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(101.5,1,100.7,1,110.6,1,96.8,1,100.0,1,104.8,1,86.8,1,92.0,1,100.2,1,106.6,1,102.1,1,93.7,1,97.6,1,96.9,1,105.6,1,102.8,1,101.7,1,104.2,1,92.7,1,91.9,1,106.5,1,112.3,1,102.8,1,96.5,1,101.0,0,98.9,0,105.1,0,103.0,0,99.0,0,104.3,0,94.6,0,90.4,0,108.9,0,111.4,0,100.8,0,102.5,0,98.2,0,98.7,0,113.3,0,104.6,0,99.3,0,111.8,0,97.3,0,97.7,0,115.6,0,111.9,0,107.0,0,107.1,0,100.6,0,99.2,0,108.4,0,103.0,0,99.8,0,115.0,0,90.8,0,95.9,0,114.4,0,108.2,0,112.6,0,109.1,0,105.0,0,105.0,0,118.5,0,103.7,0,112.5,0,116.6,0,96.6,0,101.9,0,116.5,0,119.3,0,115.4,0,108.5,0,111.5,0,108.8,0,121.8,0,109.6,0,112.2,0,119.6,0,104.1,0,105.3,0,115.0,0,124.1,0,116.8,0,107.5,0,115.6,0,116.2,0,116.3,0,119.0,0,111.9,0,118.6,0,106.9,0,103.2,0),dim=c(2,92),dimnames=list(c('Y','X'),1:92))
> y <- array(NA,dim=c(2,92),dimnames=list(c('Y','X'),1:92))
> 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 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 101.5 1 1 0 0 0 0 0 0 0 0 0 0 1
2 100.7 1 0 1 0 0 0 0 0 0 0 0 0 2
3 110.6 1 0 0 1 0 0 0 0 0 0 0 0 3
4 96.8 1 0 0 0 1 0 0 0 0 0 0 0 4
5 100.0 1 0 0 0 0 1 0 0 0 0 0 0 5
6 104.8 1 0 0 0 0 0 1 0 0 0 0 0 6
7 86.8 1 0 0 0 0 0 0 1 0 0 0 0 7
8 92.0 1 0 0 0 0 0 0 0 1 0 0 0 8
9 100.2 1 0 0 0 0 0 0 0 0 1 0 0 9
10 106.6 1 0 0 0 0 0 0 0 0 0 1 0 10
11 102.1 1 0 0 0 0 0 0 0 0 0 0 1 11
12 93.7 1 0 0 0 0 0 0 0 0 0 0 0 12
13 97.6 1 1 0 0 0 0 0 0 0 0 0 0 13
14 96.9 1 0 1 0 0 0 0 0 0 0 0 0 14
15 105.6 1 0 0 1 0 0 0 0 0 0 0 0 15
16 102.8 1 0 0 0 1 0 0 0 0 0 0 0 16
17 101.7 1 0 0 0 0 1 0 0 0 0 0 0 17
18 104.2 1 0 0 0 0 0 1 0 0 0 0 0 18
19 92.7 1 0 0 0 0 0 0 1 0 0 0 0 19
20 91.9 1 0 0 0 0 0 0 0 1 0 0 0 20
21 106.5 1 0 0 0 0 0 0 0 0 1 0 0 21
22 112.3 1 0 0 0 0 0 0 0 0 0 1 0 22
23 102.8 1 0 0 0 0 0 0 0 0 0 0 1 23
24 96.5 1 0 0 0 0 0 0 0 0 0 0 0 24
25 101.0 0 1 0 0 0 0 0 0 0 0 0 0 25
26 98.9 0 0 1 0 0 0 0 0 0 0 0 0 26
27 105.1 0 0 0 1 0 0 0 0 0 0 0 0 27
28 103.0 0 0 0 0 1 0 0 0 0 0 0 0 28
29 99.0 0 0 0 0 0 1 0 0 0 0 0 0 29
30 104.3 0 0 0 0 0 0 1 0 0 0 0 0 30
31 94.6 0 0 0 0 0 0 0 1 0 0 0 0 31
32 90.4 0 0 0 0 0 0 0 0 1 0 0 0 32
33 108.9 0 0 0 0 0 0 0 0 0 1 0 0 33
34 111.4 0 0 0 0 0 0 0 0 0 0 1 0 34
35 100.8 0 0 0 0 0 0 0 0 0 0 0 1 35
36 102.5 0 0 0 0 0 0 0 0 0 0 0 0 36
37 98.2 0 1 0 0 0 0 0 0 0 0 0 0 37
38 98.7 0 0 1 0 0 0 0 0 0 0 0 0 38
39 113.3 0 0 0 1 0 0 0 0 0 0 0 0 39
40 104.6 0 0 0 0 1 0 0 0 0 0 0 0 40
41 99.3 0 0 0 0 0 1 0 0 0 0 0 0 41
42 111.8 0 0 0 0 0 0 1 0 0 0 0 0 42
43 97.3 0 0 0 0 0 0 0 1 0 0 0 0 43
44 97.7 0 0 0 0 0 0 0 0 1 0 0 0 44
45 115.6 0 0 0 0 0 0 0 0 0 1 0 0 45
46 111.9 0 0 0 0 0 0 0 0 0 0 1 0 46
47 107.0 0 0 0 0 0 0 0 0 0 0 0 1 47
48 107.1 0 0 0 0 0 0 0 0 0 0 0 0 48
49 100.6 0 1 0 0 0 0 0 0 0 0 0 0 49
50 99.2 0 0 1 0 0 0 0 0 0 0 0 0 50
51 108.4 0 0 0 1 0 0 0 0 0 0 0 0 51
