R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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.
Natural language support but running in an English locale
R is a collaborative project with many contributors.
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(104.17
+ ,89.00
+ ,103.88
+ ,103.77
+ ,104.18
+ ,86.40
+ ,103.91
+ ,103.88
+ ,104.2
+ ,84.50
+ ,103.91
+ ,103.91
+ ,104.5
+ ,82.70
+ ,103.92
+ ,103.91
+ ,104.78
+ ,80.80
+ ,104.05
+ ,103.92
+ ,104.88
+ ,81.80
+ ,104.23
+ ,104.05
+ ,104.89
+ ,81.80
+ ,104.30
+ ,104.23
+ ,104.9
+ ,82.90
+ ,104.31
+ ,104.30
+ ,104.95
+ ,83.80
+ ,104.31
+ ,104.31
+ ,105.24
+ ,86.20
+ ,104.34
+ ,104.31
+ ,105.35
+ ,86.10
+ ,104.55
+ ,104.34
+ ,105.44
+ ,86.20
+ ,104.65
+ ,104.55
+ ,105.46
+ ,88.80
+ ,104.73
+ ,104.65
+ ,105.47
+ ,89.60
+ ,104.75
+ ,104.73
+ ,105.48
+ ,87.80
+ ,104.75
+ ,104.75
+ ,105.75
+ ,88.30
+ ,104.76
+ ,104.75
+ ,106.1
+ ,88.60
+ ,104.94
+ ,104.76
+ ,106.19
+ ,91.00
+ ,105.29
+ ,104.94
+ ,106.23
+ ,91.50
+ ,105.38
+ ,105.29
+ ,106.24
+ ,95.40
+ ,105.43
+ ,105.38
+ ,106.25
+ ,98.70
+ ,105.43
+ ,105.43
+ ,106.35
+ ,99.90
+ ,105.42
+ ,105.43
+ ,106.48
+ ,98.60
+ ,105.52
+ ,105.42
+ ,106.52
+ ,100.30
+ ,105.69
+ ,105.52
+ ,106.55
+ ,100.20
+ ,105.72
+ ,105.69
+ ,106.55
+ ,100.40
+ ,105.74
+ ,105.72
+ ,106.56
+ ,101.40
+ ,105.74
+ ,105.74
+ ,106.89
+ ,103.00
+ ,105.74
+ ,105.74
+ ,107.09
+ ,109.10
+ ,105.95
+ ,105.74
+ ,107.24
+ ,111.40
+ ,106.17
+ ,105.95
+ ,107.28
+ ,114.10
+ ,106.34
+ ,106.17
+ ,107.3
+ ,121.80
+ ,106.37
+ ,106.34
+ ,107.31
+ ,127.60
+ ,106.37
+ ,106.37
+ ,107.47
+ ,129.90
+ ,106.36
+ ,106.37
+ ,107.35
+ ,128.00
+ ,106.44
+ ,106.36
+ ,107.31
+ ,123.50
+ ,106.29
+ ,106.44
+ ,107.32
+ ,124.00
+ ,106.23
+ ,106.29
+ ,107.32
+ ,127.40
+ ,106.23
+ ,106.23
+ ,107.34
+ ,127.60
+ ,106.23
+ ,106.23
+ ,107.53
+ ,128.40
+ ,106.23
+ ,106.23
+ ,107.72
+ ,131.40
+ ,106.34
+ ,106.23
+ ,107.75
+ ,135.10
+ ,106.44
+ ,106.34
+ ,107.79
+ ,134.00
+ ,106.44
+ ,106.44
+ ,107.81
+ ,144.50
+ ,106.48
+ ,106.44
+ ,107.9
+ ,147.30
+ ,106.50
+ ,106.48
+ ,107.8
+ ,150.90
+ ,106.57
+ ,106.50
+ ,107.86
+ ,148.70
+ ,106.40
+ ,106.57
+ ,107.8
+ ,141.40
+ ,106.37
+ ,106.40
+ ,107.74
+ ,138.90
+ ,106.25
+ ,106.37
+ ,107.75
+ ,139.80
+ ,106.21
+ ,106.25
+ ,107.83
+ ,145.60
+ ,106.21
+ ,106.21
+ ,107.8
+ ,147.90
+ ,106.24
+ ,106.21
+ ,107.81
+ ,148.50
+ ,106.19
+ ,106.24
+ ,107.86
+ ,151.10
+ ,106.08
+ ,106.19
+ ,107.83
+ ,157.50
+ ,106.13
+ ,106.08)
+ ,dim=c(4
+ ,55)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2')
+ ,1:55))
> y <- array(NA,dim=c(4,55),dimnames=list(c('Y','X','Y1','Y2'),1:55))
> 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 = '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
Y X Y1 Y2 t
1 104.17 89.0 103.88 103.77 1
2 104.18 86.4 103.91 103.88 2
3 104.20 84.5 103.91 103.91 3
4 104.50 82.7 103.92 103.91 4
5 104.78 80.8 104.05 103.92 5
6 104.88 81.8 104.23 104.05 6
7 104.89 81.8 104.30 104.23 7
8 104.90 82.9 104.31 104.30 8
9 104.95 83.8 104.31 104.31 9
