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 'demo()' for some demos, 'help()' for on-line help, or
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> x <- array(list(921365,0,987921,0,1132614,0,1332224,0,1418133,0,1411549,0,1695920,0,1636173,0,1539653,0,1395314,0,1127575,0,1036076,0,989236,0,1008380,0,1207763,0,1368839,0,1469798,0,1498721,0,1761769,0,1653214,0,1599104,0,1421179,0,1163995,0,1037735,0,1015407,0,1039210,0,1258049,0,1469445,0,1552346,0,1549144,0,1785895,0,1662335,0,1629440,0,1467430,0,1202209,0,1076982,0,1039367,1,1063449,1,1335135,1,1491602,1,1591972,1,1641248,1,1898849,1,1798580,1,1762444,1,1622044,1,1368955,1,1262973,1,1195650,1,1269530,1,1479279,1,1607819,1,1712466,1,1721766,1,1949843,1,1821326,1,1757802,1,1590367,1,1260647,1,1149235,1),dim=c(2,60),dimnames=list(c('Y','X'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Y','X'),1:60))
> 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
Y X M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 921365 0 1 0 0 0 0 0 0 0 0 0 0
2 987921 0 0 1 0 0 0 0 0 0 0 0 0
3 1132614 0 0 0 1 0 0 0 0 0 0 0 0
4 1332224 0 0 0 0 1 0 0 0 0 0 0 0
5 1418133 0 0 0 0 0 1 0 0 0 0 0 0
6 1411549 0 0 0 0 0 0 1 0 0 0 0 0
7 1695920 0 0 0 0 0 0 0 1 0 0 0 0
8 1636173 0 0 0 0 0 0 0 0 1 0 0 0
9 1539653 0 0 0 0 0 0 0 0 0 1 0 0
10 1395314 0 0 0 0 0 0 0 0 0 0 1 0
11 1127575 0 0 0 0 0 0 0 0 0 0 0 1
12 1036076 0 0 0 0 0 0 0 0 0 0 0 0
13 989236 0 1 0 0 0 0 0 0 0 0 0 0
14 1008380 0 0 1 0 0 0 0 0 0 0 0 0
15 1207763 0 0 0 1 0 0 0 0 0 0 0 0
16 1368839 0 0 0 0 1 0 0 0 0 0 0 0
17 1469798 0 0 0 0 0 1 0 0 0 0 0 0
18 1498721 0 0 0 0 0 0 1 0 0 0 0 0
19 1761769 0 0 0 0 0 0 0 1 0 0 0 0
20 1653214 0 0 0 0 0 0 0 0 1 0 0 0
21 1599104 0 0 0 0 0 0 0 0 0 1 0 0
22 1421179 0 0 0 0 0 0 0 0 0 0 1 0
23 1163995 0 0 0 0 0 0 0 0 0 0 0 1
24 1037735 0 0 0 0 0 0 0 0 0 0 0 0
25 1015407 0 1 0 0 0 0 0 0 0 0 0 0
26 1039210 0 0 1 0 0 0 0 0 0 0 0 0
27 1258049 0 0 0 1 0 0 0 0 0 0 0 0
28 1469445 0 0 0 0 1 0 0 0 0 0 0 0
29 1552346 0 0 0 0 0 1 0 0 0 0 0 0
30 1549144 0 0 0 0 0 0 1 0 0 0 0 0
31 1785895 0 0 0 0 0 0 0 1 0 0 0 0
32 1662335 0 0 0 0 0 0 0 0 1 0 0 0
33 1629440 0 0 0 0 0 0 0 0 0 1 0 0
34 1467430 0 0 0 0 0 0 0 0 0 0 1 0
35 1202209 0 0 0 0 0 0 0 0 0 0 0 1
36 1076982 0 0 0 0 0 0 0 0 0 0 0 0
37 1039367 1 1 0 0 0 0 0 0 0 0 0 0
38 1063449 1 0 1 0 0 0 0 0 0 0 0 0
39 1335135 1 0 0 1 0 0 0 0 0 0 0 0
40 1491602 1 0 0 0 1 0 0 0 0 0 0 0
41 1591972 1 0 0 0 0 1 0 0 0 0 0 0
42 1641248 1 0 0 0 0 0 1 0 0 0 0 0
43 1898849 1 0 0 0 0 0 0 1 0 0 0 0
44 1798580 1 0 0 0 0 0 0 0 1 0 0 0
45 1762444 1 0 0 0 0 0 0 0 0 1 0 0
46 1622044 1 0 0 0 0 0 0 0 0 0 1 0
47 1368955 1 0 0 0 0 0 0 0 0 0 0 1
48 1262973 1 0 0 0 0 0 0 0 0 0 0 0
49 1195650 1 1 0 0 0 0 0 0 0 0 0 0
50 1269530 1 0 1 0 0 0 0 0 0 0 0 0
51 1479279 1 0 0 1 0 0 0 0 0 0 0 0
52 1607819 1 0 0 0 1 0 0 0 0 0 0 0
53 1712466 1 0 0 0 0 1 0 0 0 0 0 0
54 1721766 1 0 0 0 0 0 1 0 0 0 0 0
55 1949843 1 0 0 0 0 0 0 1 0 0 0 0
56 1821326 1 0 0 0 0 0 0 0 1 0 0 0
57 1757802 1 0 0 0 0 0 0 0 0 1 0 0
58 1590367 1 0 0 0 0 0 0 0 0 0 1 0
59 1260647 1 0 0 0 0 0 0 0 0 0 0 1
60 1149235 1 0 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
1045196 168511 -80395 -38902 169968 341386
M5 M6 M7 M8 M9 M10
436343 451885 705855 601725 545088 386667
M11
112076