52 103.0 0 0 0 0 1 0 0 0 0 0 0 0 52
53 99.8 0 0 0 0 0 1 0 0 0 0 0 0 53
54 115.0 0 0 0 0 0 0 1 0 0 0 0 0 54
55 90.8 0 0 0 0 0 0 0 1 0 0 0 0 55
56 95.9 0 0 0 0 0 0 0 0 1 0 0 0 56
57 114.4 0 0 0 0 0 0 0 0 0 1 0 0 57
58 108.2 0 0 0 0 0 0 0 0 0 0 1 0 58
59 112.6 0 0 0 0 0 0 0 0 0 0 0 1 59
60 109.1 0 0 0 0 0 0 0 0 0 0 0 0 60
61 105.0 0 1 0 0 0 0 0 0 0 0 0 0 61
62 105.0 0 0 1 0 0 0 0 0 0 0 0 0 62
63 118.5 0 0 0 1 0 0 0 0 0 0 0 0 63
64 103.7 0 0 0 0 1 0 0 0 0 0 0 0 64
65 112.5 0 0 0 0 0 1 0 0 0 0 0 0 65
66 116.6 0 0 0 0 0 0 1 0 0 0 0 0 66
67 96.6 0 0 0 0 0 0 0 1 0 0 0 0 67
68 101.9 0 0 0 0 0 0 0 0 1 0 0 0 68
69 116.5 0 0 0 0 0 0 0 0 0 1 0 0 69
70 119.3 0 0 0 0 0 0 0 0 0 0 1 0 70
71 115.4 0 0 0 0 0 0 0 0 0 0 0 1 71
72 108.5 0 0 0 0 0 0 0 0 0 0 0 0 72
73 111.5 0 1 0 0 0 0 0 0 0 0 0 0 73
74 108.8 0 0 1 0 0 0 0 0 0 0 0 0 74
75 121.8 0 0 0 1 0 0 0 0 0 0 0 0 75
76 109.6 0 0 0 0 1 0 0 0 0 0 0 0 76
77 112.2 0 0 0 0 0 1 0 0 0 0 0 0 77
78 119.6 0 0 0 0 0 0 1 0 0 0 0 0 78
79 104.1 0 0 0 0 0 0 0 1 0 0 0 0 79
80 105.3 0 0 0 0 0 0 0 0 1 0 0 0 80
81 115.0 0 0 0 0 0 0 0 0 0 1 0 0 81
82 124.1 0 0 0 0 0 0 0 0 0 0 1 0 82
83 116.8 0 0 0 0 0 0 0 0 0 0 0 1 83
84 107.5 0 0 0 0 0 0 0 0 0 0 0 0 84
85 115.6 0 1 0 0 0 0 0 0 0 0 0 0 85
86 116.2 0 0 1 0 0 0 0 0 0 0 0 0 86
87 116.3 0 0 0 1 0 0 0 0 0 0 0 0 87
88 119.0 0 0 0 0 1 0 0 0 0 0 0 0 88
89 111.9 0 0 0 0 0 1 0 0 0 0 0 0 89
90 118.6 0 0 0 0 0 0 1 0 0 0 0 0 90
91 106.9 0 0 0 0 0 0 0 1 0 0 0 0 91
92 103.2 0 0 0 0 0 0 0 0 1 0 0 0 92
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
91.7817 2.9190 1.5618 0.5089 9.6809 2.3155
M5 M6 M7 M8 M9 M10
1.3251 8.4096 -7.4558 -6.6213 8.1410 10.2988
M11 t
4.8851 0.2279
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-7.1014 -2.2494 0.5024 2.3354 5.5345
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 91.78168 1.72940 53.071 < 2e-16 ***
X 2.91902 1.18850 2.456 0.016271 *
M1 1.56184 1.67781 0.931 0.354786
M2 0.50890 1.67639 0.304 0.762266
M3 9.68095 1.67519 5.779 1.47e-07 ***
M4 2.31550 1.67423 1.383 0.170605
M5 1.32505 1.67351 0.792 0.430888
M6 8.40961 1.67301 5.027 3.10e-06 ***
M7 -7.45584 1.67274 -4.457 2.74e-05 ***
M8 -6.62129 1.67271 -3.958 0.000165 ***
M9 8.14098 1.72833 4.710 1.06e-05 ***
M10 10.29875 1.72777 5.961 6.88e-08 ***
M11 4.88509 1.72743 2.828 0.005951 **
t 0.22795 0.01969 11.574 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 3.232 on 78 degrees of freedom
Multiple R-squared: 0.8635, Adjusted R-squared: 0.8408
F-statistic: 37.96 on 13 and 78 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,] 0.75643934 0.4871213 0.2435607
[2,] 0.61623125 0.7675375 0.3837687
[3,] 0.68903205 0.6219359 0.3109679
[4,] 0.56700573 0.8659885 0.4329943
[5,] 0.60797381 0.7840524 0.3920262
[6,] 0.61545738 0.7690852 0.3845426
[7,] 0.51481766 0.9703647 0.4851823
