R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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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
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(7.9
+ ,9.1
+ ,7.6
+ ,7.5
+ ,7.6
+ ,7.3
+ ,7.9
+ ,9
+ ,7.9
+ ,7.6
+ ,7.5
+ ,7.6
+ ,8.1
+ ,9.3
+ ,7.9
+ ,7.9
+ ,7.6
+ ,7.5
+ ,8.2
+ ,9.9
+ ,8.1
+ ,7.9
+ ,7.9
+ ,7.6
+ ,8
+ ,9.8
+ ,8.2
+ ,8.1
+ ,7.9
+ ,7.9
+ ,7.5
+ ,9.3
+ ,8
+ ,8.2
+ ,8.1
+ ,7.9
+ ,6.8
+ ,8.3
+ ,7.5
+ ,8
+ ,8.2
+ ,8.1
+ ,6.5
+ ,8
+ ,6.8
+ ,7.5
+ ,8
+ ,8.2
+ ,6.6
+ ,8.5
+ ,6.5
+ ,6.8
+ ,7.5
+ ,8
+ ,7.6
+ ,10.4
+ ,6.6
+ ,6.5
+ ,6.8
+ ,7.5
+ ,8
+ ,11.1
+ ,7.6
+ ,6.6
+ ,6.5
+ ,6.8
+ ,8.1
+ ,10.9
+ ,8
+ ,7.6
+ ,6.6
+ ,6.5
+ ,7.7
+ ,10
+ ,8.1
+ ,8
+ ,7.6
+ ,6.6
+ ,7.5
+ ,9.2
+ ,7.7
+ ,8.1
+ ,8
+ ,7.6
+ ,7.6
+ ,9.2
+ ,7.5
+ ,7.7
+ ,8.1
+ ,8
+ ,7.8
+ ,9.5
+ ,7.6
+ ,7.5
+ ,7.7
+ ,8.1
+ ,7.8
+ ,9.6
+ ,7.8
+ ,7.6
+ ,7.5
+ ,7.7
+ ,7.8
+ ,9.5
+ ,7.8
+ ,7.8
+ ,7.6
+ ,7.5
+ ,7.5
+ ,9.1
+ ,7.8
+ ,7.8
+ ,7.8
+ ,7.6
+ ,7.5
+ ,8.9
+ ,7.5
+ ,7.8
+ ,7.8
+ ,7.8
+ ,7.1
+ ,9
+ ,7.5
+ ,7.5
+ ,7.8
+ ,7.8
+ ,7.5
+ ,10.1
+ ,7.1
+ ,7.5
+ ,7.5
+ ,7.8
+ ,7.5
+ ,10.3
+ ,7.5
+ ,7.1
+ ,7.5
+ ,7.5
+ ,7.6
+ ,10.2
+ ,7.5
+ ,7.5
+ ,7.1
+ ,7.5
+ ,7.7
+ ,9.6
+ ,7.6
+ ,7.5
+ ,7.5
+ ,7.1
+ ,7.7
+ ,9.2
+ ,7.7
+ ,7.6
+ ,7.5
+ ,7.5
+ ,7.9
+ ,9.3
+ ,7.7
+ ,7.7
+ ,7.6
+ ,7.5
+ ,8.1
+ ,9.4
+ ,7.9
+ ,7.7
+ ,7.7
+ ,7.6
+ ,8.2
+ ,9.4
+ ,8.1
+ ,7.9
+ ,7.7
+ ,7.7
+ ,8.2
+ ,9.2
+ ,8.2
+ ,8.1
+ ,7.9
+ ,7.7
+ ,8.2
+ ,9
+ ,8.2
+ ,8.2
+ ,8.1
+ ,7.9
+ ,7.9
+ ,9
+ ,8.2
+ ,8.2
+ ,8.2
+ ,8.1
+ ,7.3
+ ,9
+ ,7.9
+ ,8.2
+ ,8.2
+ ,8.2
+ ,6.9
+ ,9.8
+ ,7.3
+ ,7.9
+ ,8.2
+ ,8.2
+ ,6.6
+ ,10
+ ,6.9
+ ,7.3
+ ,7.9
+ ,8.2
+ ,6.7
+ ,9.8
+ ,6.6
+ ,6.9
+ ,7.3
+ ,7.9
+ ,6.9
+ ,9.3
+ ,6.7
+ ,6.6
+ ,6.9
+ ,7.3
+ ,7
+ ,9
+ ,6.9
+ ,6.7
+ ,6.6
+ ,6.9
+ ,7.1
+ ,9
+ ,7
+ ,6.9
+ ,6.7
+ ,6.6
+ ,7.2
+ ,9.1
+ ,7.1
+ ,7
+ ,6.9
+ ,6.7
+ ,7.1
+ ,9.1
+ ,7.2
+ ,7.1
+ ,7
+ ,6.9
+ ,6.9
+ ,9.1
+ ,7.1
+ ,7.2
+ ,7.1
+ ,7
+ ,7
+ ,9.2
+ ,6.9
+ ,7.1
+ ,7.2
+ ,7.1
+ ,6.8
+ ,8.8
+ ,7
+ ,6.9
+ ,7.1
+ ,7.2
+ ,6.4
+ ,8.3
+ ,6.8
+ ,7
+ ,6.9
+ ,7.1
+ ,6.7
+ ,8.4
+ ,6.4
+ ,6.8
+ ,7
+ ,6.9
+ ,6.6
+ ,8.1
+ ,6.7
+ ,6.4
+ ,6.8
+ ,7
+ ,6.4
+ ,7.7
+ ,6.6
+ ,6.7
+ ,6.4
+ ,6.8
+ ,6.3
+ ,7.9
+ ,6.4
+ ,6.6
+ ,6.7
+ ,6.4
+ ,6.2
+ ,7.9
+ ,6.3
+ ,6.4
+ ,6.6
+ ,6.7
+ ,6.5
+ ,8
+ ,6.2
+ ,6.3
+ ,6.4
