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(92.7,0,105.2,0,91.5,0,75.3,0,60.5,0,80.4,0,84.5,0,93.9,0,78,0,92.3,0,90,0,72.1,0,76.9,0,76,0,88.7,0,55.4,0,46.6,0,90.9,0,84.9,0,89,0,90.2,0,72.3,0,83,0,71.6,0,75.4,0,85.1,0,81.2,0,68.7,0,68.4,0,93.7,0,96.6,0,101.8,0,93.6,0,88.9,0,114.1,0,82.3,0,96.4,0,104,0,88.2,0,85.2,0,87.1,0,85.5,0,89.1,0,105.2,0,82.9,0,86.8,0,112,0,97.4,0,88.9,0,109.4,0,87.8,0,90.5,0,79.3,0,114.9,0,118.8,0,125,0,96.1,0,116.7,0,119.5,0,104.1,0,121,0,127.3,0,117.7,0,108,0,89.4,0,137.4,1,142,1,137.3,1,122.8,1,126.1,1,147.6,1,115.7,1,139.2,1,151.2,1,123.8,1,109,1,112.1,1,136.4,1,135.5,1,138.7,1,137.5,1,141.5,1,143.6,1,146.5,1,200.7,1),dim=c(2,85),dimnames=list(c('L&S','D'),1:85))
> y <- array(NA,dim=c(2,85),dimnames=list(c('L&S','D'),1:85))
> 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)
> 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
L&S D M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 92.7 0 1 0 0 0 0 0 0 0 0 0 0 1
2 105.2 0 0 1 0 0 0 0 0 0 0 0 0 2
3 91.5 0 0 0 1 0 0 0 0 0 0 0 0 3
4 75.3 0 0 0 0 1 0 0 0 0 0 0 0 4
5 60.5 0 0 0 0 0 1 0 0 0 0 0 0 5
6 80.4 0 0 0 0 0 0 1 0 0 0 0 0 6
7 84.5 0 0 0 0 0 0 0 1 0 0 0 0 7
8 93.9 0 0 0 0 0 0 0 0 1 0 0 0 8
9 78.0 0 0 0 0 0 0 0 0 0 1 0 0 9
10 92.3 0 0 0 0 0 0 0 0 0 0 1 0 10
11 90.0 0 0 0 0 0 0 0 0 0 0 0 1 11
12 72.1 0 0 0 0 0 0 0 0 0 0 0 0 12
13 76.9 0 1 0 0 0 0 0 0 0 0 0 0 13
14 76.0 0 0 1 0 0 0 0 0 0 0 0 0 14
15 88.7 0 0 0 1 0 0 0 0 0 0 0 0 15
16 55.4 0 0 0 0 1 0 0 0 0 0 0 0 16
17 46.6 0 0 0 0 0 1 0 0 0 0 0 0 17
18 90.9 0 0 0 0 0 0 1 0 0 0 0 0 18
19 84.9 0 0 0 0 0 0 0 1 0 0 0 0 19
20 89.0 0 0 0 0 0 0 0 0 1 0 0 0 20
21 90.2 0 0 0 0 0 0 0 0 0 1 0 0 21
22 72.3 0 0 0 0 0 0 0 0 0 0 1 0 22
23 83.0 0 0 0 0 0 0 0 0 0 0 0 1 23
24 71.6 0 0 0 0 0 0 0 0 0 0 0 0 24
25 75.4 0 1 0 0 0 0 0 0 0 0 0 0 25
26 85.1 0 0 1 0 0 0 0 0 0 0 0 0 26
27 81.2 0 0 0 1 0 0 0 0 0 0 0 0 27
28 68.7 0 0 0 0 1 0 0 0 0 0 0 0 28
29 68.4 0 0 0 0 0 1 0 0 0 0 0 0 29
30 93.7 0 0 0 0 0 0 1 0 0 0 0 0 30
31 96.6 0 0 0 0 0 0 0 1 0 0 0 0 31
32 101.8 0 0 0 0 0 0 0 0 1 0 0 0 32
33 93.6 0 0 0 0 0 0 0 0 0 1 0 0 33
34 88.9 0 0 0 0 0 0 0 0 0 0 1 0 34
35 114.1 0 0 0 0 0 0 0 0 0 0 0 1 35
36 82.3 0 0 0 0 0 0 0 0 0 0 0 0 36
37 96.4 0 1 0 0 0 0 0 0 0 0 0 0 37
38 104.0 0 0 1 0 0 0 0 0 0 0 0 0 38
39 88.2 0 0 0 1 0 0 0 0 0 0 0 0 39
