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.
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(124.9,1487.6,132,1320.9,151.4,1514,108.9,1290.9,121.3,1392.5,123.4,1288.2,90.3,1304.4,79.3,1297.8,117.2,1211,116.9,1454,120.8,1405.7,96.1,1160.8,100.8,1492.1,105.3,1263,116.1,1376.3,112.8,1368.6,114.5,1427.6,117.2,1339.8,77.1,1248.3,80.1,1309.8,120.3,1424,133.4,1590.5,109.4,1423.1,93.2,1355.3,91.2,1515,99.2,1385.6,108.2,1430,101.5,1494.2,106.9,1580.9,104.4,1369.8,77.9,1407.5,60,1388.3,99.5,1478.5,95,1630.4,105.6,1413.5,102.5,1493.8,93.3,1641.3,97.3,1465,127,1725.1,111.7,1628.4,96.4,1679.8,133,1876,72.2,1669.4,95.8,1712.4,124.1,1768.8,127.6,1820.5,110.7,1776.2,104.6,1693.7,112.7,1799.1,115.3,1917.5,139.4,1887.2,119,1787.8,97.4,1803.8,154,2196.4,81.5,1759.5,88.8,2002.6,127.7,2056.8,105.1,1851.1,114.9,1984.3,106.4,1725.3,104.5,2096.6,121.6,1792.2,141.4,2029.9,99,1785.3,126.7,2026.5,134.1,1930.8,81.3,1845.5,88.6,1943.1,132.7,2066.8,132.9,2354.4,134.4,2190.7,103.7,1929.6),dim=c(2,72),dimnames=list(c('transport','Import'),1:72))
> y <- array(NA,dim=c(2,72),dimnames=list(c('transport','Import'),1:72))
> 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 = '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
transport Import M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 124.9 1487.6 1 0 0 0 0 0 0 0 0 0 0 1
2 132.0 1320.9 0 1 0 0 0 0 0 0 0 0 0 2
3 151.4 1514.0 0 0 1 0 0 0 0 0 0 0 0 3
4 108.9 1290.9 0 0 0 1 0 0 0 0 0 0 0 4
5 121.3 1392.5 0 0 0 0 1 0 0 0 0 0 0 5
6 123.4 1288.2 0 0 0 0 0 1 0 0 0 0 0 6
7 90.3 1304.4 0 0 0 0 0 0 1 0 0 0 0 7
8 79.3 1297.8 0 0 0 0 0 0 0 1 0 0 0 8
9 117.2 1211.0 0 0 0 0 0 0 0 0 1 0 0 9
10 116.9 1454.0 0 0 0 0 0 0 0 0 0 1 0 10
11 120.8 1405.7 0 0 0 0 0 0 0 0 0 0 1 11
12 96.1 1160.8 0 0 0 0 0 0 0 0 0 0 0 12
13 100.8 1492.1 1 0 0 0 0 0 0 0 0 0 0 13
14 105.3 1263.0 0 1 0 0 0 0 0 0 0 0 0 14
15 116.1 1376.3 0 0 1 0 0 0 0 0 0 0 0 15
16 112.8 1368.6 0 0 0 1 0 0 0 0 0 0 0 16
17 114.5 1427.6 0 0 0 0 1 0 0 0 0 0 0 17
18 117.2 1339.8 0 0 0 0 0 1 0 0 0 0 0 18
19 77.1 1248.3 0 0 0 0 0 0 1 0 0 0 0 19
20 80.1 1309.8 0 0 0 0 0 0 0 1 0 0 0 20
21 120.3 1424.0 0 0 0 0 0 0 0 0 1 0 0 21
22 133.4 1590.5 0 0 0 0 0 0 0 0 0 1 0 22
23 109.4 1423.1 0 0 0 0 0 0 0 0 0 0 1 23
24 93.2 1355.3 0 0 0 0 0 0 0 0 0 0 0 24
25 91.2 1515.0 1 0 0 0 0 0 0 0 0 0 0 25
26 99.2 1385.6 0 1 0 0 0 0 0 0 0 0 0 26
27 108.2 1430.0 0 0 1 0 0 0 0 0 0 0 0 27
28 101.5 1494.2 0 0 0 1 0 0 0 0 0 0 0 28
29 106.9 1580.9 0 0 0 0 1 0 0 0 0 0 0 29
30 104.4 1369.8 0 0 0 0 0 1 0 0 0 0 0 30
31 77.9 1407.5 0 0 0 0 0 0 1 0 0 0 0 31
32 60.0 1388.3 0 0 0 0 0 0 0 1 0 0 0 32
33 99.5 1478.5 0 0 0 0 0 0 0 0 1 0 0 33
