R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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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(10540.05
+ ,0
+ ,1
+ ,0
+ ,10601.61
+ ,0
+ ,2
+ ,0
+ ,10323.73
+ ,0
+ ,3
+ ,0
+ ,10418.4
+ ,0
+ ,4
+ ,0
+ ,10092.96
+ ,0
+ ,5
+ ,0
+ ,10364.91
+ ,0
+ ,6
+ ,0
+ ,10152.09
+ ,0
+ ,7
+ ,0
+ ,10032.8
+ ,0
+ ,8
+ ,0
+ ,10204.59
+ ,0
+ ,9
+ ,0
+ ,10001.6
+ ,0
+ ,10
+ ,0
+ ,10411.75
+ ,0
+ ,11
+ ,0
+ ,10673.38
+ ,0
+ ,12
+ ,0
+ ,10539.51
+ ,0
+ ,13
+ ,0
+ ,10723.78
+ ,0
+ ,14
+ ,0
+ ,10682.06
+ ,0
+ ,15
+ ,0
+ ,10283.19
+ ,0
+ ,16
+ ,0
+ ,10377.18
+ ,0
+ ,17
+ ,0
+ ,10486.64
+ ,0
+ ,18
+ ,0
+ ,10545.38
+ ,0
+ ,19
+ ,0
+ ,10554.27
+ ,0
+ ,20
+ ,0
+ ,10532.54
+ ,0
+ ,21
+ ,0
+ ,10324.31
+ ,0
+ ,22
+ ,0
+ ,10695.25
+ ,0
+ ,23
+ ,0
+ ,10827.81
+ ,0
+ ,24
+ ,0
+ ,10872.48
+ ,0
+ ,25
+ ,0
+ ,10971.19
+ ,0
+ ,26
+ ,0
+ ,11145.65
+ ,0
+ ,27
+ ,0
+ ,11234.68
+ ,0
+ ,28
+ ,0
+ ,11333.88
+ ,0
+ ,29
+ ,0
+ ,10997.97
+ ,0
+ ,30
+ ,0
+ ,11036.89
+ ,0
+ ,31
+ ,0
+ ,11257.35
+ ,0
+ ,32
+ ,0
+ ,11533.59
+ ,0
+ ,33
+ ,0
+ ,11963.12
+ ,0
+ ,34
+ ,0
+ ,12185.15
+ ,0
+ ,35
+ ,0
+ ,12377.62
+ ,0
+ ,36
+ ,0
+ ,12512.89
+ ,0
+ ,37
+ ,0
+ ,12631.48
+ ,0
+ ,38
+ ,0
+ ,12268.53
+ ,0
+ ,39
+ ,0
+ ,12754.8
+ ,1
+ ,40
+ ,40
+ ,13407.75
+ ,1
+ ,41
+ ,41
+ ,13480.21
+ ,1
+ ,42
+ ,42
+ ,13673.28
+ ,1
+ ,43
+ ,43
+ ,13239.71
+ ,1
+ ,44
+ ,44
+ ,13557.69
+ ,1
+ ,45
+ ,45
+ ,13901.28
+ ,1
+ ,46
+ ,46
+ ,13200.58
+ ,1
+ ,47
+ ,47
+ ,13406.97
+ ,1
+ ,48
+ ,48
+ ,12538.12
+ ,1
+ ,49
+ ,49
+ ,12419.57
+ ,1
+ ,50
+ ,50
+ ,12193.88
+ ,1
+ ,51
+ ,51
+ ,12656.63
+ ,1
+ ,52
+ ,52
+ ,12812.48
+ ,1
+ ,53
+ ,53
+ ,12056.67
+ ,1
+ ,54
+ ,54
+ ,11322.38
+ ,1
+ ,55
+ ,55
+ ,11530.75
+ ,1
+ ,56
+ ,56
+ ,11114.08
+ ,1
+ ,57
+ ,57
+ ,9181.73
+ ,1
+ ,58
+ ,58
+ ,8614.55
+ ,1
+ ,59
+ ,59)
+ ,dim=c(4
+ ,59)
+ ,dimnames=list(c('DowJones'
+ ,'Dummy'
+ ,'Trend'
+ ,'Dumtrend')
+ ,1:59))
> y <- array(NA,dim=c(4,59),dimnames=list(c('DowJones','Dummy','Trend','Dumtrend'),1:59))
> 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 = 'Include Monthly 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
DowJones Dummy Trend Dumtrend M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 10540.05 0 1 0 1 0 0 0 0 0 0 0 0 0 0
2 10601.61 0 2 0 0 1 0 0 0 0 0 0 0 0 0
3 10323.73 0 3 0 0 0 1 0 0 0 0 0 0 0 0
4 10418.40 0 4 0 0 0 0 1 0 0 0 0 0 0 0
5 10092.96 0 5 0 0 0 0 0 1 0 0 0 0 0 0
6 10364.91 0 6 0 0 0 0 0 0 1 0 0 0 0 0
7 10152.09 0 7 0 0 0 0 0 0 0 1 0 0 0 0
8 10032.80 0 8 0 0 0 0 0 0 0 0 1 0 0 0
9 10204.59 0 9 0 0 0 0 0 0 0 0 0 1 0 0
10 10001.60 0 10 0 0 0 0 0 0 0 0 0 0 1 0
11 10411.75 0 11 0 0 0 0 0 0 0 0 0 0 0 1
12 10673.38 0 12 0 0 0 0 0 0 0 0 0 0 0 0
13 10539.51 0 13 0 1 0 0 0 0 0 0 0 0 0 0
14 10723.78 0 14 0 0 1 0 0 0 0 0 0 0 0 0
15 10682.06 0 15 0 0 0 1 0 0 0 0 0 0 0 0
16 10283.19 0 16 0 0 0 0 1 0 0 0 0 0 0 0
17 10377.18 0 17 0 0 0 0 0 1 0 0 0 0 0 0
18 10486.64 0 18 0 0 0 0 0 0 1 0 0 0 0 0
19 10545.38 0 19 0 0 0 0 0 0 0 1 0 0 0 0