40 85.2 0 0 0 0 1 0 0 0 0 0 0 0 40
41 87.1 0 0 0 0 0 1 0 0 0 0 0 0 41
42 85.5 0 0 0 0 0 0 1 0 0 0 0 0 42
43 89.1 0 0 0 0 0 0 0 1 0 0 0 0 43
44 105.2 0 0 0 0 0 0 0 0 1 0 0 0 44
45 82.9 0 0 0 0 0 0 0 0 0 1 0 0 45
46 86.8 0 0 0 0 0 0 0 0 0 0 1 0 46
47 112.0 0 0 0 0 0 0 0 0 0 0 0 1 47
48 97.4 0 0 0 0 0 0 0 0 0 0 0 0 48
49 88.9 0 1 0 0 0 0 0 0 0 0 0 0 49
50 109.4 0 0 1 0 0 0 0 0 0 0 0 0 50
51 87.8 0 0 0 1 0 0 0 0 0 0 0 0 51
52 90.5 0 0 0 0 1 0 0 0 0 0 0 0 52
53 79.3 0 0 0 0 0 1 0 0 0 0 0 0 53
54 114.9 0 0 0 0 0 0 1 0 0 0 0 0 54
55 118.8 0 0 0 0 0 0 0 1 0 0 0 0 55
56 125.0 0 0 0 0 0 0 0 0 1 0 0 0 56
57 96.1 0 0 0 0 0 0 0 0 0 1 0 0 57
58 116.7 0 0 0 0 0 0 0 0 0 0 1 0 58
59 119.5 0 0 0 0 0 0 0 0 0 0 0 1 59
60 104.1 0 0 0 0 0 0 0 0 0 0 0 0 60
61 121.0 0 1 0 0 0 0 0 0 0 0 0 0 61
62 127.3 0 0 1 0 0 0 0 0 0 0 0 0 62
63 117.7 0 0 0 1 0 0 0 0 0 0 0 0 63
64 108.0 0 0 0 0 1 0 0 0 0 0 0 0 64
65 89.4 0 0 0 0 0 1 0 0 0 0 0 0 65
66 137.4 1 0 0 0 0 0 1 0 0 0 0 0 66
67 142.0 1 0 0 0 0 0 0 1 0 0 0 0 67
68 137.3 1 0 0 0 0 0 0 0 1 0 0 0 68
69 122.8 1 0 0 0 0 0 0 0 0 1 0 0 69
70 126.1 1 0 0 0 0 0 0 0 0 0 1 0 70
71 147.6 1 0 0 0 0 0 0 0 0 0 0 1 71
72 115.7 1 0 0 0 0 0 0 0 0 0 0 0 72
73 139.2 1 1 0 0 0 0 0 0 0 0 0 0 73
74 151.2 1 0 1 0 0 0 0 0 0 0 0 0 74
75 123.8 1 0 0 1 0 0 0 0 0 0 0 0 75
76 109.0 1 0 0 0 1 0 0 0 0 0 0 0 76
77 112.1 1 0 0 0 0 1 0 0 0 0 0 0 77
78 136.4 1 0 0 0 0 0 1 0 0 0 0 0 78
79 135.5 1 0 0 0 0 0 0 1 0 0 0 0 79
80 138.7 1 0 0 0 0 0 0 0 1 0 0 0 80
81 137.5 1 0 0 0 0 0 0 0 0 1 0 0 81
82 141.5 1 0 0 0 0 0 0 0 0 0 1 0 82
83 143.6 1 0 0 0 0 0 0 0 0 0 0 1 83
84 146.5 1 0 0 0 0 0 0 0 0 0 0 0 84
85 200.7 1 1 0 0 0 0 0 0 0 0 0 0 85
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) D M1 M2 M3 M4
65.0887 20.0648 16.4742 18.4244 6.5186 -6.4586
M5 M6 M7 M8 M9 M10
-13.9930 10.5348 11.7004 16.7661 3.3603 6.1402
M11 t
17.7344 0.5772
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-20.9472 -6.5204 0.7596 6.1024 50.0077
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 65.0887 5.2120 12.488 < 2e-16 ***
D 20.0648 4.3986 4.562 2.07e-05 ***
M1 16.4742 5.9878 2.751 0.00753 **
M2 18.4244 6.1990 2.972 0.00404 **
M3 6.5186 6.1959 1.052 0.29633
M4 -6.4586 6.1936 -1.043 0.30059
M5 -13.9930 6.1923 -2.260 0.02691 *
M6 10.5348 6.1939 1.701 0.09335 .
M7 11.7004 6.1888 1.891 0.06276 .