34 95.0 1630.4 0 0 0 0 0 0 0 0 0 1 0 34
35 105.6 1413.5 0 0 0 0 0 0 0 0 0 0 1 35
36 102.5 1493.8 0 0 0 0 0 0 0 0 0 0 0 36
37 93.3 1641.3 1 0 0 0 0 0 0 0 0 0 0 37
38 97.3 1465.0 0 1 0 0 0 0 0 0 0 0 0 38
39 127.0 1725.1 0 0 1 0 0 0 0 0 0 0 0 39
40 111.7 1628.4 0 0 0 1 0 0 0 0 0 0 0 40
41 96.4 1679.8 0 0 0 0 1 0 0 0 0 0 0 41
42 133.0 1876.0 0 0 0 0 0 1 0 0 0 0 0 42
43 72.2 1669.4 0 0 0 0 0 0 1 0 0 0 0 43
44 95.8 1712.4 0 0 0 0 0 0 0 1 0 0 0 44
45 124.1 1768.8 0 0 0 0 0 0 0 0 1 0 0 45
46 127.6 1820.5 0 0 0 0 0 0 0 0 0 1 0 46
47 110.7 1776.2 0 0 0 0 0 0 0 0 0 0 1 47
48 104.6 1693.7 0 0 0 0 0 0 0 0 0 0 0 48
49 112.7 1799.1 1 0 0 0 0 0 0 0 0 0 0 49
50 115.3 1917.5 0 1 0 0 0 0 0 0 0 0 0 50
51 139.4 1887.2 0 0 1 0 0 0 0 0 0 0 0 51
52 119.0 1787.8 0 0 0 1 0 0 0 0 0 0 0 52
53 97.4 1803.8 0 0 0 0 1 0 0 0 0 0 0 53
54 154.0 2196.4 0 0 0 0 0 1 0 0 0 0 0 54
55 81.5 1759.5 0 0 0 0 0 0 1 0 0 0 0 55
56 88.8 2002.6 0 0 0 0 0 0 0 1 0 0 0 56
57 127.7 2056.8 0 0 0 0 0 0 0 0 1 0 0 57
58 105.1 1851.1 0 0 0 0 0 0 0 0 0 1 0 58
59 114.9 1984.3 0 0 0 0 0 0 0 0 0 0 1 59
60 106.4 1725.3 0 0 0 0 0 0 0 0 0 0 0 60
61 104.5 2096.6 1 0 0 0 0 0 0 0 0 0 0 61
62 121.6 1792.2 0 1 0 0 0 0 0 0 0 0 0 62
63 141.4 2029.9 0 0 1 0 0 0 0 0 0 0 0 63
64 99.0 1785.3 0 0 0 1 0 0 0 0 0 0 0 64
65 126.7 2026.5 0 0 0 0 1 0 0 0 0 0 0 65
66 134.1 1930.8 0 0 0 0 0 1 0 0 0 0 0 66
67 81.3 1845.5 0 0 0 0 0 0 1 0 0 0 0 67
68 88.6 1943.1 0 0 0 0 0 0 0 1 0 0 0 68
69 132.7 2066.8 0 0 0 0 0 0 0 0 1 0 0 69
70 132.9 2354.4 0 0 0 0 0 0 0 0 0 1 0 70
71 134.4 2190.7 0 0 0 0 0 0 0 0 0 0 1 71
72 103.7 1929.6 0 0 0 0 0 0 0 0 0 0 0 72
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Import M1 M2 M3 M4
12.45598 0.08027 -15.09938 4.86050 13.58428 0.81243
M5 M6 M7 M8 M9 M10
-4.03685 12.78114 -23.72901 -26.41892 7.89414 -2.29929
M11 t
2.84244 -0.87063
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-16.4198 -6.0561 -0.3087 6.2876 14.7352
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 12.455975 10.557965 1.180 0.24291
Import 0.080265 0.009313 8.618 5.69e-12 ***
M1 -15.099376 5.266853 -2.867 0.00577 **
M2 4.860502 4.808979 1.011 0.31635
M3 13.584279 5.123560 2.651 0.01032 *
M4 0.812433 4.818747 0.169 0.86670
M5 -4.036853 5.008944 -0.806 0.42358
M6 12.781136 5.015155 2.549 0.01349 *
M7 -23.729008 4.740770 -5.005 5.51e-06 ***
M8 -26.418924 4.810629 -5.492 9.22e-07 ***
M9 7.894145 4.909453 1.608 0.11328
M10 -2.299292 5.255409 -0.438 0.66337
M11 2.842444 4.926400 0.577 0.56618
t -0.870631 0.121532 -7.164 1.56e-09 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 8.176 on 58 degrees of freedom
Multiple R-squared: 0.848, Adjusted R-squared: 0.814
