R version 2.7.0 (2008-04-22)
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(1.1608
+ ,0
+ ,1.1208
+ ,0
+ ,1.0883
+ ,0
+ ,1.0704
+ ,0
+ ,1.0628
+ ,0
+ ,1.0378
+ ,0
+ ,1.0353
+ ,0
+ ,1.0604
+ ,0
+ ,1.0501
+ ,0
+ ,1.0706
+ ,0
+ ,1.0338
+ ,0
+ ,1.011
+ ,0
+ ,1.0137
+ ,0
+ ,0.9834
+ ,0
+ ,0.9643
+ ,0
+ ,0.947
+ ,0
+ ,0.906
+ ,0
+ ,0.9492
+ ,0
+ ,0.9397
+ ,0
+ ,0.9041
+ ,0
+ ,0.8721
+ ,0
+ ,0.8552
+ ,0
+ ,0.8564
+ ,0
+ ,0.8973
+ ,0
+ ,0.9383
+ ,0
+ ,0.9217
+ ,0
+ ,0.9095
+ ,0
+ ,0.892
+ ,0
+ ,0.8742
+ ,0
+ ,0.8532
+ ,0
+ ,0.8607
+ ,0
+ ,0.9005
+ ,0
+ ,0.9111
+ ,0
+ ,0.9059
+ ,0
+ ,0.8883
+ ,0
+ ,0.8924
+ ,0
+ ,0.8833
+ ,0
+ ,0.87
+ ,0
+ ,0.8758
+ ,0
+ ,0.8858
+ ,0
+ ,0.917
+ ,0
+ ,0.9554
+ ,0
+ ,0.9922
+ ,0
+ ,0.9778
+ ,0
+ ,0.9808
+ ,0
+ ,0.9811
+ ,0
+ ,1.0014
+ ,0
+ ,1.0183
+ ,0
+ ,1.0622
+ ,0
+ ,1.0773
+ ,0
+ ,1.0807
+ ,0
+ ,1.0848
+ ,0
+ ,1.1582
+ ,0
+ ,1.1663
+ ,0
+ ,1.1372
+ ,0
+ ,1.1139
+ ,0
+ ,1.1222
+ ,0
+ ,1.1692
+ ,0
+ ,1.1702
+ ,0
+ ,1.2286
+ ,0
+ ,1.2613
+ ,0
+ ,1.2646
+ ,0
+ ,1.2262
+ ,0
+ ,1.1985
+ ,0
+ ,1.2007
+ ,0
+ ,1.2138
+ ,0
+ ,1.2266
+ ,0
+ ,1.2176
+ ,0
+ ,1.2218
+ ,0
+ ,1.249
+ ,0
+ ,1.2991
+ ,0
+ ,1.3408
+ ,0
+ ,1.3119
+ ,0
+ ,1.3014
+ ,0
+ ,1.3201
+ ,0
+ ,1.2938
+ ,0
+ ,1.2694
+ ,0
+ ,1.2165
+ ,0
+ ,1.2037
+ ,0
+ ,1.2292
+ ,0
+ ,1.2256
+ ,0
+ ,1.2015
+ ,0
+ ,1.1786
+ ,0
+ ,1.1856
+ ,0
+ ,1.2103
+ ,0
+ ,1.1938
+ ,0
+ ,1.202
+ ,0
+ ,1.2271
+ ,0
+ ,1.277
+ ,0
+ ,1.265
+ ,0
+ ,1.2684
+ ,0
+ ,1.2811
+ ,0
+ ,1.2727
+ ,0
+ ,1.2611
+ ,0
+ ,1.2881
+ ,0
+ ,1.3213
+ ,0
+ ,1.2999
+ ,0
+ ,1.3074
+ ,0
+ ,1.3242
+ ,0
+ ,1.3516
+ ,0
+ ,1.3511
+ ,0
+ ,1.3419
+ ,1
+ ,1.3716
+ ,1
+ ,1.3622
+ ,1
+ ,1.3896
+ ,1
+ ,1.4227
+ ,1
+ ,1.4684
+ ,1
+ ,1.457
+ ,1
+ ,1.4718
+ ,1
+ ,1.4748
+ ,1
+ ,1.5527
+ ,1
+ ,1.5751
+ ,1
+ ,1.5557
+ ,1
+ ,1.5553
+ ,1
+ ,1.577
+ ,1)
+ ,dim=c(2
+ ,115)
+ ,dimnames=list(c('y'
+ ,'x')
+ ,1:115))
> y <- array(NA,dim=c(2,115),dimnames=list(c('y','x'),1:115))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par20 = ''
> par19 = ''
> par18 = ''
> par17 = ''
> par16 = ''
> par15 = ''
> par14 = ''
> par13 = ''
> par12 = ''
> par11 = ''
> par10 = ''
> par9 = ''
> par8 = ''
> par7 = ''
> par6 = ''
> par5 = ''
> par4 = ''
> par3 = 'No Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> ylab = ''
> xlab = ''
> main = ''
> #'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
y x M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 1.1608 0 1 0 0 0 0 0 0 0 0 0 0
2 1.1208 0 0 1 0 0 0 0 0 0 0 0 0
3 1.0883 0 0 0 1 0 0 0 0 0 0 0 0
4 1.0704 0 0 0 0 1 0 0 0 0 0 0 0
5 1.0628 0 0 0 0 0 1 0 0 0 0 0 0
6 1.0378 0 0 0 0 0 0 1 0 0 0 0 0
7 1.0353 0 0 0 0 0 0 0 1 0 0 0 0