10 105.24 86.2 104.34 104.31 10
11 105.35 86.1 104.55 104.34 11
12 105.44 86.2 104.65 104.55 12
13 105.46 88.8 104.73 104.65 13
14 105.47 89.6 104.75 104.73 14
15 105.48 87.8 104.75 104.75 15
16 105.75 88.3 104.76 104.75 16
17 106.10 88.6 104.94 104.76 17
18 106.19 91.0 105.29 104.94 18
19 106.23 91.5 105.38 105.29 19
20 106.24 95.4 105.43 105.38 20
21 106.25 98.7 105.43 105.43 21
22 106.35 99.9 105.42 105.43 22
23 106.48 98.6 105.52 105.42 23
24 106.52 100.3 105.69 105.52 24
25 106.55 100.2 105.72 105.69 25
26 106.55 100.4 105.74 105.72 26
27 106.56 101.4 105.74 105.74 27
28 106.89 103.0 105.74 105.74 28
29 107.09 109.1 105.95 105.74 29
30 107.24 111.4 106.17 105.95 30
31 107.28 114.1 106.34 106.17 31
32 107.30 121.8 106.37 106.34 32
33 107.31 127.6 106.37 106.37 33
34 107.47 129.9 106.36 106.37 34
35 107.35 128.0 106.44 106.36 35
36 107.31 123.5 106.29 106.44 36
37 107.32 124.0 106.23 106.29 37
38 107.32 127.4 106.23 106.23 38
39 107.34 127.6 106.23 106.23 39
40 107.53 128.4 106.23 106.23 40
41 107.72 131.4 106.34 106.23 41
42 107.75 135.1 106.44 106.34 42
43 107.79 134.0 106.44 106.44 43
44 107.81 144.5 106.48 106.44 44
45 107.90 147.3 106.50 106.48 45
46 107.80 150.9 106.57 106.50 46
47 107.86 148.7 106.40 106.57 47
48 107.80 141.4 106.37 106.40 48
49 107.74 138.9 106.25 106.37 49
50 107.75 139.8 106.21 106.25 50
51 107.83 145.6 106.21 106.21 51
52 107.80 147.9 106.24 106.21 52
53 107.81 148.5 106.19 106.24 53
54 107.86 151.1 106.08 106.19 54
55 107.83 157.5 106.13 106.08 55
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 t
25.72679 -0.00824 1.23003 -0.46776 0.04604
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.176947 -0.065466 -0.006052 0.051970 0.243634
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 25.726792 4.255304 6.046 1.86e-07 ***
X -0.008239 0.002317 -3.557 0.000832 ***
Y1 1.230030 0.157414 7.814 3.23e-10 ***
Y2 -0.467759 0.163279 -2.865 0.006087 **
t 0.046043 0.004376 10.521 2.83e-14 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.09928 on 50 degrees of freedom
Multiple R-squared: 0.9934, Adjusted R-squared: 0.9929
F-statistic: 1893 on 4 and 50 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.2984299 0.5968597166 0.7015701417
[2,] 0.2199854 0.4399708556 0.7800145722
[3,] 0.1991853 0.3983705803 0.8008147098
[4,] 0.3966517 0.7933034294 0.6033482853
[5,] 0.3026606 0.6053211195 0.6973394402
[6,] 0.2142646 0.4285292462 0.7857353769
[7,] 0.1657172 0.3314344329 0.8342827836
[8,] 0.3105588 0.6211176004 0.6894411998
[9,] 0.2348879 0.4697758783 0.7651120608
[10,] 0.2997816 0.5995632253 0.7002183873
[11,] 0.2597343 0.5194686007 0.7402656997
[12,] 0.4651470 0.9302940595 0.5348529703
[13,] 0.4268900 0.8537799307 0.5731100346
[14,] 0.3563781 0.7127561340 0.6436219330
[15,] 0.3053059 0.6106118973 0.6946940513
[16,] 0.2752778 0.5505556466 0.7247221767
[17,] 0.3741362 0.7482724958 0.6258637521
[18,] 0.3690495 0.7380989192 0.6309505404
[19,] 0.5353384 0.9293231482 0.4646615741
[20,] 0.8240450 0.3519099944 0.1759549972