+ ,6.6
+ ,6.8
+ ,7.9
+ ,6.5
+ ,6.2
+ ,6.3
+ ,6.4
+ ,6.8
+ ,7.6
+ ,6.8
+ ,6.5
+ ,6.2
+ ,6.3
+ ,6.4
+ ,7.1
+ ,6.8
+ ,6.8
+ ,6.5
+ ,6.2
+ ,6.1
+ ,6.8
+ ,6.4
+ ,6.8
+ ,6.8
+ ,6.5
+ ,5.8
+ ,6.5
+ ,6.1
+ ,6.4
+ ,6.8
+ ,6.8
+ ,6.1
+ ,6.9
+ ,5.8
+ ,6.1
+ ,6.4
+ ,6.8
+ ,7.2
+ ,8.2
+ ,6.1
+ ,5.8
+ ,6.1
+ ,6.4
+ ,7.3
+ ,8.7
+ ,7.2
+ ,6.1
+ ,5.8
+ ,6.1
+ ,6.9
+ ,8.3
+ ,7.3
+ ,7.2
+ ,6.1
+ ,5.8
+ ,6.1
+ ,7.9
+ ,6.9
+ ,7.3
+ ,7.2
+ ,6.1
+ ,5.8
+ ,7.5
+ ,6.1
+ ,6.9
+ ,7.3
+ ,7.2
+ ,6.2
+ ,7.8
+ ,5.8
+ ,6.1
+ ,6.9
+ ,7.3
+ ,7.1
+ ,8.3
+ ,6.2
+ ,5.8
+ ,6.1
+ ,6.9
+ ,7.7
+ ,8.4
+ ,7.1
+ ,6.2
+ ,5.8
+ ,6.1
+ ,7.9
+ ,8.2
+ ,7.7
+ ,7.1
+ ,6.2
+ ,5.8
+ ,7.7
+ ,7.7
+ ,7.9
+ ,7.7
+ ,7.1
+ ,6.2
+ ,7.4
+ ,7.2
+ ,7.7
+ ,7.9
+ ,7.7
+ ,7.1
+ ,7.5
+ ,7.3
+ ,7.4
+ ,7.7
+ ,7.9
+ ,7.7)
+ ,dim=c(6
+ ,69)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:69))
> y <- array(NA,dim=c(6,69),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:69))
> 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
Y X Y1 Y2 Y3 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 7.9 9.1 7.6 7.5 7.6 7.3 1 0 0 0 0 0 0 0 0 0 0 1
2 7.9 9.0 7.9 7.6 7.5 7.6 0 1 0 0 0 0 0 0 0 0 0 2
3 8.1 9.3 7.9 7.9 7.6 7.5 0 0 1 0 0 0 0 0 0 0 0 3
4 8.2 9.9 8.1 7.9 7.9 7.6 0 0 0 1 0 0 0 0 0 0 0 4
5 8.0 9.8 8.2 8.1 7.9 7.9 0 0 0 0 1 0 0 0 0 0 0 5
6 7.5 9.3 8.0 8.2 8.1 7.9 0 0 0 0 0 1 0 0 0 0 0 6
7 6.8 8.3 7.5 8.0 8.2 8.1 0 0 0 0 0 0 1 0 0 0 0 7
8 6.5 8.0 6.8 7.5 8.0 8.2 0 0 0 0 0 0 0 1 0 0 0 8
9 6.6 8.5 6.5 6.8 7.5 8.0 0 0 0 0 0 0 0 0 1 0 0 9
10 7.6 10.4 6.6 6.5 6.8 7.5 0 0 0 0 0 0 0 0 0 1 0 10
11 8.0 11.1 7.6 6.6 6.5 6.8 0 0 0 0 0 0 0 0 0 0 1 11
12 8.1 10.9 8.0 7.6 6.6 6.5 0 0 0 0 0 0 0 0 0 0 0 12
13 7.7 10.0 8.1 8.0 7.6 6.6 1 0 0 0 0 0 0 0 0 0 0 13
14 7.5 9.2 7.7 8.1 8.0 7.6 0 1 0 0 0 0 0 0 0 0 0 14
15 7.6 9.2 7.5 7.7 8.1 8.0 0 0 1 0 0 0 0 0 0 0 0 15
16 7.8 9.5 7.6 7.5 7.7 8.1 0 0 0 1 0 0 0 0 0 0 0 16
17 7.8 9.6 7.8 7.6 7.5 7.7 0 0 0 0 1 0 0 0 0 0 0 17
18 7.8 9.5 7.8 7.8 7.6 7.5 0 0 0 0 0 1 0 0 0 0 0 18
19 7.5 9.1 7.8 7.8 7.8 7.6 0 0 0 0 0 0 1 0 0 0 0 19
20 7.5 8.9 7.5 7.8 7.8 7.8 0 0 0 0 0 0 0 1 0 0 0 20
21 7.1 9.0 7.5 7.5 7.8 7.8 0 0 0 0 0 0 0 0 1 0 0 21
22 7.5 10.1 7.1 7.5 7.5 7.8 0 0 0 0 0 0 0 0 0 1 0 22
23 7.5 10.3 7.5 7.1 7.5 7.5 0 0 0 0 0 0 0 0 0 0 1 23
24 7.6 10.2 7.5 7.5 7.1 7.5 0 0 0 0 0 0 0 0 0 0 0 24