8 1.0604 0 0 0 0 0 0 0 0 1 0 0 0
9 1.0501 0 0 0 0 0 0 0 0 0 1 0 0
10 1.0706 0 0 0 0 0 0 0 0 0 0 1 0
11 1.0338 0 0 0 0 0 0 0 0 0 0 0 1
12 1.0110 0 0 0 0 0 0 0 0 0 0 0 0
13 1.0137 0 1 0 0 0 0 0 0 0 0 0 0
14 0.9834 0 0 1 0 0 0 0 0 0 0 0 0
15 0.9643 0 0 0 1 0 0 0 0 0 0 0 0
16 0.9470 0 0 0 0 1 0 0 0 0 0 0 0
17 0.9060 0 0 0 0 0 1 0 0 0 0 0 0
18 0.9492 0 0 0 0 0 0 1 0 0 0 0 0
19 0.9397 0 0 0 0 0 0 0 1 0 0 0 0
20 0.9041 0 0 0 0 0 0 0 0 1 0 0 0
21 0.8721 0 0 0 0 0 0 0 0 0 1 0 0
22 0.8552 0 0 0 0 0 0 0 0 0 0 1 0
23 0.8564 0 0 0 0 0 0 0 0 0 0 0 1
24 0.8973 0 0 0 0 0 0 0 0 0 0 0 0
25 0.9383 0 1 0 0 0 0 0 0 0 0 0 0
26 0.9217 0 0 1 0 0 0 0 0 0 0 0 0
27 0.9095 0 0 0 1 0 0 0 0 0 0 0 0
28 0.8920 0 0 0 0 1 0 0 0 0 0 0 0
29 0.8742 0 0 0 0 0 1 0 0 0 0 0 0
30 0.8532 0 0 0 0 0 0 1 0 0 0 0 0
31 0.8607 0 0 0 0 0 0 0 1 0 0 0 0
32 0.9005 0 0 0 0 0 0 0 0 1 0 0 0
33 0.9111 0 0 0 0 0 0 0 0 0 1 0 0
34 0.9059 0 0 0 0 0 0 0 0 0 0 1 0
35 0.8883 0 0 0 0 0 0 0 0 0 0 0 1
36 0.8924 0 0 0 0 0 0 0 0 0 0 0 0
37 0.8833 0 1 0 0 0 0 0 0 0 0 0 0
38 0.8700 0 0 1 0 0 0 0 0 0 0 0 0
39 0.8758 0 0 0 1 0 0 0 0 0 0 0 0
40 0.8858 0 0 0 0 1 0 0 0 0 0 0 0
41 0.9170 0 0 0 0 0 1 0 0 0 0 0 0
42 0.9554 0 0 0 0 0 0 1 0 0 0 0 0
43 0.9922 0 0 0 0 0 0 0 1 0 0 0 0
44 0.9778 0 0 0 0 0 0 0 0 1 0 0 0
45 0.9808 0 0 0 0 0 0 0 0 0 1 0 0
46 0.9811 0 0 0 0 0 0 0 0 0 0 1 0
47 1.0014 0 0 0 0 0 0 0 0 0 0 0 1
48 1.0183 0 0 0 0 0 0 0 0 0 0 0 0
49 1.0622 0 1 0 0 0 0 0 0 0 0 0 0
50 1.0773 0 0 1 0 0 0 0 0 0 0 0 0
51 1.0807 0 0 0 1 0 0 0 0 0 0 0 0
52 1.0848 0 0 0 0 1 0 0 0 0 0 0 0
53 1.1582 0 0 0 0 0 1 0 0 0 0 0 0
54 1.1663 0 0 0 0 0 0 1 0 0 0 0 0
55 1.1372 0 0 0 0 0 0 0 1 0 0 0 0
56 1.1139 0 0 0 0 0 0 0 0 1 0 0 0
57 1.1222 0 0 0 0 0 0 0 0 0 1 0 0
58 1.1692 0 0 0 0 0 0 0 0 0 0 1 0
59 1.1702 0 0 0 0 0 0 0 0 0 0 0 1
60 1.2286 0 0 0 0 0 0 0 0 0 0 0 0
61 1.2613 0 1 0 0 0 0 0 0 0 0 0 0
62 1.2646 0 0 1 0 0 0 0 0 0 0 0 0
63 1.2262 0 0 0 1 0 0 0 0 0 0 0 0
64 1.1985 0 0 0 0 1 0 0 0 0 0 0 0
65 1.2007 0 0 0 0 0 1 0 0 0 0 0 0
66 1.2138 0 0 0 0 0 0 1 0 0 0 0 0
67 1.2266 0 0 0 0 0 0 0 1 0 0 0 0
68 1.2176 0 0 0 0 0 0 0 0 1 0 0 0
69 1.2218 0 0 0 0 0 0 0 0 0 1 0 0
70 1.2490 0 0 0 0 0 0 0 0 0 0 1 0
71 1.2991 0 0 0 0 0 0 0 0 0 0 0 1
72 1.3408 0 0 0 0 0 0 0 0 0 0 0 0
73 1.3119 0 1 0 0 0 0 0 0 0 0 0 0
74 1.3014 0 0 1 0 0 0 0 0 0 0 0 0
75 1.3201 0 0 0 1 0 0 0 0 0 0 0 0
76 1.2938 0 0 0 0 1 0 0 0 0 0 0 0
77 1.2694 0 0 0 0 0 1 0 0 0 0 0 0
78 1.2165 0 0 0 0 0 0 1 0 0 0 0 0
79 1.2037 0 0 0 0 0 0 0 1 0 0 0 0
80 1.2292 0 0 0 0 0 0 0 0 1 0 0 0
81 1.2256 0 0 0 0 0 0 0 0 0 1 0 0
82 1.2015 0 0 0 0 0 0 0 0 0 0 1 0
83 1.1786 0 0 0 0 0 0 0 0 0 0 0 1
