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.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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(8.5,99.2,8.6,116.5,8.5,98.4,8.2,90.6,8.1,130.5,7.9,107.4,8.6,106,8.7,196.5,8.7,107.8,8.5,90.5,8.4,123.8,8.5,114.7,8.7,115.3,8.7,197,8.6,88.4,8.5,93.8,8.3,111.3,8,105.9,8.2,123.6,8.1,171,8.1,97,8,99.2,7.9,126.6,7.9,103.4,8,121.3,8,129.6,7.9,110.8,8,98.9,7.7,122.8,7.2,120.9,7.5,133.1,7.3,203.1,7,110.2,7,119.5,7,135.1,7.2,113.9,7.3,137.4,7.1,157.1,6.8,126.4,6.4,112.2,6.1,128.8,6.5,136.8,7.7,156.5,7.9,215.2,7.5,146.7,6.9,130.8,6.6,133.1,6.9,153.4,7.7,159.9,8,174.6,8,145,7.7,112.9,7.3,137.8,7.4,150.6,8.1,162.1,8.3,226.4),dim=c(2,56),dimnames=list(c('X','Yt-2'),1:56))
> y <- array(NA,dim=c(2,56),dimnames=list(c('X','Yt-2'),1:56))
> 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 = 'Include Monthly Dummies'
> par1 = '2'
> #'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
Yt-2 X M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 99.2 8.5 1 0 0 0 0 0 0 0 0 0 0 1
2 116.5 8.6 0 1 0 0 0 0 0 0 0 0 0 2
3 98.4 8.5 0 0 1 0 0 0 0 0 0 0 0 3
4 90.6 8.2 0 0 0 1 0 0 0 0 0 0 0 4
5 130.5 8.1 0 0 0 0 1 0 0 0 0 0 0 5
6 107.4 7.9 0 0 0 0 0 1 0 0 0 0 0 6
7 106.0 8.6 0 0 0 0 0 0 1 0 0 0 0 7
8 196.5 8.7 0 0 0 0 0 0 0 1 0 0 0 8
9 107.8 8.7 0 0 0 0 0 0 0 0 1 0 0 9
10 90.5 8.5 0 0 0 0 0 0 0 0 0 1 0 10
11 123.8 8.4 0 0 0 0 0 0 0 0 0 0 1 11
12 114.7 8.5 0 0 0 0 0 0 0 0 0 0 0 12
13 115.3 8.7 1 0 0 0 0 0 0 0 0 0 0 13
14 197.0 8.7 0 1 0 0 0 0 0 0 0 0 0 14
15 88.4 8.6 0 0 1 0 0 0 0 0 0 0 0 15
16 93.8 8.5 0 0 0 1 0 0 0 0 0 0 0 16
17 111.3 8.3 0 0 0 0 1 0 0 0 0 0 0 17
18 105.9 8.0 0 0 0 0 0 1 0 0 0 0 0 18
19 123.6 8.2 0 0 0 0 0 0 1 0 0 0 0 19
20 171.0 8.1 0 0 0 0 0 0 0 1 0 0 0 20
21 97.0 8.1 0 0 0 0 0 0 0 0 1 0 0 21
22 99.2 8.0 0 0 0 0 0 0 0 0 0 1 0 22
23 126.6 7.9 0 0 0 0 0 0 0 0 0 0 1 23
24 103.4 7.9 0 0 0 0 0 0 0 0 0 0 0 24
25 121.3 8.0 1 0 0 0 0 0 0 0 0 0 0 25
26 129.6 8.0 0 1 0 0 0 0 0 0 0 0 0 26
27 110.8 7.9 0 0 1 0 0 0 0 0 0 0 0 27
28 98.9 8.0 0 0 0 1 0 0 0 0 0 0 0 28
29 122.8 7.7 0 0 0 0 1 0 0 0 0 0 0 29
30 120.9 7.2 0 0 0 0 0 1 0 0 0 0 0 30
31 133.1 7.5 0 0 0 0 0 0 1 0 0 0 0 31
32 203.1 7.3 0 0 0 0 0 0 0 1 0 0 0 32
33 110.2 7.0 0 0 0 0 0 0 0 0 1 0 0 33
34 119.5 7.0 0 0 0 0 0 0 0 0 0 1 0 34
35 135.1 7.0 0 0 0 0 0 0 0 0 0 0 1 35
36 113.9 7.2 0 0 0 0 0 0 0 0 0 0 0 36
37 137.4 7.3 1 0 0 0 0 0 0 0 0 0 0 37
38 157.1 7.1 0 1 0 0 0 0 0 0 0 0 0 38
39 126.4 6.8 0 0 1 0 0 0 0 0 0 0 0 39
40 112.2 6.4 0 0 0 1 0 0 0 0 0 0 0 40
41 128.8 6.1 0 0 0 0 1 0 0 0 0 0 0 41
42 136.8 6.5 0 0 0 0 0 1 0 0 0 0 0 42
43 156.5 7.7 0 0 0 0 0 0 1 0 0 0 0 43
44 215.2 7.9 0 0 0 0 0 0 0 1 0 0 0 44
45 146.7 7.5 0 0 0 0 0 0 0 0 1 0 0 45
46 130.8 6.9 0 0 0 0 0 0 0 0 0 1 0 46
47 133.1 6.6 0 0 0 0 0 0 0 0 0 0 1 47
48 153.4 6.9 0 0 0 0 0 0 0 0 0 0 0 48
49 159.9 7.7 1 0 0 0 0 0 0 0 0 0 0 49
50 174.6 8.0 0 1 0 0 0 0 0 0 0 0 0 50
51 145.0 8.0 0 0 1 0 0 0 0 0 0 0 0 51
52 112.9 7.7 0 0 0 1 0 0 0 0 0 0 0 52
53 137.8 7.3 0 0 0 0 1 0 0 0 0 0 0 53
54 150.6 7.4 0 0 0 0 0 1 0 0 0 0 0 54