25 7.7 9.6 7.6 7.5 7.5 7.1 1 0 0 0 0 0 0 0 0 0 0 25
26 7.7 9.2 7.7 7.6 7.5 7.5 0 1 0 0 0 0 0 0 0 0 0 26
27 7.9 9.3 7.7 7.7 7.6 7.5 0 0 1 0 0 0 0 0 0 0 0 27
28 8.1 9.4 7.9 7.7 7.7 7.6 0 0 0 1 0 0 0 0 0 0 0 28
29 8.2 9.4 8.1 7.9 7.7 7.7 0 0 0 0 1 0 0 0 0 0 0 29
30 8.2 9.2 8.2 8.1 7.9 7.7 0 0 0 0 0 1 0 0 0 0 0 30
31 8.2 9.0 8.2 8.2 8.1 7.9 0 0 0 0 0 0 1 0 0 0 0 31
32 7.9 9.0 8.2 8.2 8.2 8.1 0 0 0 0 0 0 0 1 0 0 0 32
33 7.3 9.0 7.9 8.2 8.2 8.2 0 0 0 0 0 0 0 0 1 0 0 33
34 6.9 9.8 7.3 7.9 8.2 8.2 0 0 0 0 0 0 0 0 0 1 0 34
35 6.6 10.0 6.9 7.3 7.9 8.2 0 0 0 0 0 0 0 0 0 0 1 35
36 6.7 9.8 6.6 6.9 7.3 7.9 0 0 0 0 0 0 0 0 0 0 0 36
37 6.9 9.3 6.7 6.6 6.9 7.3 1 0 0 0 0 0 0 0 0 0 0 37
38 7.0 9.0 6.9 6.7 6.6 6.9 0 1 0 0 0 0 0 0 0 0 0 38
39 7.1 9.0 7.0 6.9 6.7 6.6 0 0 1 0 0 0 0 0 0 0 0 39
40 7.2 9.1 7.1 7.0 6.9 6.7 0 0 0 1 0 0 0 0 0 0 0 40
41 7.1 9.1 7.2 7.1 7.0 6.9 0 0 0 0 1 0 0 0 0 0 0 41
42 6.9 9.1 7.1 7.2 7.1 7.0 0 0 0 0 0 1 0 0 0 0 0 42
43 7.0 9.2 6.9 7.1 7.2 7.1 0 0 0 0 0 0 1 0 0 0 0 43
44 6.8 8.8 7.0 6.9 7.1 7.2 0 0 0 0 0 0 0 1 0 0 0 44
45 6.4 8.3 6.8 7.0 6.9 7.1 0 0 0 0 0 0 0 0 1 0 0 45
46 6.7 8.4 6.4 6.8 7.0 6.9 0 0 0 0 0 0 0 0 0 1 0 46
47 6.6 8.1 6.7 6.4 6.8 7.0 0 0 0 0 0 0 0 0 0 0 1 47
48 6.4 7.7 6.6 6.7 6.4 6.8 0 0 0 0 0 0 0 0 0 0 0 48
49 6.3 7.9 6.4 6.6 6.7 6.4 1 0 0 0 0 0 0 0 0 0 0 49
50 6.2 7.9 6.3 6.4 6.6 6.7 0 1 0 0 0 0 0 0 0 0 0 50
51 6.5 8.0 6.2 6.3 6.4 6.6 0 0 1 0 0 0 0 0 0 0 0 51
52 6.8 7.9 6.5 6.2 6.3 6.4 0 0 0 1 0 0 0 0 0 0 0 52
53 6.8 7.6 6.8 6.5 6.2 6.3 0 0 0 0 1 0 0 0 0 0 0 53
54 6.4 7.1 6.8 6.8 6.5 6.2 0 0 0 0 0 1 0 0 0 0 0 54
55 6.1 6.8 6.4 6.8 6.8 6.5 0 0 0 0 0 0 1 0 0 0 0 55
56 5.8 6.5 6.1 6.4 6.8 6.8 0 0 0 0 0 0 0 1 0 0 0 56
57 6.1 6.9 5.8 6.1 6.4 6.8 0 0 0 0 0 0 0 0 1 0 0 57
58 7.2 8.2 6.1 5.8 6.1 6.4 0 0 0 0 0 0 0 0 0 1 0 58
59 7.3 8.7 7.2 6.1 5.8 6.1 0 0 0 0 0 0 0 0 0 0 1 59
60 6.9 8.3 7.3 7.2 6.1 5.8 0 0 0 0 0 0 0 0 0 0 0 60
61 6.1 7.9 6.9 7.3 7.2 6.1 1 0 0 0 0 0 0 0 0 0 0 61
62 5.8 7.5 6.1 6.9 7.3 7.2 0 1 0 0 0 0 0 0 0 0 0 62
63 6.2 7.8 5.8 6.1 6.9 7.3 0 0 1 0 0 0 0 0 0 0 0 63
64 7.1 8.3 6.2 5.8 6.1 6.9 0 0 0 1 0 0 0 0 0 0 0 64
65 7.7 8.4 7.1 6.2 5.8 6.1 0 0 0 0 1 0 0 0 0 0 0 65
66 7.9 8.2 7.7 7.1 6.2 5.8 0 0 0 0 0 1 0 0 0 0 0 66
67 7.7 7.7 7.9 7.7 7.1 6.2 0 0 0 0 0 0 1 0 0 0 0 67
68 7.4 7.2 7.7 7.9 7.7 7.1 0 0 0 0 0 0 0 1 0 0 0 68