84 1.1856 0 0 0 0 0 0 0 0 0 0 0 0
85 1.2103 0 1 0 0 0 0 0 0 0 0 0 0
86 1.1938 0 0 1 0 0 0 0 0 0 0 0 0
87 1.2020 0 0 0 1 0 0 0 0 0 0 0 0
88 1.2271 0 0 0 0 1 0 0 0 0 0 0 0
89 1.2770 0 0 0 0 0 1 0 0 0 0 0 0
90 1.2650 0 0 0 0 0 0 1 0 0 0 0 0
91 1.2684 0 0 0 0 0 0 0 1 0 0 0 0
92 1.2811 0 0 0 0 0 0 0 0 1 0 0 0
93 1.2727 0 0 0 0 0 0 0 0 0 1 0 0
94 1.2611 0 0 0 0 0 0 0 0 0 0 1 0
95 1.2881 0 0 0 0 0 0 0 0 0 0 0 1
96 1.3213 0 0 0 0 0 0 0 0 0 0 0 0
97 1.2999 0 1 0 0 0 0 0 0 0 0 0 0
98 1.3074 0 0 1 0 0 0 0 0 0 0 0 0
99 1.3242 0 0 0 1 0 0 0 0 0 0 0 0
100 1.3516 0 0 0 0 1 0 0 0 0 0 0 0
101 1.3511 0 0 0 0 0 1 0 0 0 0 0 0
102 1.3419 1 0 0 0 0 0 1 0 0 0 0 0
103 1.3716 1 0 0 0 0 0 0 1 0 0 0 0
104 1.3622 1 0 0 0 0 0 0 0 1 0 0 0
105 1.3896 1 0 0 0 0 0 0 0 0 1 0 0
106 1.4227 1 0 0 0 0 0 0 0 0 0 1 0
107 1.4684 1 0 0 0 0 0 0 0 0 0 0 1
108 1.4570 1 0 0 0 0 0 0 0 0 0 0 0
109 1.4718 1 1 0 0 0 0 0 0 0 0 0 0
110 1.4748 1 0 1 0 0 0 0 0 0 0 0 0
111 1.5527 1 0 0 1 0 0 0 0 0 0 0 0
112 1.5751 1 0 0 0 1 0 0 0 0 0 0 0
113 1.5557 1 0 0 0 0 1 0 0 0 0 0 0
114 1.5553 1 0 0 0 0 0 1 0 0 0 0 0
115 1.5770 1 0 0 0 0 0 0 1 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
1.108838 0.372760 0.015236 0.005406 0.008266 0.006496
M5 M6 M7 M8 M9 M10
0.011096 -0.027950 -0.022150 -0.033944 -0.034033 -0.026222
M11
-0.018667
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.24573 -0.11862 -0.01202 0.13426 0.23627
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.108838 0.052067 21.296 < 2e-16 ***
x 0.372760 0.044619 8.354 3.46e-13 ***
M1 0.015236 0.071445 0.213 0.832
M2 0.005406 0.071445 0.076 0.940
M3 0.008266 0.071445 0.116 0.908
M4 0.006496 0.071445 0.091 0.928
M5 0.011096 0.071445 0.155 0.877
M6 -0.027950 0.071553 -0.391 0.697
M7 -0.022150 0.071553 -0.310 0.758
M8 -0.033944 0.073299 -0.463 0.644
M9 -0.034033 0.073299 -0.464 0.643
M10 -0.026222 0.073299 -0.358 0.721
M11 -0.018667 0.073299 -0.255 0.799
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.1555 on 102 degrees of freedom
Multiple R-squared: 0.4106, Adjusted R-squared: 0.3413
F-statistic: 5.921 on 12 and 102 DF, p-value: 1.006e-07
> postscript(file="/var/www/html/rcomp/tmp/1h0m21227976381.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/2nigs1227976381.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3cjzm1227976381.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4z9g41227976381.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5zgc91227976381.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 115
Frequency = 1
1 2 3 4 5 6
0.036725965 0.006555965 -0.028804035 -0.044934035 -0.057134035 -0.043088070
7 8 9 10 11 12
