R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-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 '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
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Type 'q()' to quit R.
> x <- array(list(15579,16348,15928,16171,15937,15713,15594,15683,16438,17032,17696,17745,19394,20148,20108,18584,18441,18391,19178,18079,18483,19644,19195,19650,20830,23595,22937,21814,21928,21777,21383,21467,22052,22680,24320,24977,25204,25739,26434,27525,30695,32436,30160,30236,31293,31077,32226,33865,32810,32242,32700,32819,33947,34148,35261,39506,41591,39148,41216,40225,41126,42362,40740,40256,39804,41002,41702,42254,43605,43271),dim=c(1,70),dimnames=list(c('Goudprijs'),1:70))
> y <- array(NA,dim=c(1,70),dimnames=list(c('Goudprijs'),1:70))
> 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 = 'Include Monthly Dummies'
> par1 = '1'
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, 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
Goudprijs M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 15579 1 0 0 0 0 0 0 0 0 0 0 1
2 16348 0 1 0 0 0 0 0 0 0 0 0 2
3 15928 0 0 1 0 0 0 0 0 0 0 0 3
4 16171 0 0 0 1 0 0 0 0 0 0 0 4
5 15937 0 0 0 0 1 0 0 0 0 0 0 5
6 15713 0 0 0 0 0 1 0 0 0 0 0 6
7 15594 0 0 0 0 0 0 1 0 0 0 0 7
8 15683 0 0 0 0 0 0 0 1 0 0 0 8
9 16438 0 0 0 0 0 0 0 0 1 0 0 9
10 17032 0 0 0 0 0 0 0 0 0 1 0 10
11 17696 0 0 0 0 0 0 0 0 0 0 1 11
12 17745 0 0 0 0 0 0 0 0 0 0 0 12
13 19394 1 0 0 0 0 0 0 0 0 0 0 13
14 20148 0 1 0 0 0 0 0 0 0 0 0 14
15 20108 0 0 1 0 0 0 0 0 0 0 0 15
16 18584 0 0 0 1 0 0 0 0 0 0 0 16
17 18441 0 0 0 0 1 0 0 0 0 0 0 17
18 18391 0 0 0 0 0 1 0 0 0 0 0 18
19 19178 0 0 0 0 0 0 1 0 0 0 0 19
20 18079 0 0 0 0 0 0 0 1 0 0 0 20
21 18483 0 0 0 0 0 0 0 0 1 0 0 21
22 19644 0 0 0 0 0 0 0 0 0 1 0 22
23 19195 0 0 0 0 0 0 0 0 0 0 1 23
24 19650 0 0 0 0 0 0 0 0 0 0 0 24
25 20830 1 0 0 0 0 0 0 0 0 0 0 25
26 23595 0 1 0 0 0 0 0 0 0 0 0 26
27 22937 0 0 1 0 0 0 0 0 0 0 0 27
28 21814 0 0 0 1 0 0 0 0 0 0 0 28
29 21928 0 0 0 0 1 0 0 0 0 0 0 29
30 21777 0 0 0 0 0 1 0 0 0 0 0 30
31 21383 0 0 0 0 0 0 1 0 0 0 0 31
32 21467 0 0 0 0 0 0 0 1 0 0 0 32
33 22052 0 0 0 0 0 0 0 0 1 0 0 33
34 22680 0 0 0 0 0 0 0 0 0 1 0 34
35 24320 0 0 0 0 0 0 0 0 0 0 1 35
36 24977 0 0 0 0 0 0 0 0 0 0 0 36
37 25204 1 0 0 0 0 0 0 0 0 0 0 37
38 25739 0 1 0 0 0 0 0 0 0 0 0 38
39 26434 0 0 1 0 0 0 0 0 0 0 0 39
40 27525 0 0 0 1 0 0 0 0 0 0 0 40
41 30695 0 0 0 0 1 0 0 0 0 0 0 41
42 32436 0 0 0 0 0 1 0 0 0 0 0 42
43 30160 0 0 0 0 0 0 1 0 0 0 0 43
44 30236 0 0 0 0 0 0 0 1 0 0 0 44
45 31293 0 0 0 0 0 0 0 0 1 0 0 45
46 31077 0 0 0 0 0 0 0 0 0 1 0 46
47 32226 0 0 0 0 0 0 0 0 0 0 1 47
48 33865 0 0 0 0 0 0 0 0 0 0 0 48
49 32810 1 0 0 0 0 0 0 0 0 0 0 49
50 32242 0 1 0 0 0 0 0 0 0 0 0 50
51 32700 0 0 1 0 0 0 0 0 0 0 0 51
52 32819 0 0 0 1 0 0 0 0 0 0 0 52
53 33947 0 0 0 0 1 0 0 0 0 0 0 53
54 34148 0 0 0 0 0 1 0 0 0 0 0 54
55 35261 0 0 0 0 0 0 1 0 0 0 0 55
56 39506 0 0 0 0 0 0 0 1 0 0 0 56
57 41591 0 0 0 0 0 0 0 0 1 0 0 57
58 39148 0 0 0 0 0 0 0 0 0 1 0 58