20 10554.27 0 20 0 0 0 0 0 0 0 0 1 0 0 0
21 10532.54 0 21 0 0 0 0 0 0 0 0 0 1 0 0
22 10324.31 0 22 0 0 0 0 0 0 0 0 0 0 1 0
23 10695.25 0 23 0 0 0 0 0 0 0 0 0 0 0 1
24 10827.81 0 24 0 0 0 0 0 0 0 0 0 0 0 0
25 10872.48 0 25 0 1 0 0 0 0 0 0 0 0 0 0
26 10971.19 0 26 0 0 1 0 0 0 0 0 0 0 0 0
27 11145.65 0 27 0 0 0 1 0 0 0 0 0 0 0 0
28 11234.68 0 28 0 0 0 0 1 0 0 0 0 0 0 0
29 11333.88 0 29 0 0 0 0 0 1 0 0 0 0 0 0
30 10997.97 0 30 0 0 0 0 0 0 1 0 0 0 0 0
31 11036.89 0 31 0 0 0 0 0 0 0 1 0 0 0 0
32 11257.35 0 32 0 0 0 0 0 0 0 0 1 0 0 0
33 11533.59 0 33 0 0 0 0 0 0 0 0 0 1 0 0
34 11963.12 0 34 0 0 0 0 0 0 0 0 0 0 1 0
35 12185.15 0 35 0 0 0 0 0 0 0 0 0 0 0 1
36 12377.62 0 36 0 0 0 0 0 0 0 0 0 0 0 0
37 12512.89 0 37 0 1 0 0 0 0 0 0 0 0 0 0
38 12631.48 0 38 0 0 1 0 0 0 0 0 0 0 0 0
39 12268.53 0 39 0 0 0 1 0 0 0 0 0 0 0 0
40 12754.80 1 40 40 0 0 0 1 0 0 0 0 0 0 0
41 13407.75 1 41 41 0 0 0 0 1 0 0 0 0 0 0
42 13480.21 1 42 42 0 0 0 0 0 1 0 0 0 0 0
43 13673.28 1 43 43 0 0 0 0 0 0 1 0 0 0 0
44 13239.71 1 44 44 0 0 0 0 0 0 0 1 0 0 0
45 13557.69 1 45 45 0 0 0 0 0 0 0 0 1 0 0
46 13901.28 1 46 46 0 0 0 0 0 0 0 0 0 1 0
47 13200.58 1 47 47 0 0 0 0 0 0 0 0 0 0 1
48 13406.97 1 48 48 0 0 0 0 0 0 0 0 0 0 0
49 12538.12 1 49 49 1 0 0 0 0 0 0 0 0 0 0
50 12419.57 1 50 50 0 1 0 0 0 0 0 0 0 0 0
51 12193.88 1 51 51 0 0 1 0 0 0 0 0 0 0 0
52 12656.63 1 52 52 0 0 0 1 0 0 0 0 0 0 0
53 12812.48 1 53 53 0 0 0 0 1 0 0 0 0 0 0
54 12056.67 1 54 54 0 0 0 0 0 1 0 0 0 0 0
55 11322.38 1 55 55 0 0 0 0 0 0 1 0 0 0 0
56 11530.75 1 56 56 0 0 0 0 0 0 0 1 0 0 0
57 11114.08 1 57 57 0 0 0 0 0 0 0 0 1 0 0
58 9181.73 1 58 58 0 0 0 0 0 0 0 0 0 1 0
59 8614.55 1 59 59 0 0 0 0 0 0 0 0 0 0 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummy Trend Dumtrend M1 M2
10136.66 12188.47 53.42 -247.08 -87.88 -22.97
M3 M4 M5 M6 M7 M8
-173.73 -492.01 -311.29 -393.45 -479.32 -456.93
M9 M10 M11
-346.00 -614.68 -622.22
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1662.44 -217.17 -54.59 313.73 1099.18
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 10136.655 359.960 28.160 < 2e-16 ***
Dummy 12188.472 1195.721 10.193 3.69e-13 ***
Trend 53.422 8.594 6.216 1.62e-07 ***
Dumtrend -247.081 25.046 -9.865 1.01e-12 ***
M1 -87.882 401.465 -0.219 0.828
M2 -22.972 401.066 -0.057 0.955
M3 -173.733 400.845 -0.433 0.667
M4 -492.014 404.308 -1.217 0.230
M5 -311.293 403.249 -0.772 0.444
M6 -393.452 402.485 -0.978 0.334
M7 -479.317 402.016 -1.192 0.240
M8 -456.934 401.845 -1.137 0.262
M9 -346.001 401.971 -0.861 0.394
M10 -614.680 402.395 -1.528 0.134
M11 -622.221 403.115 -1.544 0.130
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 596.3 on 44 degrees of freedom
Multiple R-squared: 0.8193, Adjusted R-squared: 0.7618
F-statistic: 14.25 on 14 and 44 DF, p-value: 5.445e-12
> 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,] 1.829297e-02 3.658594e-02 0.9817070
[2,] 6.523382e-03 1.304676e-02 0.9934766
[3,] 3.423702e-03 6.847405e-03 0.9965763
[4,] 8.283227e-04 1.656645e-03 0.9991717