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-111355 -31410 1863 36464 95605
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1045196 24952 41.888 < 2e-16 ***
X 168511 14311 11.775 1.27e-15 ***
M1 -80395 34346 -2.341 0.02354 *
M2 -38902 34346 -1.133 0.26311
M3 169968 34346 4.949 1.00e-05 ***
M4 341386 34346 9.940 3.89e-13 ***
M5 436343 34346 12.704 < 2e-16 ***
M6 451885 34346 13.157 < 2e-16 ***
M7 705855 34346 20.551 < 2e-16 ***
M8 601725 34346 17.519 < 2e-16 ***
M9 545088 34346 15.870 < 2e-16 ***
M10 386667 34346 11.258 6.10e-15 ***
M11 112076 34346 3.263 0.00206 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 54310 on 47 degrees of freedom
Multiple R-squared: 0.9684, Adjusted R-squared: 0.9604
F-statistic: 120.1 on 12 and 47 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,] 0.44265418 0.88530836 0.5573458
[2,] 0.36274131 0.72548262 0.6372587
[3,] 0.41944562 0.83889124 0.5805544
[4,] 0.38007072 0.76014144 0.6199293
[5,] 0.26726584 0.53453168 0.7327342
[6,] 0.22939792 0.45879585 0.7706021
[7,] 0.16544771 0.33089543 0.8345523
[8,] 0.11751700 0.23503399 0.8824830
[9,] 0.07397793 0.14795586 0.9260221
[10,] 0.06914223 0.13828447 0.9308578
[11,] 0.04934069 0.09868139 0.9506593
[12,] 0.06836353 0.13672706 0.9316365
[13,] 0.13486903 0.26973806 0.8651310
[14,] 0.17430095 0.34860190 0.8256990
[15,] 0.17703615 0.35407230 0.8229639
[16,] 0.13859990 0.27719979 0.8614001
[17,] 0.09308949 0.18617898 0.9069105
[18,] 0.06978992 0.13957984 0.9302101
[19,] 0.05083636 0.10167271 0.9491636
[20,] 0.03511243 0.07022487 0.9648876
[21,] 0.02128612 0.04257224 0.9787139
[22,] 0.02670570 0.05341140 0.9732943
[23,] 0.08286650 0.16573300 0.9171335
[24,] 0.15243740 0.30487481 0.8475626
[25,] 0.19038722 0.38077444 0.8096128
[26,] 0.27734180 0.55468359 0.7226582
[27,] 0.29187720 0.58375439 0.7081228
[28,] 0.22910192 0.45820383 0.7708981
[29,] 0.13620832 0.27241664 0.8637917
> postscript(file="/var/www/html/rcomp/tmp/1nvfe1261310534.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2lkdj1261310534.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3xzb71261310534.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4rayw1261310534.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5pvto1261310534.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 = 60
Frequency = 1
1 2 3 4 5 6
-43435.7778 -18372.7778 -82549.7778 -54357.5778 -63405.7778 -85532.3778
7 8 9 10 11 12
-55130.9778 -10748.3778 -50631.3778 -36548.5778 -29696.9778 -9119.9778
13 14 15 16 17 18
24435.2222 2086.2222 -7400.7778 -17742.5778 -11740.7778 1639.6222
19 20 21 22 23 24
10718.0222 6292.6222 8819.6222 -10683.5778 6723.0222 -7460.9778
25 26 27 28 29 30
50606.2222 32916.2222 42885.2222 82863.4222 70807.2222 52062.6222
31 32 33 34 35 36
34844.0222 15413.6222 39155.6222 35567.4222 44937.0222 31786.0222
37 38 39 40 41 42
-93944.3333 -111355.3333 -48539.3333 -63490.1333 -58077.3333 -24343.9333
43 44 45 46 47 48
-20712.5333 -16851.9333 3649.0667 21670.8667 43172.4667 49266.4667
49 50 51 52 53 54
62338.6667 94725.6667 95604.6667 52726.8667 62416.6667 56174.0667
55 56 57 58 59 60
30281.4667 5894.0667 -992.9333 -10006.1333 -65135.5333 -64471.5333
> postscript(file="/var/www/html/rcomp/tmp/65njr1261310534.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 -43435.7778 NA