69 7.5 7.3 7.4 7.7 7.9 7.7 0 0 0 0 0 0 0 0 1 0 0 69
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
-0.003581 0.043037 1.597928 -0.866542 -0.115378 0.314938
M1 M2 M3 M4 M5 M6
0.114619 0.059879 0.297455 0.163733 -0.034237 0.029630
M7 M8 M9 M10 M11 t
0.075059 0.008428 -0.015092 0.503061 -0.379811 0.001570
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.53023 -0.13104 0.01234 0.13003 0.43030
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.003581 0.668581 -0.005 0.99575
X 0.043037 0.055575 0.774 0.44227
Y1 1.597928 0.148078 10.791 9.02e-15 ***
Y2 -0.866542 0.269219 -3.219 0.00224 **
Y3 -0.115378 0.273253 -0.422 0.67463
Y4 0.314938 0.154496 2.038 0.04670 *
M1 0.114619 0.194376 0.590 0.55801
M2 0.059879 0.157694 0.380 0.70573
M3 0.297455 0.162991 1.825 0.07386 .
M4 0.163733 0.173158 0.946 0.34883
M5 -0.034237 0.155588 -0.220 0.82671
M6 0.029630 0.153972 0.192 0.84817
M7 0.075059 0.171619 0.437 0.66370
M8 0.008428 0.176325 0.048 0.96206
M9 -0.015092 0.168227 -0.090 0.92887
M10 0.503061 0.157899 3.186 0.00246 **
M11 -0.379811 0.202474 -1.876 0.06640 .
t 0.001570 0.002253 0.697 0.48893
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.2053 on 51 degrees of freedom
Multiple R-squared: 0.9274, Adjusted R-squared: 0.9033
F-statistic: 38.35 on 17 and 51 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,] 0.8164953 0.36700948 0.18350474
[2,] 0.7745010 0.45099807 0.22549904
[3,] 0.6996605 0.60067892 0.30033946
[4,] 0.6053537 0.78929266 0.39464633
[5,] 0.5258849 0.94823022 0.47411511
[6,] 0.4220845 0.84416907 0.57791547
[7,] 0.3370100 0.67401994 0.66299003
[8,] 0.2629253 0.52585058 0.73707471
[9,] 0.2734109 0.54682172 0.72658914
[10,] 0.2784695 0.55693896 0.72153052
[11,] 0.4614121 0.92282422 0.53858789
[12,] 0.4584465 0.91689291 0.54155355
[13,] 0.3817214 0.76344271 0.61827864
[14,] 0.8532650 0.29346999 0.14673500
[15,] 0.8020519 0.39589620 0.19794810
[16,] 0.7390808 0.52183847 0.26091924
[17,] 0.7949404 0.41011911 0.20505956
[18,] 0.7699036 0.46019286 0.23009643
[19,] 0.7195446 0.56091076 0.28045538
[20,] 0.6783739 0.64325226 0.32162613
[21,] 0.6040288 0.79194247 0.39597124
[22,] 0.4977133 0.99542657 0.50228672
[23,] 0.6154708 0.76905845 0.38452923
[24,] 0.6251702 0.74965965 0.37482982
[25,] 0.7429395 0.51412098 0.25706049
[26,] 0.9758049 0.04839025 0.02419513