59 41216 0 0 0 0 0 0 0 0 0 0 1 59
60 40225 0 0 0 0 0 0 0 0 0 0 0 60
61 41126 1 0 0 0 0 0 0 0 0 0 0 61
62 42362 0 1 0 0 0 0 0 0 0 0 0 62
63 40740 0 0 1 0 0 0 0 0 0 0 0 63
64 40256 0 0 0 1 0 0 0 0 0 0 0 64
65 39804 0 0 0 0 1 0 0 0 0 0 0 65
66 41002 0 0 0 0 0 1 0 0 0 0 0 66
67 41702 0 0 0 0 0 0 1 0 0 0 0 67
68 42254 0 0 0 0 0 0 0 1 0 0 0 68
69 43605 0 0 0 0 0 0 0 0 1 0 0 69
70 43271 0 0 0 0 0 0 0 0 0 1 0 70
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) M1 M2 M3 M4 M5
11304.02 752.04 1223.09 514.46 -209.32 -56.28
M6 M7 M8 M9 M10 M11
-47.90 -523.52 -309.81 285.57 -260.22 82.32
t
444.12
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-4193.6 -1755.5 9.9 1516.3 4686.5
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 11304.02 1151.51 9.817 7.38e-14 ***
M1 752.04 1407.11 0.534 0.595
M2 1223.09 1406.50 0.870 0.388
M3 514.46 1406.02 0.366 0.716
M4 -209.32 1405.68 -0.149 0.882
M5 -56.28 1405.47 -0.040 0.968
M6 -47.90 1405.41 -0.034 0.973
M7 -523.52 1405.47 -0.372 0.711
M8 -309.81 1405.68 -0.220 0.826
M9 285.57 1406.02 0.203 0.840
M10 -260.22 1406.50 -0.185 0.854
M11 82.32 1467.96 0.056 0.955
t 444.12 13.85 32.065 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2321 on 57 degrees of freedom
Multiple R-squared: 0.948, Adjusted R-squared: 0.9371
F-statistic: 86.6 on 12 and 57 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 3.741519e-02 7.483037e-02 0.9625848
[2,] 2.077737e-02 4.155474e-02 0.9792226
[3,] 8.071879e-03 1.614376e-02 0.9919281
[4,] 2.884448e-03 5.768895e-03 0.9971156
[5,] 1.441057e-03 2.882113e-03 0.9985589
[6,] 9.778045e-04 1.955609e-03 0.9990222
[7,] 3.575651e-04 7.151303e-04 0.9996424
[8,] 4.410008e-04 8.820015e-04 0.9995590
[9,] 2.292295e-04 4.584589e-04 0.9997708
[10,] 1.150889e-04 2.301778e-04 0.9998849
[11,] 1.817756e-04 3.635511e-04 0.9998182
[12,] 1.315561e-04 2.631122e-04 0.9998684
[13,] 5.567727e-05 1.113545e-04 0.9999443
[14,] 2.140982e-05 4.281965e-05 0.9999786
[15,] 7.321367e-06 1.464273e-05 0.9999927
[16,] 2.578622e-06 5.157244e-06 0.9999974
[17,] 1.058052e-06 2.116104e-06 0.9999989
[18,] 7.313893e-07 1.462779e-06 0.9999993
[19,] 2.926206e-07 5.852411e-07 0.9999997
[20,] 9.696923e-07 1.939385e-06 0.9999990
[21,] 4.714765e-06 9.429531e-06 0.9999953
[22,] 3.138925e-06 6.277850e-06 0.9999969
[23,] 2.246245e-06 4.492491e-06 0.9999978
[24,] 1.149359e-06 2.298718e-06 0.9999989
[25,] 1.225727e-05 2.451453e-05 0.9999877
[26,] 1.638595e-02 3.277189e-02 0.9836141
[27,] 4.551636e-01 9.103273e-01 0.5448364
[28,] 5.442234e-01 9.115533e-01 0.4557766
[29,] 5.754269e-01 8.491462e-01 0.4245731
[30,] 6.209190e-01 7.581620e-01 0.3790810
[31,] 5.749179e-01 8.501642e-01 0.4250821
[32,] 6.124867e-01 7.750266e-01 0.3875133
[33,] 5.889560e-01 8.220879e-01 0.4110440
[34,] 5.486427e-01 9.027146e-01 0.4513573
[35,] 7.075132e-01 5.849735e-01 0.2924868
[36,] 7.208886e-01 5.582227e-01 0.2791114
[37,] 7.250310e-01 5.499380e-01 0.2749690
[38,] 6.221230e-01 7.557541e-01 0.3778770
[39,] 6.521847e-01 6.956307e-01 0.3478153
