R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
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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
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(102.9
+ ,127.5
+ ,112.7
+ ,97
+ ,95.1
+ ,97.4
+ ,134.6
+ ,102.9
+ ,112.7
+ ,97
+ ,111.4
+ ,131.8
+ ,97.4
+ ,102.9
+ ,112.7
+ ,87.4
+ ,135.9
+ ,111.4
+ ,97.4
+ ,102.9
+ ,96.8
+ ,142.7
+ ,87.4
+ ,111.4
+ ,97.4
+ ,114.1
+ ,141.7
+ ,96.8
+ ,87.4
+ ,111.4
+ ,110.3
+ ,153.4
+ ,114.1
+ ,96.8
+ ,87.4
+ ,103.9
+ ,145
+ ,110.3
+ ,114.1
+ ,96.8
+ ,101.6
+ ,137.7
+ ,103.9
+ ,110.3
+ ,114.1
+ ,94.6
+ ,148.3
+ ,101.6
+ ,103.9
+ ,110.3
+ ,95.9
+ ,152.2
+ ,94.6
+ ,101.6
+ ,103.9
+ ,104.7
+ ,169.4
+ ,95.9
+ ,94.6
+ ,101.6
+ ,102.8
+ ,168.6
+ ,104.7
+ ,95.9
+ ,94.6
+ ,98.1
+ ,161.1
+ ,102.8
+ ,104.7
+ ,95.9
+ ,113.9
+ ,174.1
+ ,98.1
+ ,102.8
+ ,104.7
+ ,80.9
+ ,179
+ ,113.9
+ ,98.1
+ ,102.8
+ ,95.7
+ ,190.6
+ ,80.9
+ ,113.9
+ ,98.1
+ ,113.2
+ ,190
+ ,95.7
+ ,80.9
+ ,113.9
+ ,105.9
+ ,181.6
+ ,113.2
+ ,95.7
+ ,80.9
+ ,108.8
+ ,174.8
+ ,105.9
+ ,113.2
+ ,95.7
+ ,102.3
+ ,180.5
+ ,108.8
+ ,105.9
+ ,113.2
+ ,99
+ ,196.8
+ ,102.3
+ ,108.8
+ ,105.9
+ ,100.7
+ ,193.8
+ ,99
+ ,102.3
+ ,108.8
+ ,115.5
+ ,197
+ ,100.7
+ ,99
+ ,102.3
+ ,100.7
+ ,216.3
+ ,115.5
+ ,100.7
+ ,99
+ ,109.9
+ ,221.4
+ ,100.7
+ ,115.5
+ ,100.7
+ ,114.6
+ ,217.9
+ ,109.9
+ ,100.7
+ ,115.5
+ ,85.4
+ ,229.7
+ ,114.6
+ ,109.9
+ ,100.7
+ ,100.5
+ ,227.4
+ ,85.4
+ ,114.6
+ ,109.9
+ ,114.8
+ ,204.2
+ ,100.5
+ ,85.4
+ ,114.6
+ ,116.5
+ ,196.6
+ ,114.8
+ ,100.5
+ ,85.4
+ ,112.9
+ ,198.8
+ ,116.5
+ ,114.8
+ ,100.5
+ ,102
+ ,207.5
+ ,112.9
+ ,116.5
+ ,114.8
+ ,106
+ ,190.7
+ ,102
+ ,112.9
+ ,116.5
+ ,105.3
+ ,201.6
+ ,106
+ ,102
+ ,112.9
+ ,118.8
+ ,210.5
+ ,105.3
+ ,106
+ ,102
+ ,106.1
+ ,223.5
+ ,118.8
+ ,105.3
+ ,106
+ ,109.3
+ ,223.8
+ ,106.1
+ ,118.8
+ ,105.3
+ ,117.2
+ ,231.2
+ ,109.3
+ ,106.1
+ ,118.8
+ ,92.5
+ ,244
+ ,117.2
+ ,109.3
+ ,106.1
+ ,104.2
+ ,234.7
+ ,92.5
+ ,117.2
+ ,109.3
+ ,112.5
+ ,250.2
+ ,104.2
+ ,92.5
+ ,117.2
+ ,122.4
+ ,265.7
+ ,112.5
+ ,104.2
+ ,92.5
+ ,113.3
+ ,287.6
+ ,122.4
+ ,112.5
+ ,104.2
+ ,100
+ ,283.3
+ ,113.3
+ ,122.4
+ ,112.5
+ ,110.7
+ ,295.4
+ ,100
+ ,113.3
+ ,122.4
+ ,112.8
+ ,312.3
+ ,110.7
+ ,100
+ ,113.3
+ ,109.8
+ ,333.8
+ ,112.8
+ ,110.7
+ ,100
+ ,117.3
+ ,347.7
+ ,109.8
+ ,112.8
+ ,110.7
+ ,109.1
+ ,383.2
+ ,117.3
+ ,109.8
+ ,112.8
+ ,115.9
+ ,407.1
+ ,109.1
+ ,117.3
+ ,109.8
+ ,96
+ ,413.6
+ ,115.9
+ ,109.1
+ ,117.3
+ ,99.8
+ ,362.7
+ ,96
+ ,115.9
+ ,109.1
+ ,116.8
+ ,321.9
+ ,99.8
+ ,96
+ ,115.9
+ ,115.7
+ ,239.4
+ ,116.8
+ ,99.8
+ ,96
+ ,99.4
+ ,191
+ ,115.7
+ ,116.8
+ ,99.8
+ ,94.3
+ ,159.7
+ ,99.4
+ ,115.7
+ ,116.8
+ ,91
+ ,163.4
+ ,94.3
+ ,99.4
+ ,115.7)
+ ,dim=c(5
+ ,58)
+ ,dimnames=list(c('tot.ind.prod.index'
+ ,'prijsindex.grondst.incl.energie'
+ ,'y(t-1)'
+ ,'y(t-2)'
+ ,'y(t-3)')
+ ,1:58))