[27,] 0.9362907 0.12741860 0.06370930
[28,] 0.8454225 0.30915492 0.15457746
> postscript(file="/var/www/html/rcomp/tmp/13cur1258739787.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/25piz1258739787.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3k2dz1258739787.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/482q41258739787.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/51a8i1258739787.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 = 69
Frequency = 1
1 2 3 4 5 6
0.328385297 -0.112885125 0.138051193 0.027914595 -0.052348948 -0.166951525
7 8 9 10 11 12
-0.296708058 0.111973091 0.090501881 0.145957329 0.071701918 0.132316963
13 14 15 16 17 18
-0.074430584 0.270207326 -0.010407668 -0.101913254 -0.039850198 0.146850637
19 20 21 22 23 24
-0.191352491 0.298706154 -0.343610682 0.093883398 0.075271050 0.098658357
25 26 27 28 29 30
0.120625217 -0.008104364 0.046637256 0.034943610 0.153571119 0.133333012
31 32 33 34 35 36
0.141682809 -0.144706713 -0.274872617 -0.530230750 0.127096529 0.012338628
37 38 39 40 41 42
-0.159275557 -0.134764668 -0.154376601 -0.008085431 -0.036275231 -0.075220842
43 44 45 46 47 48
0.186451191 -0.307406452 -0.249280479 0.067081270 -0.019270506 -0.146845753
49 50 51 52 53 54
0.021877976 -0.144487242 -0.006380709 -0.084508131 -0.074658364 -0.192506705
55 56 57 58 59 60
0.052708044 -0.131040042 0.346959293 0.223308753 -0.254798990 -0.096468194
61 62 63 64 65 66
-0.237182348 0.130034073 -0.013523471 0.131648611 0.049561622 0.154495424
67 68 69
0.107218505 0.172473961 0.430302604
> postscript(file="/var/www/html/rcomp/tmp/6sn4b1258739787.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 = 69
Frequency = 1
lag(myerror, k = 1) myerror
0 0.328385297 NA
1 -0.112885125 0.328385297
2 0.138051193 -0.112885125
3 0.027914595 0.138051193
4 -0.052348948 0.027914595
5 -0.166951525 -0.052348948
6 -0.296708058 -0.166951525
7 0.111973091 -0.296708058
8 0.090501881 0.111973091
9 0.145957329 0.090501881
10 0.071701918 0.145957329
11 0.132316963 0.071701918
12 -0.074430584 0.132316963
13 0.270207326 -0.074430584
14 -0.010407668 0.270207326
15 -0.101913254 -0.010407668
16 -0.039850198 -0.101913254
17 0.146850637 -0.039850198
18 -0.191352491 0.146850637
19 0.298706154 -0.191352491
20 -0.343610682 0.298706154
21 0.093883398 -0.343610682