-0.051388070 -0.014493372 -0.024704483 -0.012015594 -0.056371150 -0.097837816
13 14 15 16 17 18
-0.110374035 -0.130844035 -0.152804035 -0.168334035 -0.213934035 -0.131688070
19 20 21 22 23 24
-0.146988070 -0.170793372 -0.202704483 -0.227415594 -0.233771150 -0.211537816
25 26 27 28 29 30
-0.185774035 -0.192544035 -0.207604035 -0.223334035 -0.245734035 -0.227688070
31 32 33 34 35 36
-0.225988070 -0.174393372 -0.163704483 -0.176715594 -0.201871150 -0.216437816
37 38 39 40 41 42
-0.240774035 -0.244244035 -0.241304035 -0.229534035 -0.202934035 -0.125488070
43 44 45 46 47 48
-0.094488070 -0.097093372 -0.094004483 -0.101515594 -0.088771150 -0.090537816
49 50 51 52 53 54
-0.061874035 -0.036944035 -0.036404035 -0.030534035 0.038265965 0.085411930
55 56 57 58 59 60
0.050511930 0.039006628 0.047395517 0.086584406 0.080028850 0.119762184
61 62 63 64 65 66
0.137225965 0.150355965 0.109095965 0.083165965 0.080765965 0.132911930
67 68 69 70 71 72
0.139911930 0.142706628 0.146995517 0.166384406 0.208928850 0.231962184
73 74 75 76 77 78
0.187825965 0.187155965 0.202995965 0.178465965 0.149465965 0.135611930
79 80 81 82 83 84
0.117011930 0.154306628 0.150795517 0.118884406 0.088428850 0.076762184
85 86 87 88 89 90
0.086225965 0.079555965 0.084895965 0.111765965 0.157065965 0.184111930
91 92 93 94 95 96
0.181711930 0.206206628 0.197895517 0.178484406 0.197928850 0.212462184
97 98 99 100 101 102
0.175825965 0.193155965 0.207095965 0.236265965 0.231165965 -0.111747722
103 104 105 106 107 108
-0.087847722 -0.085453024 -0.057964135 -0.032675247 0.005469198 -0.024597469
109 110 111 112 113 114
-0.025033687 -0.012203687 0.062836313 0.087006313 0.063006313 0.101652278
115
0.117552278
> postscript(file="/var/www/html/rcomp/tmp/6ypon1227976381.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 = 115
Frequency = 1
lag(myerror, k = 1) myerror
0 0.036725965 NA
1 0.006555965 0.036725965
2 -0.028804035 0.006555965
3 -0.044934035 -0.028804035
4 -0.057134035 -0.044934035
5 -0.043088070 -0.057134035
6 -0.051388070 -0.043088070
7 -0.014493372 -0.051388070
8 -0.024704483 -0.014493372
9 -0.012015594 -0.024704483
10 -0.056371150 -0.012015594
11 -0.097837816 -0.056371150
12 -0.110374035 -0.097837816
13 -0.130844035 -0.110374035
14 -0.152804035 -0.130844035
15 -0.168334035 -0.152804035
16 -0.213934035 -0.168334035
17 -0.131688070 -0.213934035
18 -0.146988070 -0.131688070
19 -0.170793372 -0.146988070
20 -0.202704483 -0.170793372
21 -0.227415594 -0.202704483
22 -0.233771150 -0.227415594
23 -0.211537816 -0.233771150
24 -0.185774035 -0.211537816
25 -0.192544035 -0.185774035
26 -0.207604035 -0.192544035
27 -0.223334035 -0.207604035