> y <- array(NA,dim=c(5,58),dimnames=list(c('tot.ind.prod.index','prijsindex.grondst.incl.energie','y(t-1)','y(t-2)','y(t-3)'),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 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
tot.ind.prod.index prijsindex.grondst.incl.energie y(t-1) y(t-2) y(t-3)
1 102.9 127.5 112.7 97.0 95.1
2 97.4 134.6 102.9 112.7 97.0
3 111.4 131.8 97.4 102.9 112.7
4 87.4 135.9 111.4 97.4 102.9
5 96.8 142.7 87.4 111.4 97.4
6 114.1 141.7 96.8 87.4 111.4
7 110.3 153.4 114.1 96.8 87.4
8 103.9 145.0 110.3 114.1 96.8
9 101.6 137.7 103.9 110.3 114.1
10 94.6 148.3 101.6 103.9 110.3
11 95.9 152.2 94.6 101.6 103.9
12 104.7 169.4 95.9 94.6 101.6
13 102.8 168.6 104.7 95.9 94.6
14 98.1 161.1 102.8 104.7 95.9
15 113.9 174.1 98.1 102.8 104.7
16 80.9 179.0 113.9 98.1 102.8
17 95.7 190.6 80.9 113.9 98.1
18 113.2 190.0 95.7 80.9 113.9
19 105.9 181.6 113.2 95.7 80.9
20 108.8 174.8 105.9 113.2 95.7
21 102.3 180.5 108.8 105.9 113.2
22 99.0 196.8 102.3 108.8 105.9
23 100.7 193.8 99.0 102.3 108.8
24 115.5 197.0 100.7 99.0 102.3
25 100.7 216.3 115.5 100.7 99.0
26 109.9 221.4 100.7 115.5 100.7
27 114.6 217.9 109.9 100.7 115.5
28 85.4 229.7 114.6 109.9 100.7
29 100.5 227.4 85.4 114.6 109.9
30 114.8 204.2 100.5 85.4 114.6
31 116.5 196.6 114.8 100.5 85.4
32 112.9 198.8 116.5 114.8 100.5
33 102.0 207.5 112.9 116.5 114.8
34 106.0 190.7 102.0 112.9 116.5
35 105.3 201.6 106.0 102.0 112.9
36 118.8 210.5 105.3 106.0 102.0
37 106.1 223.5 118.8 105.3 106.0
38 109.3 223.8 106.1 118.8 105.3
39 117.2 231.2 109.3 106.1 118.8
40 92.5 244.0 117.2 109.3 106.1
41 104.2 234.7 92.5 117.2 109.3
42 112.5 250.2 104.2 92.5 117.2
43 122.4 265.7 112.5 104.2 92.5
44 113.3 287.6 122.4 112.5 104.2
45 100.0 283.3 113.3 122.4 112.5
46 110.7 295.4 100.0 113.3 122.4
47 112.8 312.3 110.7 100.0 113.3
48 109.8 333.8 112.8 110.7 100.0
49 117.3 347.7 109.8 112.8 110.7
50 109.1 383.2 117.3 109.8 112.8
51 115.9 407.1 109.1 117.3 109.8
52 96.0 413.6 115.9 109.1 117.3
53 99.8 362.7 96.0 115.9 109.1
54 116.8 321.9 99.8 96.0 115.9
55 115.7 239.4 116.8 99.8 96.0
56 99.4 191.0 115.7 116.8 99.8
57 94.3 159.7 99.4 115.7 116.8
58 91.0 163.4 94.3 99.4 115.7
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) prijsindex.grondst.incl.energie
136.36955 0.05308
`y(t-1)` `y(t-2)`
-0.01194 -0.30107
`y(t-3)`
-0.08919
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-24.9089 -4.0726 0.8583 6.5405 13.5234
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 136.36955 27.04674 5.042 5.73e-06 ***
prijsindex.grondst.incl.energie 0.05308 0.01925 2.758 0.00796 **
`y(t-1)` -0.01194 0.14143 -0.084 0.93305
`y(t-2)` -0.30107 0.13435 -2.241 0.02924 *
`y(t-3)` -0.08919 0.14287 -0.624 0.53514
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 8.633 on 53 degrees of freedom
Multiple R-squared: 0.1696, Adjusted R-squared: 0.1069
F-statistic: 2.706 on 4 and 53 DF, p-value: 0.03994
> 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,] 0.8265919 0.3468162 0.1734081