> postscript(file="/var/wessaorg/rcomp/tmp/1grn71355057851.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/2q26q1355057851.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/394qy1355057851.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4ff1i1355057851.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5kkf71355057851.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$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 = 70
Frequency = 1
1 2 3 4 5 6
3078.81410 2932.64744 2777.14744 3299.81410 2468.64744 1792.14744
7 8 9 10 11 12
1704.64744 1135.81410 851.31410 1546.98077 1424.31795 1111.51795
13 14 15 16 17 18
1564.35513 1403.18846 1627.68846 383.35513 -356.81154 -859.31154
19 20 21 22 23 24
-40.81154 -1797.64487 -2433.14487 -1170.47821 -2406.14103 -2312.94103
25 26 27 28 29 30
-2329.10385 -479.27051 -872.77051 -1716.10385 -2199.27051 -2802.77051
31 32 33 34 35 36
-3165.27051 -3739.10385 -4193.60385 -3463.93718 -2610.60000 -2315.40000
37 38 39 40 41 42
-3284.56282 -3664.72949 -2705.22949 -1334.56282 1238.27051 2526.77051
43 44 45 46 47 48
282.27051 -299.56282 -282.06282 -396.39615 -34.05897 1243.14103
49 50 51 52 53 54
-1008.02179 -2491.18846 -1768.68846 -1370.02179 -839.18846 -1090.68846
55 56 57 58 59 60
53.81154 3640.97821 4686.47821 2345.14487 3626.48205 2273.68205
61 62 63 64 65 66
1978.51923 2299.35256 941.85256 737.51923 -311.64744 433.85256
67 68 69 70
1165.35256 1059.51923 1371.01923 1138.68590
> postscript(file="/var/wessaorg/rcomp/tmp/6omb51355057851.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 = 70
Frequency = 1
lag(myerror, k = 1) myerror
0 3078.81410 NA
1 2932.64744 3078.81410
2 2777.14744 2932.64744
3 3299.81410 2777.14744
4 2468.64744 3299.81410
5 1792.14744 2468.64744
6 1704.64744 1792.14744
7 1135.81410 1704.64744
8 851.31410 1135.81410
9 1546.98077 851.31410
10 1424.31795 1546.98077
11 1111.51795 1424.31795
12 1564.35513 1111.51795
13 1403.18846 1564.35513
14 1627.68846 1403.18846
15 383.35513 1627.68846
16 -356.81154 383.35513
17 -859.31154 -356.81154
18 -40.81154 -859.31154
19 -1797.64487 -40.81154
20 -2433.14487 -1797.64487
21 -1170.47821 -2433.14487
22 -2406.14103 -1170.47821
23 -2312.94103 -2406.14103
24 -2329.10385 -2312.94103
25 -479.27051 -2329.10385
26 -872.77051 -479.27051
27 -1716.10385 -872.77051
28 -2199.27051 -1716.10385
29 -2802.77051 -2199.27051
30 -3165.27051 -2802.77051
31 -3739.10385 -3165.27051
32 -4193.60385 -3739.10385
33 -3463.93718 -4193.60385
34 -2610.60000 -3463.93718
35 -2315.40000 -2610.60000
36 -3284.56282 -2315.40000
37 -3664.72949 -3284.56282
38 -2705.22949 -3664.72949
39 -1334.56282 -2705.22949
40 1238.27051 -1334.56282
41 2526.77051 1238.27051
42 282.27051 2526.77051
43 -299.56282 282.27051
44 -282.06282 -299.56282
45 -396.39615 -282.06282
46 -34.05897 -396.39615
47 1243.14103 -34.05897
48 -1008.02179 1243.14103
49 -2491.18846 -1008.02179
50 -1768.68846 -2491.18846
51 -1370.02179 -1768.68846
52 -839.18846 -1370.02179
53 -1090.68846 -839.18846
54 53.81154 -1090.68846
55 3640.97821 53.81154