M8 16.7661 6.1846 2.711 0.00841 **
M9 3.3603 6.1814 0.544 0.58841
M10 6.1402 6.1790 0.994 0.32374
M11 17.7344 6.1776 2.871 0.00539 **
t 0.5772 0.0757 7.625 8.28e-11 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 11.56 on 71 degrees of freedom
Multiple R-squared: 0.8337, Adjusted R-squared: 0.8033
F-statistic: 27.39 on 13 and 71 DF, p-value: < 2.2e-16
> postscript(file="/var/www/html/rcomp/tmp/1ofdn1227793249.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/20zqy1227793249.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/30vh61227793249.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4rszj1227793249.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/51jbk1227793249.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 85
Frequency = 1
1 2 3 4 5 6
10.55985099 20.53238529 18.16095672 14.36095672 6.51809957 1.31307356
7 8 9 10 11 12
3.67021641 7.42735927 4.35593070 15.29878784 0.82735927 0.08450213
13 14 15 16 17 18
-12.16690516 -15.59437086 8.43420057 -12.46579943 -14.30865658 4.88631741
19 20 21 22 23 24
-2.85653974 -4.39939688 9.62917455 -11.62796831 -13.09939688 -7.34225402
25 26 27 28 29 30
-20.59366131 -13.42112701 -5.99255558 -6.09255558 0.56458728 0.75956126
31 32 33 34 35 36
1.91670412 1.47384697 6.10241840 -1.95472446 11.07384697 -3.56901017
37 38 39 40 41 42
-6.52041746 -1.44788316 -5.91931173 3.48068827 12.33783113 -14.36719489
43 44 45 46 47 48
-12.51005203 -2.05290918 -11.52433775 -10.98148061 2.04709082 4.60423368
49 50 51 52 53 54
-20.94717360 -2.97463931 -13.24606788 1.85393212 -2.38892502 8.10604896
55 56 57 58 59 60
10.26319182 10.82033467 -5.25109390 11.99176325 2.62033467 4.37747753
61 62 63 64 65 66
4.22607025 7.99860454 9.72717597 12.42717597 0.78431883 3.61447493
67 68 69 70 71 72
6.47161779 -3.87123936 -5.54266793 -5.59981079 3.72876064 -11.01409650
73 74 75 76 77 78
-4.56550378 4.90703051 -11.16439806 -13.56439806 -3.50725520 -4.31228122
79 80 81 82 83 84
-6.95513836 -9.39799551 2.23057592 2.87343307 -7.19799551 12.85914735
85
50.00774007
> postscript(file="/var/www/html/rcomp/tmp/6dz4z1227793249.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 = 85
Frequency = 1
lag(myerror, k = 1) myerror
0 10.55985099 NA
1 20.53238529 10.55985099
2 18.16095672 20.53238529
3 14.36095672 18.16095672
4 6.51809957 14.36095672
5 1.31307356 6.51809957
6 3.67021641 1.31307356
7 7.42735927 3.67021641
8 4.35593070 7.42735927
9 15.29878784 4.35593070
10 0.82735927 15.29878784
11 0.08450213 0.82735927
12 -12.16690516 0.08450213
13 -15.59437086 -12.16690516
14 8.43420057 -15.59437086
15 -12.46579943 8.43420057
16 -14.30865658 -12.46579943
17 4.88631741 -14.30865658
18 -2.85653974 4.88631741
19 -4.39939688 -2.85653974
20 9.62917455 -4.39939688
21 -11.62796831 9.62917455
22 -13.09939688 -11.62796831
23 -7.34225402 -13.09939688
24 -20.59366131 -7.34225402
25 -13.42112701 -20.59366131
26 -5.99255558 -13.42112701
27 -6.09255558 -5.99255558
28 0.56458728 -6.09255558
29 0.75956126 0.56458728
30 1.91670412 0.75956126
31 1.47384697 1.91670412
32 6.10241840 1.47384697
33 -1.95472446 6.10241840
34 11.07384697 -1.95472446
35 -3.56901017 11.07384697
36 -6.52041746 -3.56901017
37 -1.44788316 -6.52041746
38 -5.91931173 -1.44788316
39 3.48068827 -5.91931173
40 12.33783113 3.48068827
41 -14.36719489 12.33783113
42 -12.51005203 -14.36719489
43 -2.05290918 -12.51005203
44 -11.52433775 -2.05290918
45 -10.98148061 -11.52433775
46 2.04709082 -10.98148061
47 4.60423368 2.04709082
48 -20.94717360 4.60423368