[2,] 0.7095685 0.5808630 0.2904315
[3,] 0.7234941 0.5530117 0.2765059
[4,] 0.6821941 0.6356117 0.3178059
[5,] 0.5673192 0.8653616 0.4326808
[6,] 0.4562084 0.9124168 0.5437916
[7,] 0.3626370 0.7252741 0.6373630
[8,] 0.4020058 0.8040115 0.5979942
[9,] 0.7991737 0.4016526 0.2008263
[10,] 0.7544868 0.4910264 0.2455132
[11,] 0.7032600 0.5934799 0.2967400
[12,] 0.6754124 0.6491753 0.3245876
[13,] 0.7200736 0.5598528 0.2799264
[14,] 0.6531093 0.6937813 0.3468907
[15,] 0.5872973 0.8254055 0.4127027
[16,] 0.5239628 0.9520743 0.4760372
[17,] 0.5424395 0.9151210 0.4575605
[18,] 0.5112167 0.9775666 0.4887833
[19,] 0.4856244 0.9712488 0.5143756
[20,] 0.4770395 0.9540791 0.5229605
[21,] 0.8089951 0.3820098 0.1910049
[22,] 0.7599925 0.4800150 0.2400075
[23,] 0.7011726 0.5976548 0.2988274
[24,] 0.7083909 0.5832181 0.2916091
[25,] 0.7313424 0.5373152 0.2686576
[26,] 0.6606600 0.6786800 0.3393400
[27,] 0.6087645 0.7824711 0.3912355
[28,] 0.5252385 0.9495229 0.4747615
[29,] 0.5757768 0.8484464 0.4242232
[30,] 0.4902510 0.9805020 0.5097490
[31,] 0.4522386 0.9044772 0.5477614
[32,] 0.5905679 0.8188642 0.4094321
[33,] 0.7221570 0.5556859 0.2778430
[34,] 0.6472567 0.7054865 0.3527433
[35,] 0.5657883 0.8684233 0.4342117
[36,] 0.5591099 0.8817803 0.4408901
[37,] 0.4853249 0.9706498 0.5146751
[38,] 0.3887976 0.7775951 0.6112024
[39,] 0.4410137 0.8820274 0.5589863
[40,] 0.3453262 0.6906525 0.6546738
[41,] 0.2522777 0.5045553 0.7477223
[42,] 0.2803584 0.5607168 0.7196416
[43,] 0.1762376 0.3524753 0.8237624
> postscript(file="/var/www/html/rcomp/tmp/1p5cx1258646084.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2eswz1258646084.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3ofm61258646084.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4u7y01258646084.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5ykv61258646084.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 58
Frequency = 1
1 2 3 4 5 6
-1.2072888 -2.3049339 10.2277920 -16.3526385 -3.8756512 7.6125869
7 8 9 10 11 12
4.0875946 4.1349800 2.5449524 -7.3109422 -7.5647751 -1.9749167
13 14 15 16 17 18
-3.9603169 -5.5195171 9.7470879 -24.9089016 -6.7808770 2.4015006
19 20 21 22 23 24
-2.7310095 7.0314793 -0.3735368 -4.3943563 -4.2728032 8.8043850
25 26 27 28 29 30
-6.6259751 6.7340658 8.5938091 -19.7265992 -2.6175250 4.7222391
31 32 33 34 35 36
8.9382906 10.8937864 1.2761537 5.1056281 0.2720370 13.5233815
37 38 39 40 41 42
0.4404257 7.4749032 12.4007102 -13.0537078 1.5089776 2.3939975
43 44 45 46 47 48
12.8898826 6.2878538 -3.1716847 4.8704492 1.3852413 -0.6957385
49 50 51 52 53 54
7.6171112 -3.0937734 4.3300891 -17.6336607 -10.0532642 3.7731292
55 56 57 58
6.6247756 -1.6619976 -4.1100448 -12.6728602
> postscript(file="/var/www/html/rcomp/tmp/6pu201258646084.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 58
Frequency = 1
lag(myerror, k = 1) myerror
0 -1.2072888 NA
1 -2.3049339 -1.2072888
2 10.2277920 -2.3049339