[5,] 1.826716e-04 3.653431e-04 0.9998173
[6,] 3.951468e-05 7.902935e-05 0.9999605
[7,] 7.595167e-06 1.519033e-05 0.9999924
[8,] 1.258798e-06 2.517596e-06 0.9999987
[9,] 1.974065e-07 3.948129e-07 0.9999998
[10,] 1.279624e-07 2.559249e-07 0.9999999
[11,] 4.631017e-07 9.262034e-07 0.9999995
[12,] 2.291361e-06 4.582723e-06 0.9999977
[13,] 5.201596e-07 1.040319e-06 0.9999995
[14,] 1.347887e-07 2.695774e-07 0.9999999
[15,] 9.975042e-08 1.995008e-07 0.9999999
[16,] 2.142938e-07 4.285877e-07 0.9999998
[17,] 7.179944e-06 1.435989e-05 0.9999928
[18,] 1.793166e-05 3.586333e-05 0.9999821
[19,] 2.284494e-05 4.568988e-05 0.9999772
[20,] 1.826741e-05 3.653481e-05 0.9999817
[21,] 1.067392e-05 2.134783e-05 0.9999893
[22,] 3.137692e-06 6.275385e-06 0.9999969
[23,] 9.304526e-06 1.860905e-05 0.9999907
[24,] 3.536784e-05 7.073568e-05 0.9999646
> postscript(file="/var/www/html/rcomp/tmp/1q1c51229329558.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/294ve1229329558.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ph151229329558.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4y1yw1229329558.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5e70s1229329558.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 = 59
Frequency = 1
1 2 3 4 5
437.8553722 381.0831441 200.5429159 560.0720380 0.4895817
6 7 8 9 10
301.1771253 120.8006690 -74.2937873 -66.8582436 -54.5906999
11 12 13 14 15
309.6788437 -104.3335372 -203.7426655 -137.8048937 -82.1851218
16 17 18 19 20
-216.1959997 -356.3484561 -218.1509124 -126.9673687 -193.8818250
21 22 23 24 25
-379.9662814 -372.9387377 -47.8791940 -590.9615750 -511.8307032
26 27 28 29 30
-531.4529314 -259.6531595 94.2359625 -40.7064938 -347.8789501
31 32 33 34 35
-276.5154064 -131.8598628 -19.9743191 624.8132246 800.9627683
36 37 38 39 40
317.7903873 487.5212590 487.7790309 222.1688027 -1331.9288263
41 42 43 44 45
-666.0401418 -317.7614574 154.8332271 -107.4600884 293.2465961
46 47 48 49 50
1099.1752806 599.6759650 377.5047249 -209.8032626 -199.6043499
51 52 53 54 55
-80.8734373 893.8168256 1062.6055100 582.6141945 127.8488790
56 57 58 59
507.4955635 173.5522480 -1296.4590675 -1662.4383831
> postscript(file="/var/www/html/rcomp/tmp/6n7261229329558.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 = 59
Frequency = 1
lag(myerror, k = 1) myerror
0 437.8553722 NA
1 381.0831441 437.8553722
2 200.5429159 381.0831441
3 560.0720380 200.5429159
4 0.4895817 560.0720380
5 301.1771253 0.4895817
6 120.8006690 301.1771253
7 -74.2937873 120.8006690
8 -66.8582436 -74.2937873
9 -54.5906999 -66.8582436
10 309.6788437 -54.5906999
11 -104.3335372 309.6788437
12 -203.7426655 -104.3335372
13 -137.8048937 -203.7426655
14 -82.1851218 -137.8048937
15 -216.1959997 -82.1851218
16 -356.3484561 -216.1959997
17 -218.1509124 -356.3484561
18 -126.9673687 -218.1509124
19 -193.8818250 -126.9673687
20 -379.9662814 -193.8818250
21 -372.9387377 -379.9662814
22 -47.8791940 -372.9387377
23 -590.9615750 -47.8791940