56 4686.47821 3640.97821
57 2345.14487 4686.47821
58 3626.48205 2345.14487
59 2273.68205 3626.48205
60 1978.51923 2273.68205
61 2299.35256 1978.51923
62 941.85256 2299.35256
63 737.51923 941.85256
64 -311.64744 737.51923
65 433.85256 -311.64744
66 1165.35256 433.85256
67 1059.51923 1165.35256
68 1371.01923 1059.51923
69 1138.68590 1371.01923
70 NA 1138.68590
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 2932.64744 3078.81410
[2,] 2777.14744 2932.64744
[3,] 3299.81410 2777.14744
[4,] 2468.64744 3299.81410
[5,] 1792.14744 2468.64744
[6,] 1704.64744 1792.14744
[7,] 1135.81410 1704.64744
[8,] 851.31410 1135.81410
[9,] 1546.98077 851.31410
[10,] 1424.31795 1546.98077
[11,] 1111.51795 1424.31795
[12,] 1564.35513 1111.51795
[13,] 1403.18846 1564.35513
[14,] 1627.68846 1403.18846
[15,] 383.35513 1627.68846
[16,] -356.81154 383.35513
[17,] -859.31154 -356.81154
[18,] -40.81154 -859.31154
[19,] -1797.64487 -40.81154
[20,] -2433.14487 -1797.64487
[21,] -1170.47821 -2433.14487
[22,] -2406.14103 -1170.47821
[23,] -2312.94103 -2406.14103
[24,] -2329.10385 -2312.94103
[25,] -479.27051 -2329.10385
[26,] -872.77051 -479.27051
[27,] -1716.10385 -872.77051
[28,] -2199.27051 -1716.10385
[29,] -2802.77051 -2199.27051
[30,] -3165.27051 -2802.77051
[31,] -3739.10385 -3165.27051
[32,] -4193.60385 -3739.10385
[33,] -3463.93718 -4193.60385
[34,] -2610.60000 -3463.93718
[35,] -2315.40000 -2610.60000
[36,] -3284.56282 -2315.40000
[37,] -3664.72949 -3284.56282
[38,] -2705.22949 -3664.72949
[39,] -1334.56282 -2705.22949
[40,] 1238.27051 -1334.56282
[41,] 2526.77051 1238.27051
[42,] 282.27051 2526.77051
[43,] -299.56282 282.27051
[44,] -282.06282 -299.56282
[45,] -396.39615 -282.06282
[46,] -34.05897 -396.39615
[47,] 1243.14103 -34.05897
[48,] -1008.02179 1243.14103
[49,] -2491.18846 -1008.02179
[50,] -1768.68846 -2491.18846
[51,] -1370.02179 -1768.68846
[52,] -839.18846 -1370.02179
[53,] -1090.68846 -839.18846
[54,] 53.81154 -1090.68846
[55,] 3640.97821 53.81154
[56,] 4686.47821 3640.97821
[57,] 2345.14487 4686.47821
[58,] 3626.48205 2345.14487
[59,] 2273.68205 3626.48205
[60,] 1978.51923 2273.68205
[61,] 2299.35256 1978.51923
[62,] 941.85256 2299.35256
[63,] 737.51923 941.85256
[64,] -311.64744 737.51923
[65,] 433.85256 -311.64744
[66,] 1165.35256 433.85256
[67,] 1059.51923 1165.35256
[68,] 1371.01923 1059.51923
[69,] 1138.68590 1371.01923
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 2932.64744 3078.81410
2 2777.14744 2932.64744
3 3299.81410 2777.14744
4 2468.64744 3299.81410
5 1792.14744 2468.64744
6 1704.64744 1792.14744
7 1135.81410 1704.64744
8 851.31410 1135.81410
9 1546.98077 851.31410
10 1424.31795 1546.98077
11 1111.51795 1424.31795
12 1564.35513 1111.51795
13 1403.18846 1564.35513
14 1627.68846 1403.18846
15 383.35513 1627.68846
16 -356.81154 383.35513
17 -859.31154 -356.81154
18 -40.81154 -859.31154
19 -1797.64487 -40.81154
20 -2433.14487 -1797.64487
21 -1170.47821 -2433.14487
22 -2406.14103 -1170.47821
23 -2312.94103 -2406.14103
24 -2329.10385 -2312.94103
25 -479.27051 -2329.10385