[21,] 0.8156848 0.3686304332 0.1843152166
[22,] 0.8099918 0.3800164803 0.1900082402
[23,] 0.8295663 0.3408673064 0.1704336532
[24,] 0.7777204 0.4445592727 0.2222796363
[25,] 0.7786760 0.4426480767 0.2213240384
[26,] 0.7348458 0.5303084553 0.2651542276
[27,] 0.8205497 0.3589006436 0.1794503218
[28,] 0.8819558 0.2360883568 0.1180441784
[29,] 0.8560906 0.2878187789 0.1439093894
[30,] 0.8527491 0.2945017129 0.1472508565
[31,] 0.8976461 0.2047078457 0.1023539229
[32,] 0.9925876 0.0148247303 0.0074123652
[33,] 0.9996514 0.0006971328 0.0003485664
[34,] 0.9991991 0.0016017088 0.0008008544
[35,] 0.9983516 0.0032967598 0.0016483799
[36,] 0.9951249 0.0097502259 0.0048751129
[37,] 0.9925743 0.0148513013 0.0074256506
[38,] 0.9926239 0.0147522293 0.0073761147
[39,] 0.9821128 0.0357743033 0.0178871517
[40,] 0.9450219 0.1099561698 0.0549780849
> postscript(file="/var/www/html/freestat/rcomp/tmp/13hjc1292763245.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2vq1x1292763245.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/3vq1x1292763245.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4vq1x1292763245.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/56iii1292763245.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 = 55
Frequency = 1
1 2 3 4 5 6
-0.105639260 -0.148551832 -0.176216629 0.050609442 0.113685575 0.015285784
7 8 9 10 11 12
-0.022662221 -0.029198548 -0.013148030 0.213683197 0.032543166 0.052550991
13 14 15 16 17 18
-0.003695450 -0.020326322 -0.061844766 0.153932075 0.243633539 -0.038948113
19 20 21 22 23 24
0.012142103 -0.011169730 0.003365878 0.079510942 0.025076464 -0.129288183
25 26 27 28 29 30
-0.103536533 -0.158499051 -0.176946993 0.120193558 0.066105430 0.016636495
31 32 33 34 35 36
-0.073357568 0.006661910 0.032440994 0.177649469 -0.107128090 -0.008323050
37 38 39 40 41 42
-0.036608018 -0.082701990 -0.107096690 0.043452289 0.076824806 0.019718773
43 44 45 46 47 48
0.051388701 0.062659296 0.123796981 -0.069330442 0.168348372 -0.040460506
49 50 51 52 53 54
-0.033530958 -0.069087958 -0.006052026 -0.100044746 -0.055609387 0.081685948
55
-0.054579088
> postscript(file="/var/www/html/freestat/rcomp/tmp/66iii1292763245.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 = 55
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.105639260 NA
1 -0.148551832 -0.105639260
2 -0.176216629 -0.148551832
3 0.050609442 -0.176216629
4 0.113685575 0.050609442
5 0.015285784 0.113685575
6 -0.022662221 0.015285784
7 -0.029198548 -0.022662221
8 -0.013148030 -0.029198548
9 0.213683197 -0.013148030
10 0.032543166 0.213683197
11 0.052550991 0.032543166
12 -0.003695450 0.052550991
13 -0.020326322 -0.003695450
14 -0.061844766 -0.020326322
15 0.153932075 -0.061844766
16 0.243633539 0.153932075
17 -0.038948113 0.243633539
18 0.012142103 -0.038948113
19 -0.011169730 0.012142103
20 0.003365878 -0.011169730
21 0.079510942 0.003365878
22 0.025076464 0.079510942
23 -0.129288183 0.025076464
24 -0.103536533 -0.129288183