49 -2.97463931 -20.94717360
50 -13.24606788 -2.97463931
51 1.85393212 -13.24606788
52 -2.38892502 1.85393212
53 8.10604896 -2.38892502
54 10.26319182 8.10604896
55 10.82033467 10.26319182
56 -5.25109390 10.82033467
57 11.99176325 -5.25109390
58 2.62033467 11.99176325
59 4.37747753 2.62033467
60 4.22607025 4.37747753
61 7.99860454 4.22607025
62 9.72717597 7.99860454
63 12.42717597 9.72717597
64 0.78431883 12.42717597
65 3.61447493 0.78431883
66 6.47161779 3.61447493
67 -3.87123936 6.47161779
68 -5.54266793 -3.87123936
69 -5.59981079 -5.54266793
70 3.72876064 -5.59981079
71 -11.01409650 3.72876064
72 -4.56550378 -11.01409650
73 4.90703051 -4.56550378
74 -11.16439806 4.90703051
75 -13.56439806 -11.16439806
76 -3.50725520 -13.56439806
77 -4.31228122 -3.50725520
78 -6.95513836 -4.31228122
79 -9.39799551 -6.95513836
80 2.23057592 -9.39799551
81 2.87343307 2.23057592
82 -7.19799551 2.87343307
83 12.85914735 -7.19799551
84 50.00774007 12.85914735
85 NA 50.00774007
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 20.53238529 10.55985099
[2,] 18.16095672 20.53238529
[3,] 14.36095672 18.16095672
[4,] 6.51809957 14.36095672
[5,] 1.31307356 6.51809957
[6,] 3.67021641 1.31307356
[7,] 7.42735927 3.67021641
[8,] 4.35593070 7.42735927
[9,] 15.29878784 4.35593070
[10,] 0.82735927 15.29878784
[11,] 0.08450213 0.82735927
[12,] -12.16690516 0.08450213
[13,] -15.59437086 -12.16690516
[14,] 8.43420057 -15.59437086
[15,] -12.46579943 8.43420057
[16,] -14.30865658 -12.46579943
[17,] 4.88631741 -14.30865658
[18,] -2.85653974 4.88631741
[19,] -4.39939688 -2.85653974
[20,] 9.62917455 -4.39939688
[21,] -11.62796831 9.62917455
[22,] -13.09939688 -11.62796831
[23,] -7.34225402 -13.09939688
[24,] -20.59366131 -7.34225402
[25,] -13.42112701 -20.59366131
[26,] -5.99255558 -13.42112701
[27,] -6.09255558 -5.99255558
[28,] 0.56458728 -6.09255558
[29,] 0.75956126 0.56458728
[30,] 1.91670412 0.75956126
[31,] 1.47384697 1.91670412
[32,] 6.10241840 1.47384697
[33,] -1.95472446 6.10241840
[34,] 11.07384697 -1.95472446
[35,] -3.56901017 11.07384697
[36,] -6.52041746 -3.56901017
[37,] -1.44788316 -6.52041746
[38,] -5.91931173 -1.44788316
[39,] 3.48068827 -5.91931173
[40,] 12.33783113 3.48068827
[41,] -14.36719489 12.33783113
[42,] -12.51005203 -14.36719489
[43,] -2.05290918 -12.51005203
[44,] -11.52433775 -2.05290918
[45,] -10.98148061 -11.52433775
[46,] 2.04709082 -10.98148061
[47,] 4.60423368 2.04709082
[48,] -20.94717360 4.60423368
[49,] -2.97463931 -20.94717360
[50,] -13.24606788 -2.97463931
[51,] 1.85393212 -13.24606788
[52,] -2.38892502 1.85393212
[53,] 8.10604896 -2.38892502
[54,] 10.26319182 8.10604896
[55,] 10.82033467 10.26319182
[56,] -5.25109390 10.82033467
[57,] 11.99176325 -5.25109390
[58,] 2.62033467 11.99176325
[59,] 4.37747753 2.62033467
[60,] 4.22607025 4.37747753
[61,] 7.99860454 4.22607025
[62,] 9.72717597 7.99860454
[63,] 12.42717597 9.72717597
[64,] 0.78431883 12.42717597
[65,] 3.61447493 0.78431883
[66,] 6.47161779 3.61447493
[67,] -3.87123936 6.47161779
[68,] -5.54266793 -3.87123936
[69,] -5.59981079 -5.54266793
[70,] 3.72876064 -5.59981079
[71,] -11.01409650 3.72876064
[72,] -4.56550378 -11.01409650
[73,] 4.90703051 -4.56550378
[74,] -11.16439806 4.90703051
[75,] -13.56439806 -11.16439806
[76,] -3.50725520 -13.56439806
[77,] -4.31228122 -3.50725520
[78,] -6.95513836 -4.31228122
[79,] -9.39799551 -6.95513836
[80,] 2.23057592 -9.39799551
[81,] 2.87343307 2.23057592
[82,] -7.19799551 2.87343307
[83,] 12.85914735 -7.19799551