24 -511.8307032 -590.9615750
25 -531.4529314 -511.8307032
26 -259.6531595 -531.4529314
27 94.2359625 -259.6531595
28 -40.7064938 94.2359625
29 -347.8789501 -40.7064938
30 -276.5154064 -347.8789501
31 -131.8598628 -276.5154064
32 -19.9743191 -131.8598628
33 624.8132246 -19.9743191
34 800.9627683 624.8132246
35 317.7903873 800.9627683
36 487.5212590 317.7903873
37 487.7790309 487.5212590
38 222.1688027 487.7790309
39 -1331.9288263 222.1688027
40 -666.0401418 -1331.9288263
41 -317.7614574 -666.0401418
42 154.8332271 -317.7614574
43 -107.4600884 154.8332271
44 293.2465961 -107.4600884
45 1099.1752806 293.2465961
46 599.6759650 1099.1752806
47 377.5047249 599.6759650
48 -209.8032626 377.5047249
49 -199.6043499 -209.8032626
50 -80.8734373 -199.6043499
51 893.8168256 -80.8734373
52 1062.6055100 893.8168256
53 582.6141945 1062.6055100
54 127.8488790 582.6141945
55 507.4955635 127.8488790
56 173.5522480 507.4955635
57 -1296.4590675 173.5522480
58 -1662.4383831 -1296.4590675
59 NA -1662.4383831
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 381.0831441 437.8553722
[2,] 200.5429159 381.0831441
[3,] 560.0720380 200.5429159
[4,] 0.4895817 560.0720380
[5,] 301.1771253 0.4895817
[6,] 120.8006690 301.1771253
[7,] -74.2937873 120.8006690
[8,] -66.8582436 -74.2937873
[9,] -54.5906999 -66.8582436
[10,] 309.6788437 -54.5906999
[11,] -104.3335372 309.6788437
[12,] -203.7426655 -104.3335372
[13,] -137.8048937 -203.7426655
[14,] -82.1851218 -137.8048937
[15,] -216.1959997 -82.1851218
[16,] -356.3484561 -216.1959997
[17,] -218.1509124 -356.3484561
[18,] -126.9673687 -218.1509124
[19,] -193.8818250 -126.9673687
[20,] -379.9662814 -193.8818250
[21,] -372.9387377 -379.9662814
[22,] -47.8791940 -372.9387377
[23,] -590.9615750 -47.8791940
[24,] -511.8307032 -590.9615750
[25,] -531.4529314 -511.8307032
[26,] -259.6531595 -531.4529314
[27,] 94.2359625 -259.6531595
[28,] -40.7064938 94.2359625
[29,] -347.8789501 -40.7064938
[30,] -276.5154064 -347.8789501
[31,] -131.8598628 -276.5154064
[32,] -19.9743191 -131.8598628
[33,] 624.8132246 -19.9743191
[34,] 800.9627683 624.8132246
[35,] 317.7903873 800.9627683
[36,] 487.5212590 317.7903873
[37,] 487.7790309 487.5212590
[38,] 222.1688027 487.7790309
[39,] -1331.9288263 222.1688027
[40,] -666.0401418 -1331.9288263
[41,] -317.7614574 -666.0401418
[42,] 154.8332271 -317.7614574
[43,] -107.4600884 154.8332271
[44,] 293.2465961 -107.4600884
[45,] 1099.1752806 293.2465961
[46,] 599.6759650 1099.1752806
[47,] 377.5047249 599.6759650
[48,] -209.8032626 377.5047249
[49,] -199.6043499 -209.8032626
[50,] -80.8734373 -199.6043499
[51,] 893.8168256 -80.8734373
[52,] 1062.6055100 893.8168256
[53,] 582.6141945 1062.6055100
[54,] 127.8488790 582.6141945
[55,] 507.4955635 127.8488790
[56,] 173.5522480 507.4955635
[57,] -1296.4590675 173.5522480
[58,] -1662.4383831 -1296.4590675
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 381.0831441 437.8553722
2 200.5429159 381.0831441
3 560.0720380 200.5429159