26 -872.77051 -479.27051
27 -1716.10385 -872.77051
28 -2199.27051 -1716.10385
29 -2802.77051 -2199.27051
30 -3165.27051 -2802.77051
31 -3739.10385 -3165.27051
32 -4193.60385 -3739.10385
33 -3463.93718 -4193.60385
34 -2610.60000 -3463.93718
35 -2315.40000 -2610.60000
36 -3284.56282 -2315.40000
37 -3664.72949 -3284.56282
38 -2705.22949 -3664.72949
39 -1334.56282 -2705.22949
40 1238.27051 -1334.56282
41 2526.77051 1238.27051
42 282.27051 2526.77051
43 -299.56282 282.27051
44 -282.06282 -299.56282
45 -396.39615 -282.06282
46 -34.05897 -396.39615
47 1243.14103 -34.05897
48 -1008.02179 1243.14103
49 -2491.18846 -1008.02179
50 -1768.68846 -2491.18846
51 -1370.02179 -1768.68846
52 -839.18846 -1370.02179
53 -1090.68846 -839.18846
54 53.81154 -1090.68846
55 3640.97821 53.81154
56 4686.47821 3640.97821
57 2345.14487 4686.47821
58 3626.48205 2345.14487
59 2273.68205 3626.48205
60 1978.51923 2273.68205
61 2299.35256 1978.51923
62 941.85256 2299.35256
63 737.51923 941.85256
64 -311.64744 737.51923
65 433.85256 -311.64744
66 1165.35256 433.85256
67 1059.51923 1165.35256
68 1371.01923 1059.51923
69 1138.68590 1371.01923
> 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/7d83i1355057851.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/89yep1355057851.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/9dn4a1355057851.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/10ahpv1355057851.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11l3u01355057851.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12h6a71355057851.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$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$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13jzp81355057851.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$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/14z7y51355057851.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/15rqu21355057851.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/16c9q01355057851.tab")
+ }
>
> try(system("convert tmp/1grn71355057851.ps tmp/1grn71355057851.png",intern=TRUE))
character(0)
> try(system("convert tmp/2q26q1355057851.ps tmp/2q26q1355057851.png",intern=TRUE))
character(0)
> try(system("convert tmp/394qy1355057851.ps tmp/394qy1355057851.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ff1i1355057851.ps tmp/4ff1i1355057851.png",intern=TRUE))
character(0)
> try(system("convert tmp/5kkf71355057851.ps tmp/5kkf71355057851.png",intern=TRUE))
character(0)
> try(system("convert tmp/6omb51355057851.ps tmp/6omb51355057851.png",intern=TRUE))
character(0)
> try(system("convert tmp/7d83i1355057851.ps tmp/7d83i1355057851.png",intern=TRUE))
character(0)
> try(system("convert tmp/89yep1355057851.ps tmp/89yep1355057851.png",intern=TRUE))
character(0)
> try(system("convert tmp/9dn4a1355057851.ps tmp/9dn4a1355057851.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ahpv1355057851.ps tmp/10ahpv1355057851.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
5.724 1.102 6.859