22 0.075271050 0.093883398
23 0.098658357 0.075271050
24 0.120625217 0.098658357
25 -0.008104364 0.120625217
26 0.046637256 -0.008104364
27 0.034943610 0.046637256
28 0.153571119 0.034943610
29 0.133333012 0.153571119
30 0.141682809 0.133333012
31 -0.144706713 0.141682809
32 -0.274872617 -0.144706713
33 -0.530230750 -0.274872617
34 0.127096529 -0.530230750
35 0.012338628 0.127096529
36 -0.159275557 0.012338628
37 -0.134764668 -0.159275557
38 -0.154376601 -0.134764668
39 -0.008085431 -0.154376601
40 -0.036275231 -0.008085431
41 -0.075220842 -0.036275231
42 0.186451191 -0.075220842
43 -0.307406452 0.186451191
44 -0.249280479 -0.307406452
45 0.067081270 -0.249280479
46 -0.019270506 0.067081270
47 -0.146845753 -0.019270506
48 0.021877976 -0.146845753
49 -0.144487242 0.021877976
50 -0.006380709 -0.144487242
51 -0.084508131 -0.006380709
52 -0.074658364 -0.084508131
53 -0.192506705 -0.074658364
54 0.052708044 -0.192506705
55 -0.131040042 0.052708044
56 0.346959293 -0.131040042
57 0.223308753 0.346959293
58 -0.254798990 0.223308753
59 -0.096468194 -0.254798990
60 -0.237182348 -0.096468194
61 0.130034073 -0.237182348
62 -0.013523471 0.130034073
63 0.131648611 -0.013523471
64 0.049561622 0.131648611
65 0.154495424 0.049561622
66 0.107218505 0.154495424
67 0.172473961 0.107218505
68 0.430302604 0.172473961
69 NA 0.430302604
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.112885125 0.328385297
[2,] 0.138051193 -0.112885125
[3,] 0.027914595 0.138051193
[4,] -0.052348948 0.027914595
[5,] -0.166951525 -0.052348948
[6,] -0.296708058 -0.166951525
[7,] 0.111973091 -0.296708058
[8,] 0.090501881 0.111973091
[9,] 0.145957329 0.090501881
[10,] 0.071701918 0.145957329
[11,] 0.132316963 0.071701918
[12,] -0.074430584 0.132316963
[13,] 0.270207326 -0.074430584
[14,] -0.010407668 0.270207326
[15,] -0.101913254 -0.010407668
[16,] -0.039850198 -0.101913254
[17,] 0.146850637 -0.039850198
[18,] -0.191352491 0.146850637
[19,] 0.298706154 -0.191352491
[20,] -0.343610682 0.298706154
[21,] 0.093883398 -0.343610682
[22,] 0.075271050 0.093883398
[23,] 0.098658357 0.075271050
[24,] 0.120625217 0.098658357
[25,] -0.008104364 0.120625217
[26,] 0.046637256 -0.008104364
[27,] 0.034943610 0.046637256
[28,] 0.153571119 0.034943610
[29,] 0.133333012 0.153571119
[30,] 0.141682809 0.133333012