28 -0.245734035 -0.223334035
29 -0.227688070 -0.245734035
30 -0.225988070 -0.227688070
31 -0.174393372 -0.225988070
32 -0.163704483 -0.174393372
33 -0.176715594 -0.163704483
34 -0.201871150 -0.176715594
35 -0.216437816 -0.201871150
36 -0.240774035 -0.216437816
37 -0.244244035 -0.240774035
38 -0.241304035 -0.244244035
39 -0.229534035 -0.241304035
40 -0.202934035 -0.229534035
41 -0.125488070 -0.202934035
42 -0.094488070 -0.125488070
43 -0.097093372 -0.094488070
44 -0.094004483 -0.097093372
45 -0.101515594 -0.094004483
46 -0.088771150 -0.101515594
47 -0.090537816 -0.088771150
48 -0.061874035 -0.090537816
49 -0.036944035 -0.061874035
50 -0.036404035 -0.036944035
51 -0.030534035 -0.036404035
52 0.038265965 -0.030534035
53 0.085411930 0.038265965
54 0.050511930 0.085411930
55 0.039006628 0.050511930
56 0.047395517 0.039006628
57 0.086584406 0.047395517
58 0.080028850 0.086584406
59 0.119762184 0.080028850
60 0.137225965 0.119762184
61 0.150355965 0.137225965
62 0.109095965 0.150355965
63 0.083165965 0.109095965
64 0.080765965 0.083165965
65 0.132911930 0.080765965
66 0.139911930 0.132911930
67 0.142706628 0.139911930
68 0.146995517 0.142706628
69 0.166384406 0.146995517
70 0.208928850 0.166384406
71 0.231962184 0.208928850
72 0.187825965 0.231962184
73 0.187155965 0.187825965
74 0.202995965 0.187155965
75 0.178465965 0.202995965
76 0.149465965 0.178465965
77 0.135611930 0.149465965
78 0.117011930 0.135611930
79 0.154306628 0.117011930
80 0.150795517 0.154306628
81 0.118884406 0.150795517
82 0.088428850 0.118884406
83 0.076762184 0.088428850
84 0.086225965 0.076762184
85 0.079555965 0.086225965
86 0.084895965 0.079555965
87 0.111765965 0.084895965
88 0.157065965 0.111765965
89 0.184111930 0.157065965
90 0.181711930 0.184111930
91 0.206206628 0.181711930
92 0.197895517 0.206206628
93 0.178484406 0.197895517
94 0.197928850 0.178484406
95 0.212462184 0.197928850
96 0.175825965 0.212462184
97 0.193155965 0.175825965
98 0.207095965 0.193155965
99 0.236265965 0.207095965
100 0.231165965 0.236265965
101 -0.111747722 0.231165965
102 -0.087847722 -0.111747722
103 -0.085453024 -0.087847722
104 -0.057964135 -0.085453024
105 -0.032675247 -0.057964135
106 0.005469198 -0.032675247
107 -0.024597469 0.005469198
108 -0.025033687 -0.024597469
109 -0.012203687 -0.025033687
110 0.062836313 -0.012203687
111 0.087006313 0.062836313
112 0.063006313 0.087006313
113 0.101652278 0.063006313
114 0.117552278 0.101652278
115 NA 0.117552278
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.006555965 0.036725965
[2,] -0.028804035 0.006555965
[3,] -0.044934035 -0.028804035
[4,] -0.057134035 -0.044934035