F-statistic: 24.9 on 13 and 58 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,] 0.19821574 0.3964315 0.8017843
[2,] 0.08818522 0.1763704 0.9118148
[3,] 0.11504942 0.2300988 0.8849506
[4,] 0.14914212 0.2982842 0.8508579
[5,] 0.20026141 0.4005228 0.7997386
[6,] 0.33728491 0.6745698 0.6627151
[7,] 0.25187201 0.5037440 0.7481280
[8,] 0.29487214 0.5897443 0.7051279
[9,] 0.22474578 0.4494916 0.7752542
[10,] 0.20368281 0.4073656 0.7963172
[11,] 0.15488130 0.3097626 0.8451187
[12,] 0.11407444 0.2281489 0.8859256
[13,] 0.09287721 0.1857544 0.9071228
[14,] 0.06628106 0.1325621 0.9337189
[15,] 0.05701755 0.1140351 0.9429824
[16,] 0.05095284 0.1019057 0.9490472
[17,] 0.07465669 0.1493134 0.9253433
[18,] 0.18010377 0.3602075 0.8198962
[19,] 0.22136584 0.4427317 0.7786342
[20,] 0.21243211 0.4248642 0.7875679
[21,] 0.16941890 0.3388378 0.8305811
[22,] 0.13429308 0.2685862 0.8657069
[23,] 0.10855003 0.2171001 0.8914500
[24,] 0.10028539 0.2005708 0.8997146
[25,] 0.10398767 0.2079753 0.8960123
[26,] 0.08441402 0.1688280 0.9155860
[27,] 0.09575903 0.1915181 0.9042410
[28,] 0.16565540 0.3313108 0.8343446
[29,] 0.11762883 0.2352577 0.8823712
[30,] 0.24500895 0.4900179 0.7549911
[31,] 0.19027638 0.3805528 0.8097236
[32,] 0.13427749 0.2685550 0.8657225
[33,] 0.37076747 0.7415349 0.6292325
[34,] 0.45879259 0.9175852 0.5412074
[35,] 0.40048333 0.8009667 0.5995167
[36,] 0.59176705 0.8164659 0.4082329
[37,] 0.76033111 0.4793378 0.2396689
[38,] 0.65527753 0.6894449 0.3447225
[39,] 0.52463507 0.9507299 0.4753649
> postscript(file="/var/www/html/freestat/rcomp/tmp/18hp71229557196.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/22gds1229557196.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/freestat/rcomp/tmp/3o41t1229557196.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4r35y1229557196.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5xcat1229557196.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 = 72
Frequency = 1
1 2 3 4 5 6
9.01132240 10.40230624 6.44992410 -4.50040289 5.46455571 -0.01112782
7 8 9 10 11 12
2.96934858 -3.94035344 7.48423925 -1.25616894 2.24954165 0.91959620
13 14 15 16 17 18
-5.00230157 -1.20276095 -7.34996951 3.61055076 6.29481255 0.09475103
19 20 21 22 23 24
4.71980380 6.34403259 3.93529334 14.73518314 -0.09950511 -7.14444104
25 26 27 28 29 30
-5.99280766 -6.69572075 -9.11264786 -7.32320504 -3.16229297 -4.66563893
31 32 33 34 35 36
3.18913281 -9.60922602 -10.79159727 -16.41983362 7.31861212 1.48638036
37 38 39 40 41 42
-3.58274919 -4.52121816 -3.55137761 2.55275730 -11.15296438 -6.24838048
43 44 45 46 47 48
-13.08478788 10.62434958 0.95494658 11.36929660 -6.24605414 -2.01108968