[31,] -0.144706713 0.141682809
[32,] -0.274872617 -0.144706713
[33,] -0.530230750 -0.274872617
[34,] 0.127096529 -0.530230750
[35,] 0.012338628 0.127096529
[36,] -0.159275557 0.012338628
[37,] -0.134764668 -0.159275557
[38,] -0.154376601 -0.134764668
[39,] -0.008085431 -0.154376601
[40,] -0.036275231 -0.008085431
[41,] -0.075220842 -0.036275231
[42,] 0.186451191 -0.075220842
[43,] -0.307406452 0.186451191
[44,] -0.249280479 -0.307406452
[45,] 0.067081270 -0.249280479
[46,] -0.019270506 0.067081270
[47,] -0.146845753 -0.019270506
[48,] 0.021877976 -0.146845753
[49,] -0.144487242 0.021877976
[50,] -0.006380709 -0.144487242
[51,] -0.084508131 -0.006380709
[52,] -0.074658364 -0.084508131
[53,] -0.192506705 -0.074658364
[54,] 0.052708044 -0.192506705
[55,] -0.131040042 0.052708044
[56,] 0.346959293 -0.131040042
[57,] 0.223308753 0.346959293
[58,] -0.254798990 0.223308753
[59,] -0.096468194 -0.254798990
[60,] -0.237182348 -0.096468194
[61,] 0.130034073 -0.237182348
[62,] -0.013523471 0.130034073
[63,] 0.131648611 -0.013523471
[64,] 0.049561622 0.131648611
[65,] 0.154495424 0.049561622
[66,] 0.107218505 0.154495424
[67,] 0.172473961 0.107218505
[68,] 0.430302604 0.172473961
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.112885125 0.328385297
2 0.138051193 -0.112885125
3 0.027914595 0.138051193
4 -0.052348948 0.027914595
5 -0.166951525 -0.052348948
6 -0.296708058 -0.166951525
7 0.111973091 -0.296708058
8 0.090501881 0.111973091
9 0.145957329 0.090501881
10 0.071701918 0.145957329
11 0.132316963 0.071701918
12 -0.074430584 0.132316963
13 0.270207326 -0.074430584
14 -0.010407668 0.270207326
15 -0.101913254 -0.010407668
16 -0.039850198 -0.101913254
17 0.146850637 -0.039850198
18 -0.191352491 0.146850637
19 0.298706154 -0.191352491
20 -0.343610682 0.298706154
21 0.093883398 -0.343610682
22 0.075271050 0.093883398
23 0.098658357 0.075271050
24 0.120625217 0.098658357
25 -0.008104364 0.120625217
26 0.046637256 -0.008104364
27 0.034943610 0.046637256
28 0.153571119 0.034943610
29 0.133333012 0.153571119
30 0.141682809 0.133333012
31 -0.144706713 0.141682809
32 -0.274872617 -0.144706713
33 -0.530230750 -0.274872617
34 0.127096529 -0.530230750
35 0.012338628 0.127096529
36 -0.159275557 0.012338628
37 -0.134764668 -0.159275557
38 -0.154376601 -0.134764668