55 162.1 8.1 0 0 0 0 0 0 1 0 0 0 0 55
56 226.4 8.3 0 0 0 0 0 0 0 1 0 0 0 56
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
54.448 4.891 8.175 35.332 -6.228 -18.356
M5 M6 M7 M8 M9 M10
6.488 4.070 11.991 76.989 -3.942 -9.254
M11 t
10.021 0.987
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-24.9687 -6.8783 -0.7588 6.0030 50.8511
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 54.4479 35.3695 1.539 0.13121
X 4.8909 4.1044 1.192 0.24009
M1 8.1750 9.2101 0.888 0.37980
M2 35.3324 9.2422 3.823 0.00043 ***
M3 -6.2276 9.1855 -0.678 0.50150
M4 -18.3564 9.1280 -2.011 0.05077 .
M5 6.4883 9.1408 0.710 0.48174
M6 4.0705 9.1656 0.444 0.65925
M7 11.9911 9.2822 1.292 0.20347
M8 76.9885 9.3388 8.244 2.56e-10 ***
M9 -3.9423 9.6310 -0.409 0.68437
M10 -9.2538 9.6201 -0.962 0.34159
M11 10.0206 9.6401 1.039 0.30453
t 0.9870 0.1567 6.299 1.48e-07 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 13.59 on 42 degrees of freedom
Multiple R-squared: 0.8626, Adjusted R-squared: 0.82
F-statistic: 20.28 on 13 and 42 DF, p-value: 5.195e-14
> 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,] 0.9999814 3.710197e-05 1.855098e-05
[2,] 0.9999681 6.373112e-05 3.186556e-05
[3,] 0.9999333 1.334294e-04 6.671470e-05
[4,] 0.9999592 8.162762e-05 4.081381e-05
[5,] 0.9998986 2.028649e-04 1.014325e-04
[6,] 0.9997462 5.075725e-04 2.537863e-04
[7,] 0.9996621 6.757437e-04 3.378718e-04
[8,] 0.9992532 1.493650e-03 7.468248e-04
[9,] 0.9984923 3.015498e-03 1.507749e-03
[10,] 0.9990482 1.903575e-03 9.517876e-04
[11,] 0.9983894 3.221274e-03 1.610637e-03
[12,] 0.9964390 7.122017e-03 3.561008e-03
[13,] 0.9951763 9.647418e-03 4.823709e-03
[14,] 0.9907785 1.844309e-02 9.221543e-03
[15,] 0.9836151 3.276973e-02 1.638486e-02
[16,] 0.9721945 5.561093e-02 2.780547e-02
[17,] 0.9804365 3.912691e-02 1.956346e-02
[18,] 0.9647889 7.042229e-02 3.521114e-02
[19,] 0.9921793 1.564150e-02 7.820750e-03
[20,] 0.9936352 1.272956e-02 6.364781e-03
[21,] 0.9908052 1.838954e-02 9.194770e-03
[22,] 0.9795663 4.086738e-02 2.043369e-02
[23,] 0.9771707 4.565852e-02 2.282926e-02
> postscript(file="/var/www/html/rcomp/tmp/1v32f1258810444.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2dou41258810444.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3559v1258810444.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4difz1258810444.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5xsnv1258810444.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 = 56
Frequency = 1
1 2 3 4 5 6
-5.9828672 -17.3163237 5.6458575 10.4549516 25.0124010 4.3214951
7 8 9 10 11 12
-9.4097801 14.6167634 5.8606509 -6.1366226 7.3911039 6.8356509
13 14 15 16 17 18
-2.7045382 50.8510995 -16.6867194 0.3441866 -7.0092699 -9.5110817
19 20 21 22 23 24
-1.6968866 -19.7921549 -13.8482673 -6.8346349 0.7930915 -13.3732673
25 26 27 28 29 30
-5.1243624 -24.9687247 -2.7065436 -3.9538258 -4.4181882 -2.4418118
31 32 33 34 35 36
-0.6167108 4.3771150 -7.1117152 6.5128231 1.8514555 -11.2930915
37 38 39 40 41 42
2.5558134 -4.9103608 6.4300086 5.3281968 -2.4361656 5.0383640
43 44 45 46 47 48