49 50 51 52 53 54
13.59895129 -12.39371132 6.28518194 7.50603325 -9.65829564 -0.51782315
55 56 57 58 59 60
-0.56912435 -9.22108003 -8.11389930 -3.13925255 -8.30169991 7.70009583
61 62 63 64 65 66
-8.03241526 14.41110494 7.27888895 -1.84573339 12.21418473 11.34821934
67 68 69 70 71 72
2.77562704 5.80227731 6.53101740 -5.28922463 5.07910539 -0.95054167
> postscript(file="/var/www/html/freestat/rcomp/tmp/6rx2c1229557196.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 = 72
Frequency = 1
lag(myerror, k = 1) myerror
0 9.01132240 NA
1 10.40230624 9.01132240
2 6.44992410 10.40230624
3 -4.50040289 6.44992410
4 5.46455571 -4.50040289
5 -0.01112782 5.46455571
6 2.96934858 -0.01112782
7 -3.94035344 2.96934858
8 7.48423925 -3.94035344
9 -1.25616894 7.48423925
10 2.24954165 -1.25616894
11 0.91959620 2.24954165
12 -5.00230157 0.91959620
13 -1.20276095 -5.00230157
14 -7.34996951 -1.20276095
15 3.61055076 -7.34996951
16 6.29481255 3.61055076
17 0.09475103 6.29481255
18 4.71980380 0.09475103
19 6.34403259 4.71980380
20 3.93529334 6.34403259
21 14.73518314 3.93529334
22 -0.09950511 14.73518314
23 -7.14444104 -0.09950511
24 -5.99280766 -7.14444104
25 -6.69572075 -5.99280766
26 -9.11264786 -6.69572075
27 -7.32320504 -9.11264786
28 -3.16229297 -7.32320504
29 -4.66563893 -3.16229297
30 3.18913281 -4.66563893
31 -9.60922602 3.18913281
32 -10.79159727 -9.60922602
33 -16.41983362 -10.79159727
34 7.31861212 -16.41983362
35 1.48638036 7.31861212
36 -3.58274919 1.48638036
37 -4.52121816 -3.58274919
38 -3.55137761 -4.52121816
39 2.55275730 -3.55137761
40 -11.15296438 2.55275730
41 -6.24838048 -11.15296438
42 -13.08478788 -6.24838048
43 10.62434958 -13.08478788
44 0.95494658 10.62434958
45 11.36929660 0.95494658
46 -6.24605414 11.36929660
47 -2.01108968 -6.24605414
48 13.59895129 -2.01108968
49 -12.39371132 13.59895129
50 6.28518194 -12.39371132
51 7.50603325 6.28518194
52 -9.65829564 7.50603325
53 -0.51782315 -9.65829564
54 -0.56912435 -0.51782315
55 -9.22108003 -0.56912435
56 -8.11389930 -9.22108003
57 -3.13925255 -8.11389930
58 -8.30169991 -3.13925255
59 7.70009583 -8.30169991
60 -8.03241526 7.70009583
61 14.41110494 -8.03241526
62 7.27888895 14.41110494
63 -1.84573339 7.27888895
64 12.21418473 -1.84573339
65 11.34821934 12.21418473
66 2.77562704 11.34821934
67 5.80227731 2.77562704
68 6.53101740 5.80227731
69 -5.28922463 6.53101740
70 5.07910539 -5.28922463
71 -0.95054167 5.07910539
72 NA -0.95054167
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 10.40230624 9.01132240
[2,] 6.44992410 10.40230624
[3,] -4.50040289 6.44992410
[4,] 5.46455571 -4.50040289
[5,] -0.01112782 5.46455571
[6,] 2.96934858 -0.01112782