39 -0.008085431 -0.154376601
40 -0.036275231 -0.008085431
41 -0.075220842 -0.036275231
42 0.186451191 -0.075220842
43 -0.307406452 0.186451191
44 -0.249280479 -0.307406452
45 0.067081270 -0.249280479
46 -0.019270506 0.067081270
47 -0.146845753 -0.019270506
48 0.021877976 -0.146845753
49 -0.144487242 0.021877976
50 -0.006380709 -0.144487242
51 -0.084508131 -0.006380709
52 -0.074658364 -0.084508131
53 -0.192506705 -0.074658364
54 0.052708044 -0.192506705
55 -0.131040042 0.052708044
56 0.346959293 -0.131040042
57 0.223308753 0.346959293
58 -0.254798990 0.223308753
59 -0.096468194 -0.254798990
60 -0.237182348 -0.096468194
61 0.130034073 -0.237182348
62 -0.013523471 0.130034073
63 0.131648611 -0.013523471
64 0.049561622 0.131648611
65 0.154495424 0.049561622
66 0.107218505 0.154495424
67 0.172473961 0.107218505
68 0.430302604 0.172473961
> 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/79a5b1258739787.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8w33h1258739787.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9g74x1258739787.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10jreh1258739787.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/115zjw1258739787.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/12vx851258739787.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/13js2b1258739787.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/14gcob1258739787.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/1538c81258739787.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/16grlh1258739787.tab")
+ }
>
> system("convert tmp/13cur1258739787.ps tmp/13cur1258739787.png")
> system("convert tmp/25piz1258739787.ps tmp/25piz1258739787.png")
> system("convert tmp/3k2dz1258739787.ps tmp/3k2dz1258739787.png")
> system("convert tmp/482q41258739787.ps tmp/482q41258739787.png")
> system("convert tmp/51a8i1258739787.ps tmp/51a8i1258739787.png")
> system("convert tmp/6sn4b1258739787.ps tmp/6sn4b1258739787.png")
> system("convert tmp/79a5b1258739787.ps tmp/79a5b1258739787.png")
> system("convert tmp/8w33h1258739787.ps tmp/8w33h1258739787.png")
> system("convert tmp/9g74x1258739787.ps tmp/9g74x1258739787.png")
> system("convert tmp/10jreh1258739787.ps tmp/10jreh1258739787.png")
>
>
> proc.time()
user system elapsed
2.457 1.607 2.911