[5,] -0.043088070 -0.057134035
[6,] -0.051388070 -0.043088070
[7,] -0.014493372 -0.051388070
[8,] -0.024704483 -0.014493372
[9,] -0.012015594 -0.024704483
[10,] -0.056371150 -0.012015594
[11,] -0.097837816 -0.056371150
[12,] -0.110374035 -0.097837816
[13,] -0.130844035 -0.110374035
[14,] -0.152804035 -0.130844035
[15,] -0.168334035 -0.152804035
[16,] -0.213934035 -0.168334035
[17,] -0.131688070 -0.213934035
[18,] -0.146988070 -0.131688070
[19,] -0.170793372 -0.146988070
[20,] -0.202704483 -0.170793372
[21,] -0.227415594 -0.202704483
[22,] -0.233771150 -0.227415594
[23,] -0.211537816 -0.233771150
[24,] -0.185774035 -0.211537816
[25,] -0.192544035 -0.185774035
[26,] -0.207604035 -0.192544035
[27,] -0.223334035 -0.207604035
[28,] -0.245734035 -0.223334035
[29,] -0.227688070 -0.245734035
[30,] -0.225988070 -0.227688070
[31,] -0.174393372 -0.225988070
[32,] -0.163704483 -0.174393372
[33,] -0.176715594 -0.163704483
[34,] -0.201871150 -0.176715594
[35,] -0.216437816 -0.201871150
[36,] -0.240774035 -0.216437816
[37,] -0.244244035 -0.240774035
[38,] -0.241304035 -0.244244035
[39,] -0.229534035 -0.241304035
[40,] -0.202934035 -0.229534035
[41,] -0.125488070 -0.202934035
[42,] -0.094488070 -0.125488070
[43,] -0.097093372 -0.094488070
[44,] -0.094004483 -0.097093372
[45,] -0.101515594 -0.094004483
[46,] -0.088771150 -0.101515594
[47,] -0.090537816 -0.088771150
[48,] -0.061874035 -0.090537816
[49,] -0.036944035 -0.061874035
[50,] -0.036404035 -0.036944035
[51,] -0.030534035 -0.036404035
[52,] 0.038265965 -0.030534035
[53,] 0.085411930 0.038265965
[54,] 0.050511930 0.085411930
[55,] 0.039006628 0.050511930
[56,] 0.047395517 0.039006628
[57,] 0.086584406 0.047395517
[58,] 0.080028850 0.086584406
[59,] 0.119762184 0.080028850
[60,] 0.137225965 0.119762184
[61,] 0.150355965 0.137225965
[62,] 0.109095965 0.150355965
[63,] 0.083165965 0.109095965
[64,] 0.080765965 0.083165965
[65,] 0.132911930 0.080765965
[66,] 0.139911930 0.132911930
[67,] 0.142706628 0.139911930
[68,] 0.146995517 0.142706628
[69,] 0.166384406 0.146995517
[70,] 0.208928850 0.166384406
[71,] 0.231962184 0.208928850
[72,] 0.187825965 0.231962184
[73,] 0.187155965 0.187825965
[74,] 0.202995965 0.187155965
[75,] 0.178465965 0.202995965
[76,] 0.149465965 0.178465965
[77,] 0.135611930 0.149465965
[78,] 0.117011930 0.135611930
[79,] 0.154306628 0.117011930
[80,] 0.150795517 0.154306628
[81,] 0.118884406 0.150795517
[82,] 0.088428850 0.118884406
[83,] 0.076762184 0.088428850
[84,] 0.086225965 0.076762184
[85,] 0.079555965 0.086225965
[86,] 0.084895965 0.079555965
[87,] 0.111765965 0.084895965
[88,] 0.157065965 0.111765965