9.9616183 1.6990678 15.0993316 6.4584344 -10.0356509 17.8307079
49 50 51 52 53 54
11.2559543 -3.6556903 7.3173968 -12.1735091 -11.1487774 2.5930345
55 56
1.7617592 -0.9007913
> postscript(file="/var/www/html/rcomp/tmp/6ukbo1258810444.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 = 56
Frequency = 1
lag(myerror, k = 1) myerror
0 -5.9828672 NA
1 -17.3163237 -5.9828672
2 5.6458575 -17.3163237
3 10.4549516 5.6458575
4 25.0124010 10.4549516
5 4.3214951 25.0124010
6 -9.4097801 4.3214951
7 14.6167634 -9.4097801
8 5.8606509 14.6167634
9 -6.1366226 5.8606509
10 7.3911039 -6.1366226
11 6.8356509 7.3911039
12 -2.7045382 6.8356509
13 50.8510995 -2.7045382
14 -16.6867194 50.8510995
15 0.3441866 -16.6867194
16 -7.0092699 0.3441866
17 -9.5110817 -7.0092699
18 -1.6968866 -9.5110817
19 -19.7921549 -1.6968866
20 -13.8482673 -19.7921549
21 -6.8346349 -13.8482673
22 0.7930915 -6.8346349
23 -13.3732673 0.7930915
24 -5.1243624 -13.3732673
25 -24.9687247 -5.1243624
26 -2.7065436 -24.9687247
27 -3.9538258 -2.7065436
28 -4.4181882 -3.9538258
29 -2.4418118 -4.4181882
30 -0.6167108 -2.4418118
31 4.3771150 -0.6167108
32 -7.1117152 4.3771150
33 6.5128231 -7.1117152
34 1.8514555 6.5128231
35 -11.2930915 1.8514555
36 2.5558134 -11.2930915
37 -4.9103608 2.5558134
38 6.4300086 -4.9103608
39 5.3281968 6.4300086
40 -2.4361656 5.3281968
41 5.0383640 -2.4361656
42 9.9616183 5.0383640
43 1.6990678 9.9616183
44 15.0993316 1.6990678
45 6.4584344 15.0993316
46 -10.0356509 6.4584344
47 17.8307079 -10.0356509
48 11.2559543 17.8307079
49 -3.6556903 11.2559543
50 7.3173968 -3.6556903
51 -12.1735091 7.3173968
52 -11.1487774 -12.1735091
53 2.5930345 -11.1487774
54 1.7617592 2.5930345
55 -0.9007913 1.7617592
56 NA -0.9007913
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -17.3163237 -5.9828672
[2,] 5.6458575 -17.3163237
[3,] 10.4549516 5.6458575
[4,] 25.0124010 10.4549516
[5,] 4.3214951 25.0124010
[6,] -9.4097801 4.3214951
[7,] 14.6167634 -9.4097801
[8,] 5.8606509 14.6167634
[9,] -6.1366226 5.8606509
[10,] 7.3911039 -6.1366226
[11,] 6.8356509 7.3911039
[12,] -2.7045382 6.8356509
[13,] 50.8510995 -2.7045382
[14,] -16.6867194 50.8510995
[15,] 0.3441866 -16.6867194
[16,] -7.0092699 0.3441866
[17,] -9.5110817 -7.0092699
[18,] -1.6968866 -9.5110817
[19,] -19.7921549 -1.6968866
[20,] -13.8482673 -19.7921549
[21,] -6.8346349 -13.8482673
[22,] 0.7930915 -6.8346349
[23,] -13.3732673 0.7930915
[24,] -5.1243624 -13.3732673
[25,] -24.9687247 -5.1243624
[26,] -2.7065436 -24.9687247
[27,] -3.9538258 -2.7065436
[28,] -4.4181882 -3.9538258
[29,] -2.4418118 -4.4181882
[30,] -0.6167108 -2.4418118
[31,] 4.3771150 -0.6167108
[32,] -7.1117152 4.3771150
[33,] 6.5128231 -7.1117152
[34,] 1.8514555 6.5128231
[35,] -11.2930915 1.8514555
[36,] 2.5558134 -11.2930915
[37,] -4.9103608 2.5558134
[38,] 6.4300086 -4.9103608
[39,] 5.3281968 6.4300086
[40,] -2.4361656 5.3281968
[41,] 5.0383640 -2.4361656
[42,] 9.9616183 5.0383640
[43,] 1.6990678 9.9616183
[44,] 15.0993316 1.6990678
[45,] 6.4584344 15.0993316
[46,] -10.0356509 6.4584344
[47,] 17.8307079 -10.0356509