1 -18372.7778 -43435.7778
2 -82549.7778 -18372.7778
3 -54357.5778 -82549.7778
4 -63405.7778 -54357.5778
5 -85532.3778 -63405.7778
6 -55130.9778 -85532.3778
7 -10748.3778 -55130.9778
8 -50631.3778 -10748.3778
9 -36548.5778 -50631.3778
10 -29696.9778 -36548.5778
11 -9119.9778 -29696.9778
12 24435.2222 -9119.9778
13 2086.2222 24435.2222
14 -7400.7778 2086.2222
15 -17742.5778 -7400.7778
16 -11740.7778 -17742.5778
17 1639.6222 -11740.7778
18 10718.0222 1639.6222
19 6292.6222 10718.0222
20 8819.6222 6292.6222
21 -10683.5778 8819.6222
22 6723.0222 -10683.5778
23 -7460.9778 6723.0222
24 50606.2222 -7460.9778
25 32916.2222 50606.2222
26 42885.2222 32916.2222
27 82863.4222 42885.2222
28 70807.2222 82863.4222
29 52062.6222 70807.2222
30 34844.0222 52062.6222
31 15413.6222 34844.0222
32 39155.6222 15413.6222
33 35567.4222 39155.6222
34 44937.0222 35567.4222
35 31786.0222 44937.0222
36 -93944.3333 31786.0222
37 -111355.3333 -93944.3333
38 -48539.3333 -111355.3333
39 -63490.1333 -48539.3333
40 -58077.3333 -63490.1333
41 -24343.9333 -58077.3333
42 -20712.5333 -24343.9333
43 -16851.9333 -20712.5333
44 3649.0667 -16851.9333
45 21670.8667 3649.0667
46 43172.4667 21670.8667
47 49266.4667 43172.4667
48 62338.6667 49266.4667
49 94725.6667 62338.6667
50 95604.6667 94725.6667
51 52726.8667 95604.6667
52 62416.6667 52726.8667
53 56174.0667 62416.6667
54 30281.4667 56174.0667
55 5894.0667 30281.4667
56 -992.9333 5894.0667
57 -10006.1333 -992.9333
58 -65135.5333 -10006.1333
59 -64471.5333 -65135.5333
60 NA -64471.5333
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -18372.7778 -43435.7778
[2,] -82549.7778 -18372.7778
[3,] -54357.5778 -82549.7778
[4,] -63405.7778 -54357.5778
[5,] -85532.3778 -63405.7778
[6,] -55130.9778 -85532.3778
[7,] -10748.3778 -55130.9778
[8,] -50631.3778 -10748.3778
[9,] -36548.5778 -50631.3778
[10,] -29696.9778 -36548.5778
[11,] -9119.9778 -29696.9778
[12,] 24435.2222 -9119.9778
[13,] 2086.2222 24435.2222
[14,] -7400.7778 2086.2222
[15,] -17742.5778 -7400.7778
[16,] -11740.7778 -17742.5778
[17,] 1639.6222 -11740.7778
[18,] 10718.0222 1639.6222
[19,] 6292.6222 10718.0222
[20,] 8819.6222 6292.6222
[21,] -10683.5778 8819.6222
[22,] 6723.0222 -10683.5778
[23,] -7460.9778 6723.0222
[24,] 50606.2222 -7460.9778
[25,] 32916.2222 50606.2222
[26,] 42885.2222 32916.2222
[27,] 82863.4222 42885.2222
[28,] 70807.2222 82863.4222
[29,] 52062.6222 70807.2222
[30,] 34844.0222 52062.6222
[31,] 15413.6222 34844.0222
[32,] 39155.6222 15413.6222
[33,] 35567.4222 39155.6222
[34,] 44937.0222 35567.4222
[35,] 31786.0222 44937.0222
[36,] -93944.3333 31786.0222
[37,] -111355.3333 -93944.3333
[38,] -48539.3333 -111355.3333
[39,] -63490.1333 -48539.3333
[40,] -58077.3333 -63490.1333
[41,] -24343.9333 -58077.3333
[42,] -20712.5333 -24343.9333
[43,] -16851.9333 -20712.5333
[44,] 3649.0667 -16851.9333
[45,] 21670.8667 3649.0667
[46,] 43172.4667 21670.8667
[47,] 49266.4667 43172.4667
[48,] 62338.6667 49266.4667
[49,] 94725.6667 62338.6667
[50,] 95604.6667 94725.6667
[51,] 52726.8667 95604.6667
[52,] 62416.6667 52726.8667
[53,] 56174.0667 62416.6667
[54,] 30281.4667 56174.0667
[55,] 5894.0667 30281.4667
[56,] -992.9333 5894.0667
[57,] -10006.1333 -992.9333
[58,] -65135.5333 -10006.1333
[59,] -64471.5333 -65135.5333