[7,] -3.94035344 2.96934858
[8,] 7.48423925 -3.94035344
[9,] -1.25616894 7.48423925
[10,] 2.24954165 -1.25616894
[11,] 0.91959620 2.24954165
[12,] -5.00230157 0.91959620
[13,] -1.20276095 -5.00230157
[14,] -7.34996951 -1.20276095
[15,] 3.61055076 -7.34996951
[16,] 6.29481255 3.61055076
[17,] 0.09475103 6.29481255
[18,] 4.71980380 0.09475103
[19,] 6.34403259 4.71980380
[20,] 3.93529334 6.34403259
[21,] 14.73518314 3.93529334
[22,] -0.09950511 14.73518314
[23,] -7.14444104 -0.09950511
[24,] -5.99280766 -7.14444104
[25,] -6.69572075 -5.99280766
[26,] -9.11264786 -6.69572075
[27,] -7.32320504 -9.11264786
[28,] -3.16229297 -7.32320504
[29,] -4.66563893 -3.16229297
[30,] 3.18913281 -4.66563893
[31,] -9.60922602 3.18913281
[32,] -10.79159727 -9.60922602
[33,] -16.41983362 -10.79159727
[34,] 7.31861212 -16.41983362
[35,] 1.48638036 7.31861212
[36,] -3.58274919 1.48638036
[37,] -4.52121816 -3.58274919
[38,] -3.55137761 -4.52121816
[39,] 2.55275730 -3.55137761
[40,] -11.15296438 2.55275730
[41,] -6.24838048 -11.15296438
[42,] -13.08478788 -6.24838048
[43,] 10.62434958 -13.08478788
[44,] 0.95494658 10.62434958
[45,] 11.36929660 0.95494658
[46,] -6.24605414 11.36929660
[47,] -2.01108968 -6.24605414
[48,] 13.59895129 -2.01108968
[49,] -12.39371132 13.59895129
[50,] 6.28518194 -12.39371132
[51,] 7.50603325 6.28518194
[52,] -9.65829564 7.50603325
[53,] -0.51782315 -9.65829564
[54,] -0.56912435 -0.51782315
[55,] -9.22108003 -0.56912435
[56,] -8.11389930 -9.22108003
[57,] -3.13925255 -8.11389930
[58,] -8.30169991 -3.13925255
[59,] 7.70009583 -8.30169991
[60,] -8.03241526 7.70009583
[61,] 14.41110494 -8.03241526
[62,] 7.27888895 14.41110494
[63,] -1.84573339 7.27888895
[64,] 12.21418473 -1.84573339
[65,] 11.34821934 12.21418473
[66,] 2.77562704 11.34821934
[67,] 5.80227731 2.77562704
[68,] 6.53101740 5.80227731
[69,] -5.28922463 6.53101740
[70,] 5.07910539 -5.28922463
[71,] -0.95054167 5.07910539
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 10.40230624 9.01132240
2 6.44992410 10.40230624
3 -4.50040289 6.44992410
4 5.46455571 -4.50040289
5 -0.01112782 5.46455571
6 2.96934858 -0.01112782
7 -3.94035344 2.96934858
8 7.48423925 -3.94035344
9 -1.25616894 7.48423925
10 2.24954165 -1.25616894
11 0.91959620 2.24954165
12 -5.00230157 0.91959620
13 -1.20276095 -5.00230157
14 -7.34996951 -1.20276095
15 3.61055076 -7.34996951
16 6.29481255 3.61055076
17 0.09475103 6.29481255
18 4.71980380 0.09475103
19 6.34403259 4.71980380
20 3.93529334 6.34403259
21 14.73518314 3.93529334
22 -0.09950511 14.73518314
23 -7.14444104 -0.09950511
24 -5.99280766 -7.14444104
25 -6.69572075 -5.99280766
26 -9.11264786 -6.69572075