[48,] 11.2559543 17.8307079
[49,] -3.6556903 11.2559543
[50,] 7.3173968 -3.6556903
[51,] -12.1735091 7.3173968
[52,] -11.1487774 -12.1735091
[53,] 2.5930345 -11.1487774
[54,] 1.7617592 2.5930345
[55,] -0.9007913 1.7617592
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -17.3163237 -5.9828672
2 5.6458575 -17.3163237
3 10.4549516 5.6458575
4 25.0124010 10.4549516
5 4.3214951 25.0124010
6 -9.4097801 4.3214951
7 14.6167634 -9.4097801
8 5.8606509 14.6167634
9 -6.1366226 5.8606509
10 7.3911039 -6.1366226
11 6.8356509 7.3911039
12 -2.7045382 6.8356509
13 50.8510995 -2.7045382
14 -16.6867194 50.8510995
15 0.3441866 -16.6867194
16 -7.0092699 0.3441866
17 -9.5110817 -7.0092699
18 -1.6968866 -9.5110817
19 -19.7921549 -1.6968866
20 -13.8482673 -19.7921549
21 -6.8346349 -13.8482673
22 0.7930915 -6.8346349
23 -13.3732673 0.7930915
24 -5.1243624 -13.3732673
25 -24.9687247 -5.1243624
26 -2.7065436 -24.9687247
27 -3.9538258 -2.7065436
28 -4.4181882 -3.9538258
29 -2.4418118 -4.4181882
30 -0.6167108 -2.4418118
31 4.3771150 -0.6167108
32 -7.1117152 4.3771150
33 6.5128231 -7.1117152
34 1.8514555 6.5128231
35 -11.2930915 1.8514555
36 2.5558134 -11.2930915
37 -4.9103608 2.5558134
38 6.4300086 -4.9103608
39 5.3281968 6.4300086
40 -2.4361656 5.3281968
41 5.0383640 -2.4361656
42 9.9616183 5.0383640
43 1.6990678 9.9616183
44 15.0993316 1.6990678
45 6.4584344 15.0993316
46 -10.0356509 6.4584344
47 17.8307079 -10.0356509
48 11.2559543 17.8307079
49 -3.6556903 11.2559543
50 7.3173968 -3.6556903
51 -12.1735091 7.3173968
52 -11.1487774 -12.1735091
53 2.5930345 -11.1487774
54 1.7617592 2.5930345
55 -0.9007913 1.7617592
> 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/7wwn61258810444.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8koii1258810444.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/92t001258810444.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ndal1258810444.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11rknb1258810444.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/12n8u81258810444.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/13iqk81258810444.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/14rlsq1258810444.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/15d9si1258810444.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/16ddqx1258810444.tab")
+ }
>
> system("convert tmp/1v32f1258810444.ps tmp/1v32f1258810444.png")
> system("convert tmp/2dou41258810444.ps tmp/2dou41258810444.png")
> system("convert tmp/3559v1258810444.ps tmp/3559v1258810444.png")
> system("convert tmp/4difz1258810444.ps tmp/4difz1258810444.png")
> system("convert tmp/5xsnv1258810444.ps tmp/5xsnv1258810444.png")
> system("convert tmp/6ukbo1258810444.ps tmp/6ukbo1258810444.png")
> system("convert tmp/7wwn61258810444.ps tmp/7wwn61258810444.png")
> system("convert tmp/8koii1258810444.ps tmp/8koii1258810444.png")
> system("convert tmp/92t001258810444.ps tmp/92t001258810444.png")
> system("convert tmp/10ndal1258810444.ps tmp/10ndal1258810444.png")
>
>
> proc.time()
user system elapsed
2.340 1.544 3.463