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -18372.7778 -43435.7778
2 -82549.7778 -18372.7778
3 -54357.5778 -82549.7778
4 -63405.7778 -54357.5778
5 -85532.3778 -63405.7778
6 -55130.9778 -85532.3778
7 -10748.3778 -55130.9778
8 -50631.3778 -10748.3778
9 -36548.5778 -50631.3778
10 -29696.9778 -36548.5778
11 -9119.9778 -29696.9778
12 24435.2222 -9119.9778
13 2086.2222 24435.2222
14 -7400.7778 2086.2222
15 -17742.5778 -7400.7778
16 -11740.7778 -17742.5778
17 1639.6222 -11740.7778
18 10718.0222 1639.6222
19 6292.6222 10718.0222
20 8819.6222 6292.6222
21 -10683.5778 8819.6222
22 6723.0222 -10683.5778
23 -7460.9778 6723.0222
24 50606.2222 -7460.9778
25 32916.2222 50606.2222
26 42885.2222 32916.2222
27 82863.4222 42885.2222
28 70807.2222 82863.4222
29 52062.6222 70807.2222
30 34844.0222 52062.6222
31 15413.6222 34844.0222
32 39155.6222 15413.6222
33 35567.4222 39155.6222
34 44937.0222 35567.4222
35 31786.0222 44937.0222
36 -93944.3333 31786.0222
37 -111355.3333 -93944.3333
38 -48539.3333 -111355.3333
39 -63490.1333 -48539.3333
40 -58077.3333 -63490.1333
41 -24343.9333 -58077.3333
42 -20712.5333 -24343.9333
43 -16851.9333 -20712.5333
44 3649.0667 -16851.9333
45 21670.8667 3649.0667
46 43172.4667 21670.8667
47 49266.4667 43172.4667
48 62338.6667 49266.4667
49 94725.6667 62338.6667
50 95604.6667 94725.6667
51 52726.8667 95604.6667
52 62416.6667 52726.8667
53 56174.0667 62416.6667
54 30281.4667 56174.0667
55 5894.0667 30281.4667
56 -992.9333 5894.0667
57 -10006.1333 -992.9333
58 -65135.5333 -10006.1333
59 -64471.5333 -65135.5333
> 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/7qdf01261310534.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/81wc81261310534.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9as7q1261310534.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ehso1261310534.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11zc5f1261310534.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/1220551261310534.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/1366xf1261310534.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/14fdgq1261310534.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/15oq5e1261310534.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/16nqj31261310534.tab")
+ }
>
> try(system("convert tmp/1nvfe1261310534.ps tmp/1nvfe1261310534.png",intern=TRUE))
character(0)
> try(system("convert tmp/2lkdj1261310534.ps tmp/2lkdj1261310534.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xzb71261310534.ps tmp/3xzb71261310534.png",intern=TRUE))
character(0)
> try(system("convert tmp/4rayw1261310534.ps tmp/4rayw1261310534.png",intern=TRUE))
character(0)
> try(system("convert tmp/5pvto1261310534.ps tmp/5pvto1261310534.png",intern=TRUE))
character(0)
> try(system("convert tmp/65njr1261310534.ps tmp/65njr1261310534.png",intern=TRUE))
character(0)
> try(system("convert tmp/7qdf01261310534.ps tmp/7qdf01261310534.png",intern=TRUE))
character(0)
> try(system("convert tmp/81wc81261310534.ps tmp/81wc81261310534.png",intern=TRUE))
character(0)
> try(system("convert tmp/9as7q1261310534.ps tmp/9as7q1261310534.png",intern=TRUE))
character(0)
> try(system("convert tmp/10ehso1261310534.ps tmp/10ehso1261310534.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.382 1.540 3.952