27 -7.32320504 -9.11264786
28 -3.16229297 -7.32320504
29 -4.66563893 -3.16229297
30 3.18913281 -4.66563893
31 -9.60922602 3.18913281
32 -10.79159727 -9.60922602
33 -16.41983362 -10.79159727
34 7.31861212 -16.41983362
35 1.48638036 7.31861212
36 -3.58274919 1.48638036
37 -4.52121816 -3.58274919
38 -3.55137761 -4.52121816
39 2.55275730 -3.55137761
40 -11.15296438 2.55275730
41 -6.24838048 -11.15296438
42 -13.08478788 -6.24838048
43 10.62434958 -13.08478788
44 0.95494658 10.62434958
45 11.36929660 0.95494658
46 -6.24605414 11.36929660
47 -2.01108968 -6.24605414
48 13.59895129 -2.01108968
49 -12.39371132 13.59895129
50 6.28518194 -12.39371132
51 7.50603325 6.28518194
52 -9.65829564 7.50603325
53 -0.51782315 -9.65829564
54 -0.56912435 -0.51782315
55 -9.22108003 -0.56912435
56 -8.11389930 -9.22108003
57 -3.13925255 -8.11389930
58 -8.30169991 -3.13925255
59 7.70009583 -8.30169991
60 -8.03241526 7.70009583
61 14.41110494 -8.03241526
62 7.27888895 14.41110494
63 -1.84573339 7.27888895
64 12.21418473 -1.84573339
65 11.34821934 12.21418473
66 2.77562704 11.34821934
67 5.80227731 2.77562704
68 6.53101740 5.80227731
69 -5.28922463 6.53101740
70 5.07910539 -5.28922463
71 -0.95054167 5.07910539
> 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/73ji01229557196.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8f6t11229557196.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9yhgi1229557196.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10sdiv1229557196.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ze5x1229557196.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/12jqyv1229557196.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/1309jo1229557196.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/14i1os1229557196.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/15fm5m1229557196.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/1624tv1229557196.tab")
+ }
>
> system("convert tmp/18hp71229557196.ps tmp/18hp71229557196.png")
> system("convert tmp/22gds1229557196.ps tmp/22gds1229557196.png")
> system("convert tmp/3o41t1229557196.ps tmp/3o41t1229557196.png")
> system("convert tmp/4r35y1229557196.ps tmp/4r35y1229557196.png")
> system("convert tmp/5xcat1229557196.ps tmp/5xcat1229557196.png")
> system("convert tmp/6rx2c1229557196.ps tmp/6rx2c1229557196.png")
> system("convert tmp/73ji01229557196.ps tmp/73ji01229557196.png")
> system("convert tmp/8f6t11229557196.ps tmp/8f6t11229557196.png")
> system("convert tmp/9yhgi1229557196.ps tmp/9yhgi1229557196.png")
> system("convert tmp/10sdiv1229557196.ps tmp/10sdiv1229557196.png")
>
>
> proc.time()
user system elapsed
3.823 2.527 4.334