3 -16.3526385 10.2277920
4 -3.8756512 -16.3526385
5 7.6125869 -3.8756512
6 4.0875946 7.6125869
7 4.1349800 4.0875946
8 2.5449524 4.1349800
9 -7.3109422 2.5449524
10 -7.5647751 -7.3109422
11 -1.9749167 -7.5647751
12 -3.9603169 -1.9749167
13 -5.5195171 -3.9603169
14 9.7470879 -5.5195171
15 -24.9089016 9.7470879
16 -6.7808770 -24.9089016
17 2.4015006 -6.7808770
18 -2.7310095 2.4015006
19 7.0314793 -2.7310095
20 -0.3735368 7.0314793
21 -4.3943563 -0.3735368
22 -4.2728032 -4.3943563
23 8.8043850 -4.2728032
24 -6.6259751 8.8043850
25 6.7340658 -6.6259751
26 8.5938091 6.7340658
27 -19.7265992 8.5938091
28 -2.6175250 -19.7265992
29 4.7222391 -2.6175250
30 8.9382906 4.7222391
31 10.8937864 8.9382906
32 1.2761537 10.8937864
33 5.1056281 1.2761537
34 0.2720370 5.1056281
35 13.5233815 0.2720370
36 0.4404257 13.5233815
37 7.4749032 0.4404257
38 12.4007102 7.4749032
39 -13.0537078 12.4007102
40 1.5089776 -13.0537078
41 2.3939975 1.5089776
42 12.8898826 2.3939975
43 6.2878538 12.8898826
44 -3.1716847 6.2878538
45 4.8704492 -3.1716847
46 1.3852413 4.8704492
47 -0.6957385 1.3852413
48 7.6171112 -0.6957385
49 -3.0937734 7.6171112
50 4.3300891 -3.0937734
51 -17.6336607 4.3300891
52 -10.0532642 -17.6336607
53 3.7731292 -10.0532642
54 6.6247756 3.7731292
55 -1.6619976 6.6247756
56 -4.1100448 -1.6619976
57 -12.6728602 -4.1100448
58 NA -12.6728602
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -2.3049339 -1.2072888
[2,] 10.2277920 -2.3049339
[3,] -16.3526385 10.2277920
[4,] -3.8756512 -16.3526385
[5,] 7.6125869 -3.8756512
[6,] 4.0875946 7.6125869
[7,] 4.1349800 4.0875946
[8,] 2.5449524 4.1349800
[9,] -7.3109422 2.5449524
[10,] -7.5647751 -7.3109422
[11,] -1.9749167 -7.5647751
[12,] -3.9603169 -1.9749167
[13,] -5.5195171 -3.9603169
[14,] 9.7470879 -5.5195171
[15,] -24.9089016 9.7470879
[16,] -6.7808770 -24.9089016
[17,] 2.4015006 -6.7808770
[18,] -2.7310095 2.4015006
[19,] 7.0314793 -2.7310095
[20,] -0.3735368 7.0314793
[21,] -4.3943563 -0.3735368
[22,] -4.2728032 -4.3943563
[23,] 8.8043850 -4.2728032
[24,] -6.6259751 8.8043850
[25,] 6.7340658 -6.6259751
[26,] 8.5938091 6.7340658
[27,] -19.7265992 8.5938091
[28,] -2.6175250 -19.7265992
[29,] 4.7222391 -2.6175250
[30,] 8.9382906 4.7222391
[31,] 10.8937864 8.9382906
[32,] 1.2761537 10.8937864
[33,] 5.1056281 1.2761537
[34,] 0.2720370 5.1056281
[35,] 13.5233815 0.2720370
[36,] 0.4404257 13.5233815
[37,] 7.4749032 0.4404257
[38,] 12.4007102 7.4749032
[39,] -13.0537078 12.4007102
[40,] 1.5089776 -13.0537078
[41,] 2.3939975 1.5089776
[42,] 12.8898826 2.3939975
[43,] 6.2878538 12.8898826
[44,] -3.1716847 6.2878538
[45,] 4.8704492 -3.1716847
[46,] 1.3852413 4.8704492
[47,] -0.6957385 1.3852413
[48,] 7.6171112 -0.6957385
[49,] -3.0937734 7.6171112
[50,] 4.3300891 -3.0937734
[51,] -17.6336607 4.3300891
[52,] -10.0532642 -17.6336607
[53,] 3.7731292 -10.0532642
[54,] 6.6247756 3.7731292
[55,] -1.6619976 6.6247756
[56,] -4.1100448 -1.6619976
