158842445 0.139405537
40 -0.247612395 -0.158842445
41 0.526430538 -0.247612395
42 0.327660588 0.526430538
43 0.283081424 0.327660588
44 0.465599055 0.283081424
45 0.445729651 0.465599055
46 0.116959701 0.445729651
47 -0.012219724 0.116959701
48 -0.183572905 -0.012219724
49 -0.062752331 -0.183572905
50 -0.244105512 -0.062752331
51 -0.259225628 -0.244105512
52 -0.388481604 -0.259225628
53 -0.262827492 -0.388481604
54 -0.183694647 -0.262827492
55 -0.062464596 -0.183694647
56 0.071342253 -0.062464596
57 0.222572303 0.071342253
58 NA 0.222572303
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.699463566 0.253553079
[2,] 0.530693617 0.699463566
[3,] 0.448359083 0.530693617
[4,] 0.279589134 0.448359083
[5,] 0.150819184 0.279589134
[6,] 0.002049235 0.150819184
[7,] -0.106720715 0.002049235
[8,] -0.105450881 -0.106720715
[9,] -0.211561049 -0.105450881
[10,] -0.310330998 -0.211561049
[11,] -0.433704835 -0.310330998
[12,] -0.214147712 -0.433704835
[13,] -0.262917662 -0.214147712
[14,] -0.313631716 -0.262917662
[15,] -0.217336735 -0.313631716
[16,] -0.386106685 -0.217336735
[17,] -0.564876634 -0.386106685
[18,] -0.559478899 -0.564876634
[19,] -0.068248848 -0.559478899
[20,] -0.177467411 -0.068248848
[21,] -0.302938453 -0.177467411
[22,] -0.331708402 -0.302938453
[23,] -0.011859880 -0.331708402
[24,] 0.198766852 -0.011859880
[25,] 0.359996902 0.198766852
[26,] 0.181226952 0.359996902
[27,] -0.022307080 0.181226952
[28,] -0.150591003 -0.022307080
[29,] -0.049360953 -0.150591003
[30,] 0.031869098 -0.049360953
[31,] 0.147446659 0.031869098
[32,] 0.365377593 0.147446659
[33,] 0.232156857 0.365377593
[34,] 0.223769658 0.232156857
[35,] 0.066610888 0.223769658
[36,] -0.092159062 0.066610888
[37,] 0.188175487 -0.092159062
[38,] 0.139405537 0.188175487
[39,] -0.158842445 0.139405537
[40,] -0.247612395 -0.158842445
[41,] 0.526430538 -0.247612395
[42,] 0.327660588 0.526430538
[43,] 0.283081424 0.327660588
[44,] 0.465599055 0.283081424
[45,] 0.445729651 0.465599055
[46,] 0.116959701 0.445729651
[47,] -0.012219724 0.116959701
[48,] -0.183572905 -0.012219724
[49,] -0.062752331 -0.183572905
[50,] -0.244105512 -0.062752331
[51,] -0.259225628 -0.244105512
[52,] -0.388481604 -0.259225628
[53,] -0.262827492 -0.388481604
[54,] -0.183694647 -0.262827492
[55,] -0.062464596 -0.183694647
[56,] 0.071342253 -0.062464596
[57,] 0.222572303 0.071342253
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.699463566 0.253553079
2 0.530693617 0.699463566
3 0.448359083 0.530693617
4 0.279589134 0.448359083
5 0.150819184 0.279589134
6 0.002049235 0.150819184
7 -0.106720715 0.002049235
8 -0.105450881 -0.106720715
9 -0.211561049 -0.105450881
10 -0.310330998 -0.211561049
11 -0.433704835 -0.310330998
12 -0.214147712 -0.433704835
13 -0.262917662 -0.214147712
14 -0.313631716 -0.262917662
15 -0.217336735 -0.313631716
16 -0.386106685 -0.217336735
17 -0.564876634 -0.386106685
18 -0.559478899 -0.564876634
19 -0.068248848 -0.559478899
20 -0.177467411 -0.068248848
21 -0.302938453 -0.177467411
22 -0.331708402 -0.302938453
23 -0.011859880 -0.331708402
24 0.198766852 -0.011859880
25 0.359996902 0.198766852
26 0.181226952 0.359996902
27 -0.022307080 0.181226952
28 -0.150591003 -0.022307080
29 -0.049360953 -0.150591003
30 0.031869098 -0.049360953
31 0.147446659 0.031869098
32 0.365377593 0.147446659
33 0.232156857 0.365377593
34 0.223769658 0.232156857
35 0.066610888 0.223769658
36 -0.092159062 0.066610888
37 0.188175487 -0.092159062
38 0.139405537 0.188175487
39 -0.158842445 0.139405537
40 -0.247612395 -0.158842445
41 0.526430538 -0.247612395
42 0.327660588 0.526430538
43 0.283081424 0.327660588
44 0.465599055 0.283081424
45 0.445729651 0.465599055
46 0.116959701 0.445729651
47 -0.012219724 0.116959701
48 -0.183572905 -0.012219724
49 -0.062752331 -0.183572905
50 -0.244105512 -0.062752331
51 -0.259225628 -0.244105512
52 -0.388481604 -0.259225628
53 -0.262827492 -0.388481604
54 -0.183694647 -0.262827492
55 -0.062464596 -0.183694647
56 0.071342253 -0.062464596
57 0.222572303 0.071342253
> 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/7dc6g1321907889.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/8l98x1321907889.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/9yvk51321907889.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/10gufy1321907889.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/117ox71321907889.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12cnkx1321907889.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/134ynh1321907889.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14kauy1321907889.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/15n1f81321907889.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/16ao591321907889.tab")
+ }
>
> try(system("convert tmp/1bpmn1321907889.ps tmp/1bpmn1321907889.png",intern=TRUE))
character(0)
> try(system("convert tmp/26ka91321907889.ps tmp/26ka91321907889.png",intern=TRUE))
character(0)
> try(system("convert tmp/3hc9z1321907889.ps tmp/3hc9z1321907889.png",intern=TRUE))
character(0)
> try(system("convert tmp/4znqd1321907889.ps tmp/4znqd1321907889.png",intern=TRUE))
character(0)
> try(system("convert tmp/5khdp1321907889.ps tmp/5khdp1321907889.png",intern=TRUE))
character(0)
> try(system("convert tmp/6cmnc1321907889.ps tmp/6cmnc1321907889.png",intern=TRUE))
character(0)
> try(system("convert tmp/7dc6g1321907889.ps tmp/7dc6g1321907889.png",intern=TRUE))
character(0)
> try(system("convert tmp/8l98x1321907889.ps tmp/8l98x1321907889.png",intern=TRUE))
character(0)
> try(system("convert tmp/9yvk51321907889.ps tmp/9yvk51321907889.png",intern=TRUE))
character(0)
> try(system("convert tmp/10gufy1321907889.ps tmp/10gufy1321907889.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.268 0.514 3.799