[89,] 0.184111930 0.157065965
[90,] 0.181711930 0.184111930
[91,] 0.206206628 0.181711930
[92,] 0.197895517 0.206206628
[93,] 0.178484406 0.197895517
[94,] 0.197928850 0.178484406
[95,] 0.212462184 0.197928850
[96,] 0.175825965 0.212462184
[97,] 0.193155965 0.175825965
[98,] 0.207095965 0.193155965
[99,] 0.236265965 0.207095965
[100,] 0.231165965 0.236265965
[101,] -0.111747722 0.231165965
[102,] -0.087847722 -0.111747722
[103,] -0.085453024 -0.087847722
[104,] -0.057964135 -0.085453024
[105,] -0.032675247 -0.057964135
[106,] 0.005469198 -0.032675247
[107,] -0.024597469 0.005469198
[108,] -0.025033687 -0.024597469
[109,] -0.012203687 -0.025033687
[110,] 0.062836313 -0.012203687
[111,] 0.087006313 0.062836313
[112,] 0.063006313 0.087006313
[113,] 0.101652278 0.063006313
[114,] 0.117552278 0.101652278
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.006555965 0.036725965
2 -0.028804035 0.006555965
3 -0.044934035 -0.028804035
4 -0.057134035 -0.044934035
5 -0.043088070 -0.057134035
6 -0.051388070 -0.043088070
7 -0.014493372 -0.051388070
8 -0.024704483 -0.014493372
9 -0.012015594 -0.024704483
10 -0.056371150 -0.012015594
11 -0.097837816 -0.056371150
12 -0.110374035 -0.097837816
13 -0.130844035 -0.110374035
14 -0.152804035 -0.130844035
15 -0.168334035 -0.152804035
16 -0.213934035 -0.168334035
17 -0.131688070 -0.213934035
18 -0.146988070 -0.131688070
19 -0.170793372 -0.146988070
20 -0.202704483 -0.170793372
21 -0.227415594 -0.202704483
22 -0.233771150 -0.227415594
23 -0.211537816 -0.233771150
24 -0.185774035 -0.211537816
25 -0.192544035 -0.185774035
26 -0.207604035 -0.192544035
27 -0.223334035 -0.207604035
28 -0.245734035 -0.223334035
29 -0.227688070 -0.245734035
30 -0.225988070 -0.227688070
31 -0.174393372 -0.225988070
32 -0.163704483 -0.174393372
33 -0.176715594 -0.163704483
34 -0.201871150 -0.176715594
35 -0.216437816 -0.201871150
36 -0.240774035 -0.216437816
37 -0.244244035 -0.240774035
38 -0.241304035 -0.244244035
39 -0.229534035 -0.241304035
40 -0.202934035 -0.229534035
41 -0.125488070 -0.202934035
42 -0.094488070 -0.125488070
43 -0.097093372 -0.094488070
44 -0.094004483 -0.097093372
45 -0.101515594 -0.094004483
46 -0.088771150 -0.101515594
47 -0.090537816 -0.088771150
48 -0.061874035 -0.090537816
49 -0.036944035 -0.061874035
50 -0.036404035 -0.036944035
51 -0.030534035 -0.036404035
52 0.038265965 -0.030534035
53 0.085411930 0.038265965
54 0.050511930 0.085411930
55 0.039006628 0.050511930
56 0.047395517 0.039006628
57 0.086584406 0.047395517
58 0.080028850 0.086584406
59 0.119762184 0.080028850
60 0.137225965 0.119762184
61 0.150355965 0.137225965