[57,] -12.6728602 -4.1100448
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -2.3049339 -1.2072888
2 10.2277920 -2.3049339
3 -16.3526385 10.2277920
4 -3.8756512 -16.3526385
5 7.6125869 -3.8756512
6 4.0875946 7.6125869
7 4.1349800 4.0875946
8 2.5449524 4.1349800
9 -7.3109422 2.5449524
10 -7.5647751 -7.3109422
11 -1.9749167 -7.5647751
12 -3.9603169 -1.9749167
13 -5.5195171 -3.9603169
14 9.7470879 -5.5195171
15 -24.9089016 9.7470879
16 -6.7808770 -24.9089016
17 2.4015006 -6.7808770
18 -2.7310095 2.4015006
19 7.0314793 -2.7310095
20 -0.3735368 7.0314793
21 -4.3943563 -0.3735368
22 -4.2728032 -4.3943563
23 8.8043850 -4.2728032
24 -6.6259751 8.8043850
25 6.7340658 -6.6259751
26 8.5938091 6.7340658
27 -19.7265992 8.5938091
28 -2.6175250 -19.7265992
29 4.7222391 -2.6175250
30 8.9382906 4.7222391
31 10.8937864 8.9382906
32 1.2761537 10.8937864
33 5.1056281 1.2761537
34 0.2720370 5.1056281
35 13.5233815 0.2720370
36 0.4404257 13.5233815
37 7.4749032 0.4404257
38 12.4007102 7.4749032
39 -13.0537078 12.4007102
40 1.5089776 -13.0537078
41 2.3939975 1.5089776
42 12.8898826 2.3939975
43 6.2878538 12.8898826
44 -3.1716847 6.2878538
45 4.8704492 -3.1716847
46 1.3852413 4.8704492
47 -0.6957385 1.3852413
48 7.6171112 -0.6957385
49 -3.0937734 7.6171112
50 4.3300891 -3.0937734
51 -17.6336607 4.3300891
52 -10.0532642 -17.6336607
53 3.7731292 -10.0532642
54 6.6247756 3.7731292
55 -1.6619976 6.6247756
56 -4.1100448 -1.6619976
57 -12.6728602 -4.1100448
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/70n9v1258646084.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8aeps1258646084.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9pqx51258646084.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10q1a61258646084.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/11swmr1258646084.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/12komw1258646084.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13ptx61258646084.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/14sgld1258646084.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/15wasw1258646084.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/16nmi21258646084.tab")
+ }
>
> system("convert tmp/1p5cx1258646084.ps tmp/1p5cx1258646084.png")
> system("convert tmp/2eswz1258646084.ps tmp/2eswz1258646084.png")
> system("convert tmp/3ofm61258646084.ps tmp/3ofm61258646084.png")
> system("convert tmp/4u7y01258646084.ps tmp/4u7y01258646084.png")
> system("convert tmp/5ykv61258646084.ps tmp/5ykv61258646084.png")
> system("convert tmp/6pu201258646084.ps tmp/6pu201258646084.png")
> system("convert tmp/70n9v1258646084.ps tmp/70n9v1258646084.png")
> system("convert tmp/8aeps1258646084.ps tmp/8aeps1258646084.png")
> system("convert tmp/9pqx51258646084.ps tmp/9pqx51258646084.png")
> system("convert tmp/10q1a61258646084.ps tmp/10q1a61258646084.png")
>
>
> proc.time()
user system elapsed
2.471 1.570 2.858