4 0.4895817 560.0720380
5 301.1771253 0.4895817
6 120.8006690 301.1771253
7 -74.2937873 120.8006690
8 -66.8582436 -74.2937873
9 -54.5906999 -66.8582436
10 309.6788437 -54.5906999
11 -104.3335372 309.6788437
12 -203.7426655 -104.3335372
13 -137.8048937 -203.7426655
14 -82.1851218 -137.8048937
15 -216.1959997 -82.1851218
16 -356.3484561 -216.1959997
17 -218.1509124 -356.3484561
18 -126.9673687 -218.1509124
19 -193.8818250 -126.9673687
20 -379.9662814 -193.8818250
21 -372.9387377 -379.9662814
22 -47.8791940 -372.9387377
23 -590.9615750 -47.8791940
24 -511.8307032 -590.9615750
25 -531.4529314 -511.8307032
26 -259.6531595 -531.4529314
27 94.2359625 -259.6531595
28 -40.7064938 94.2359625
29 -347.8789501 -40.7064938
30 -276.5154064 -347.8789501
31 -131.8598628 -276.5154064
32 -19.9743191 -131.8598628
33 624.8132246 -19.9743191
34 800.9627683 624.8132246
35 317.7903873 800.9627683
36 487.5212590 317.7903873
37 487.7790309 487.5212590
38 222.1688027 487.7790309
39 -1331.9288263 222.1688027
40 -666.0401418 -1331.9288263
41 -317.7614574 -666.0401418
42 154.8332271 -317.7614574
43 -107.4600884 154.8332271
44 293.2465961 -107.4600884
45 1099.1752806 293.2465961
46 599.6759650 1099.1752806
47 377.5047249 599.6759650
48 -209.8032626 377.5047249
49 -199.6043499 -209.8032626
50 -80.8734373 -199.6043499
51 893.8168256 -80.8734373
52 1062.6055100 893.8168256
53 582.6141945 1062.6055100
54 127.8488790 582.6141945
55 507.4955635 127.8488790
56 173.5522480 507.4955635
57 -1296.4590675 173.5522480
58 -1662.4383831 -1296.4590675
> 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/70q6s1229329558.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8sd7k1229329558.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9figx1229329558.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10gi841229329558.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/110eht1229329558.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/12gnn51229329558.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/133u3m1229329559.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/14my071229329559.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/1515e71229329559.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/16v1vn1229329559.tab")
+ }
> system("convert tmp/1q1c51229329558.ps tmp/1q1c51229329558.png")
> system("convert tmp/294ve1229329558.ps tmp/294ve1229329558.png")
> system("convert tmp/3ph151229329558.ps tmp/3ph151229329558.png")
> system("convert tmp/4y1yw1229329558.ps tmp/4y1yw1229329558.png")
> system("convert tmp/5e70s1229329558.ps tmp/5e70s1229329558.png")
> system("convert tmp/6n7261229329558.ps tmp/6n7261229329558.png")
> system("convert tmp/70q6s1229329558.ps tmp/70q6s1229329558.png")
> system("convert tmp/8sd7k1229329558.ps tmp/8sd7k1229329558.png")
> system("convert tmp/9figx1229329558.ps tmp/9figx1229329558.png")
> system("convert tmp/10gi841229329558.ps tmp/10gi841229329558.png")
>
>
> proc.time()
user system elapsed
2.420 1.579 3.028