25 -0.158499051 -0.103536533
26 -0.176946993 -0.158499051
27 0.120193558 -0.176946993
28 0.066105430 0.120193558
29 0.016636495 0.066105430
30 -0.073357568 0.016636495
31 0.006661910 -0.073357568
32 0.032440994 0.006661910
33 0.177649469 0.032440994
34 -0.107128090 0.177649469
35 -0.008323050 -0.107128090
36 -0.036608018 -0.008323050
37 -0.082701990 -0.036608018
38 -0.107096690 -0.082701990
39 0.043452289 -0.107096690
40 0.076824806 0.043452289
41 0.019718773 0.076824806
42 0.051388701 0.019718773
43 0.062659296 0.051388701
44 0.123796981 0.062659296
45 -0.069330442 0.123796981
46 0.168348372 -0.069330442
47 -0.040460506 0.168348372
48 -0.033530958 -0.040460506
49 -0.069087958 -0.033530958
50 -0.006052026 -0.069087958
51 -0.100044746 -0.006052026
52 -0.055609387 -0.100044746
53 0.081685948 -0.055609387
54 -0.054579088 0.081685948
55 NA -0.054579088
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.148551832 -0.105639260
[2,] -0.176216629 -0.148551832
[3,] 0.050609442 -0.176216629
[4,] 0.113685575 0.050609442
[5,] 0.015285784 0.113685575
[6,] -0.022662221 0.015285784
[7,] -0.029198548 -0.022662221
[8,] -0.013148030 -0.029198548
[9,] 0.213683197 -0.013148030
[10,] 0.032543166 0.213683197
[11,] 0.052550991 0.032543166
[12,] -0.003695450 0.052550991
[13,] -0.020326322 -0.003695450
[14,] -0.061844766 -0.020326322
[15,] 0.153932075 -0.061844766
[16,] 0.243633539 0.153932075
[17,] -0.038948113 0.243633539
[18,] 0.012142103 -0.038948113
[19,] -0.011169730 0.012142103
[20,] 0.003365878 -0.011169730
[21,] 0.079510942 0.003365878
[22,] 0.025076464 0.079510942
[23,] -0.129288183 0.025076464
[24,] -0.103536533 -0.129288183
[25,] -0.158499051 -0.103536533
[26,] -0.176946993 -0.158499051
[27,] 0.120193558 -0.176946993
[28,] 0.066105430 0.120193558
[29,] 0.016636495 0.066105430
[30,] -0.073357568 0.016636495
[31,] 0.006661910 -0.073357568
[32,] 0.032440994 0.006661910
[33,] 0.177649469 0.032440994
[34,] -0.107128090 0.177649469
[35,] -0.008323050 -0.107128090
[36,] -0.036608018 -0.008323050
[37,] -0.082701990 -0.036608018
[38,] -0.107096690 -0.082701990
[39,] 0.043452289 -0.107096690
[40,] 0.076824806 0.043452289
[41,] 0.019718773 0.076824806
[42,] 0.051388701 0.019718773
[43,] 0.062659296 0.051388701
[44,] 0.123796981 0.062659296
[45,] -0.069330442 0.123796981
[46,] 0.168348372 -0.069330442
[47,] -0.040460506 0.168348372
[48,] -0.033530958 -0.040460506
[49,] -0.069087958 -0.033530958
[50,] -0.006052026 -0.069087958
[51,] -0.100044746 -0.006052026
[52,] -0.055609387 -0.100044746
[53,] 0.081685948 -0.055609387
[54,] -0.054579088 0.081685948
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.148551832 -0.105639260
2 -0.176216629 -0.148551832
3 0.050609442 -0.176216629
4 0.113685575 0.050609442
5 0.015285784 0.113685575
6 -0.022662221 0.015285784
7 -0.029198548 -0.022662221
8 -0.013148030 -0.029198548
9 0.213683197 -0.013148030
10 0.032543166 0.213683197
11 0.052550991 0.032543166
12 -0.003695450 0.052550991
13 -0.020326322 -0.003695450