[84,] 50.00774007 12.85914735
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 20.53238529 10.55985099
2 18.16095672 20.53238529
3 14.36095672 18.16095672
4 6.51809957 14.36095672
5 1.31307356 6.51809957
6 3.67021641 1.31307356
7 7.42735927 3.67021641
8 4.35593070 7.42735927
9 15.29878784 4.35593070
10 0.82735927 15.29878784
11 0.08450213 0.82735927
12 -12.16690516 0.08450213
13 -15.59437086 -12.16690516
14 8.43420057 -15.59437086
15 -12.46579943 8.43420057
16 -14.30865658 -12.46579943
17 4.88631741 -14.30865658
18 -2.85653974 4.88631741
19 -4.39939688 -2.85653974
20 9.62917455 -4.39939688
21 -11.62796831 9.62917455
22 -13.09939688 -11.62796831
23 -7.34225402 -13.09939688
24 -20.59366131 -7.34225402
25 -13.42112701 -20.59366131
26 -5.99255558 -13.42112701
27 -6.09255558 -5.99255558
28 0.56458728 -6.09255558
29 0.75956126 0.56458728
30 1.91670412 0.75956126
31 1.47384697 1.91670412
32 6.10241840 1.47384697
33 -1.95472446 6.10241840
34 11.07384697 -1.95472446
35 -3.56901017 11.07384697
36 -6.52041746 -3.56901017
37 -1.44788316 -6.52041746
38 -5.91931173 -1.44788316
39 3.48068827 -5.91931173
40 12.33783113 3.48068827
41 -14.36719489 12.33783113
42 -12.51005203 -14.36719489
43 -2.05290918 -12.51005203
44 -11.52433775 -2.05290918
45 -10.98148061 -11.52433775
46 2.04709082 -10.98148061
47 4.60423368 2.04709082
48 -20.94717360 4.60423368
49 -2.97463931 -20.94717360
50 -13.24606788 -2.97463931
51 1.85393212 -13.24606788
52 -2.38892502 1.85393212
53 8.10604896 -2.38892502
54 10.26319182 8.10604896
55 10.82033467 10.26319182
56 -5.25109390 10.82033467
57 11.99176325 -5.25109390
58 2.62033467 11.99176325
59 4.37747753 2.62033467
60 4.22607025 4.37747753
61 7.99860454 4.22607025
62 9.72717597 7.99860454
63 12.42717597 9.72717597
64 0.78431883 12.42717597
65 3.61447493 0.78431883
66 6.47161779 3.61447493
67 -3.87123936 6.47161779
68 -5.54266793 -3.87123936
69 -5.59981079 -5.54266793
70 3.72876064 -5.59981079
71 -11.01409650 3.72876064
72 -4.56550378 -11.01409650
73 4.90703051 -4.56550378
74 -11.16439806 4.90703051
75 -13.56439806 -11.16439806
76 -3.50725520 -13.56439806
77 -4.31228122 -3.50725520
78 -6.95513836 -4.31228122
79 -9.39799551 -6.95513836
80 2.23057592 -9.39799551
81 2.87343307 2.23057592
82 -7.19799551 2.87343307
83 12.85914735 -7.19799551
84 50.00774007 12.85914735
> 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/79dfr1227793249.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/824ns1227793249.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9wtqv1227793249.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10h1771227793249.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/118bv91227793249.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/124er81227793250.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/133fbg1227793250.tab")
>
> system("convert tmp/1ofdn1227793249.ps tmp/1ofdn1227793249.png")
> system("convert tmp/20zqy1227793249.ps tmp/20zqy1227793249.png")
> system("convert tmp/30vh61227793249.ps tmp/30vh61227793249.png")
> system("convert tmp/4rszj1227793249.ps tmp/4rszj1227793249.png")
> system("convert tmp/51jbk1227793249.ps tmp/51jbk1227793249.png")
> system("convert tmp/6dz4z1227793249.ps tmp/6dz4z1227793249.png")
> system("convert tmp/79dfr1227793249.ps tmp/79dfr1227793249.png")
> system("convert tmp/824ns1227793249.ps tmp/824ns1227793249.png")
> system("convert tmp/9wtqv1227793249.ps tmp/9wtqv1227793249.png")
>
>
> proc.time()
user system elapsed
2.017 1.423 3.840