62 0.109095965 0.150355965
63 0.083165965 0.109095965
64 0.080765965 0.083165965
65 0.132911930 0.080765965
66 0.139911930 0.132911930
67 0.142706628 0.139911930
68 0.146995517 0.142706628
69 0.166384406 0.146995517
70 0.208928850 0.166384406
71 0.231962184 0.208928850
72 0.187825965 0.231962184
73 0.187155965 0.187825965
74 0.202995965 0.187155965
75 0.178465965 0.202995965
76 0.149465965 0.178465965
77 0.135611930 0.149465965
78 0.117011930 0.135611930
79 0.154306628 0.117011930
80 0.150795517 0.154306628
81 0.118884406 0.150795517
82 0.088428850 0.118884406
83 0.076762184 0.088428850
84 0.086225965 0.076762184
85 0.079555965 0.086225965
86 0.084895965 0.079555965
87 0.111765965 0.084895965
88 0.157065965 0.111765965
89 0.184111930 0.157065965
90 0.181711930 0.184111930
91 0.206206628 0.181711930
92 0.197895517 0.206206628
93 0.178484406 0.197895517
94 0.197928850 0.178484406
95 0.212462184 0.197928850
96 0.175825965 0.212462184
97 0.193155965 0.175825965
98 0.207095965 0.193155965
99 0.236265965 0.207095965
100 0.231165965 0.236265965
101 -0.111747722 0.231165965
102 -0.087847722 -0.111747722
103 -0.085453024 -0.087847722
104 -0.057964135 -0.085453024
105 -0.032675247 -0.057964135
106 0.005469198 -0.032675247
107 -0.024597469 0.005469198
108 -0.025033687 -0.024597469
109 -0.012203687 -0.025033687
110 0.062836313 -0.012203687
111 0.087006313 0.062836313
112 0.063006313 0.087006313
113 0.101652278 0.063006313
114 0.117552278 0.101652278
> 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/733391227976381.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/806wq1227976381.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/92ta91227976381.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/10ljrd1227976381.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/11yzz01227976381.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/12t14r1227976382.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/13rmul1227976382.tab")
>
> system("convert tmp/1h0m21227976381.ps tmp/1h0m21227976381.png")
> system("convert tmp/2nigs1227976381.ps tmp/2nigs1227976381.png")
> system("convert tmp/3cjzm1227976381.ps tmp/3cjzm1227976381.png")
> system("convert tmp/4z9g41227976381.ps tmp/4z9g41227976381.png")
> system("convert tmp/5zgc91227976381.ps tmp/5zgc91227976381.png")
> system("convert tmp/6ypon1227976381.ps tmp/6ypon1227976381.png")
> system("convert tmp/733391227976381.ps tmp/733391227976381.png")
> system("convert tmp/806wq1227976381.ps tmp/806wq1227976381.png")
> system("convert tmp/92ta91227976381.ps tmp/92ta91227976381.png")
>
>
> proc.time()
user system elapsed
4.336 2.568 4.666