14 -0.061844766 -0.020326322
15 0.153932075 -0.061844766
16 0.243633539 0.153932075
17 -0.038948113 0.243633539
18 0.012142103 -0.038948113
19 -0.011169730 0.012142103
20 0.003365878 -0.011169730
21 0.079510942 0.003365878
22 0.025076464 0.079510942
23 -0.129288183 0.025076464
24 -0.103536533 -0.129288183
25 -0.158499051 -0.103536533
26 -0.176946993 -0.158499051
27 0.120193558 -0.176946993
28 0.066105430 0.120193558
29 0.016636495 0.066105430
30 -0.073357568 0.016636495
31 0.006661910 -0.073357568
32 0.032440994 0.006661910
33 0.177649469 0.032440994
34 -0.107128090 0.177649469
35 -0.008323050 -0.107128090
36 -0.036608018 -0.008323050
37 -0.082701990 -0.036608018
38 -0.107096690 -0.082701990
39 0.043452289 -0.107096690
40 0.076824806 0.043452289
41 0.019718773 0.076824806
42 0.051388701 0.019718773
43 0.062659296 0.051388701
44 0.123796981 0.062659296
45 -0.069330442 0.123796981
46 0.168348372 -0.069330442
47 -0.040460506 0.168348372
48 -0.033530958 -0.040460506
49 -0.069087958 -0.033530958
50 -0.006052026 -0.069087958
51 -0.100044746 -0.006052026
52 -0.055609387 -0.100044746
53 0.081685948 -0.055609387
54 -0.054579088 0.081685948
> 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/freestat/rcomp/tmp/7hrzl1292763245.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8hrzl1292763245.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/990g51292763245.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/1090g51292763245.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/11d1fb1292763245.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/freestat/rcomp/tmp/12yjdz1292763245.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/freestat/rcomp/tmp/13utt81292763245.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/freestat/rcomp/tmp/14gcaw1292763245.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/freestat/rcomp/tmp/151cqk1292763245.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/freestat/rcomp/tmp/165v7q1292763245.tab")
+ }
>
> try(system("convert tmp/13hjc1292763245.ps tmp/13hjc1292763245.png",intern=TRUE))
character(0)
> try(system("convert tmp/2vq1x1292763245.ps tmp/2vq1x1292763245.png",intern=TRUE))
character(0)
> try(system("convert tmp/3vq1x1292763245.ps tmp/3vq1x1292763245.png",intern=TRUE))
character(0)
> try(system("convert tmp/4vq1x1292763245.ps tmp/4vq1x1292763245.png",intern=TRUE))
character(0)
> try(system("convert tmp/56iii1292763245.ps tmp/56iii1292763245.png",intern=TRUE))
character(0)
> try(system("convert tmp/66iii1292763245.ps tmp/66iii1292763245.png",intern=TRUE))
character(0)
> try(system("convert tmp/7hrzl1292763245.ps tmp/7hrzl1292763245.png",intern=TRUE))
character(0)
> try(system("convert tmp/8hrzl1292763245.ps tmp/8hrzl1292763245.png",intern=TRUE))
character(0)
> try(system("convert tmp/990g51292763245.ps tmp/990g51292763245.png",intern=TRUE))
character(0)
> try(system("convert tmp/1090g51292763245.ps tmp/1090g51292763245.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.765 2.429 4.156