[8,] 0.42189187 0.8437837 0.5781081
[9,] 0.33841842 0.6768368 0.6615816
[10,] 0.26214506 0.5242901 0.7378549
[11,] 0.23262821 0.4652564 0.7673718
[12,] 0.21748151 0.4349630 0.7825185
[13,] 0.17144210 0.3428842 0.8285579
[14,] 0.12864053 0.2572811 0.8713595
[15,] 0.15277593 0.3055519 0.8472241
[16,] 0.12014704 0.2402941 0.8798530
[17,] 0.13534768 0.2706954 0.8646523
[18,] 0.10334947 0.2066989 0.8966505
[19,] 0.09602741 0.1920548 0.9039726
[20,] 0.14046623 0.2809325 0.8595338
[21,] 0.13711391 0.2742278 0.8628861
[22,] 0.10611665 0.2122333 0.8938834
[23,] 0.12416190 0.2483238 0.8758381
[24,] 0.10254200 0.2050840 0.8974580
[25,] 0.08879956 0.1775991 0.9112004
[26,] 0.10325685 0.2065137 0.8967431
[27,] 0.11474377 0.2294875 0.8852562
[28,] 0.11728456 0.2345691 0.8827154
[29,] 0.23961873 0.4792375 0.7603813
[30,] 0.19638766 0.3927753 0.8036123
[31,] 0.15689421 0.3137884 0.8431058
[32,] 0.22791876 0.4558375 0.7720812
[33,] 0.21814842 0.4362968 0.7818516
[34,] 0.21880506 0.4376101 0.7811949
[35,] 0.22010381 0.4402076 0.7798962
[36,] 0.18057653 0.3611531 0.8194235
[37,] 0.21344633 0.4268927 0.7865537
[38,] 0.22753826 0.4550765 0.7724617
[39,] 0.28862809 0.5772562 0.7113719
[40,] 0.23637992 0.4727598 0.7636201
[41,] 0.21466990 0.4293398 0.7853301
[42,] 0.42398687 0.8479737 0.5760131
[43,] 0.41659408 0.8331882 0.5834059
[44,] 0.47207061 0.9441412 0.5279294
[45,] 0.46535246 0.9307049 0.5346475
[46,] 0.44326141 0.8865228 0.5567386
[47,] 0.43092785 0.8618557 0.5690722
[48,] 0.57955478 0.8408904 0.4204452
[49,] 0.61568671 0.7686266 0.3843133
[50,] 0.53951459 0.9209708 0.4604854
[51,] 0.62091417 0.7581717 0.3790858
[52,] 0.53126630 0.9374674 0.4687337
[53,] 0.47097086 0.9419417 0.5290291
[54,] 0.41496043 0.8299209 0.5850396
[55,] 0.32555330 0.6511066 0.6744467
[56,] 0.24949229 0.4989846 0.7505077
[57,] 0.18135892 0.3627178 0.8186411
[58,] 0.20591552 0.4118310 0.7940845
[59,] 0.26706568 0.5341314 0.7329343
> postscript(file="/var/www/html/freestat/rcomp/tmp/1zns01229040984.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/23ujf1229040984.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3q6mh1229040984.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/469bf1229040984.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5ygtg1229040984.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 = 92
Frequency = 1
1 2 3 4 5 6
5.009510870 5.034510870 5.534510870 -1.127989130 2.834510870 0.322010870
7 8 9 10 11 12
-2.040489130 2.097010870 -4.693206522 -0.678920807 0.006793478 -3.736063665
13 14 15 16 17 18
-1.625854037 -1.500854037 -2.200854037 2.136645963 1.799145963 -3.013354037
19 20 21 22 23 24
1.124145963 -0.738354037 -1.128571429 2.285714286 -2.028571429 -3.671428571
25 26 27 28 29 30
1.957802795 0.682802795 -2.517197205 2.520302795 -0.717197205 -2.729697205
31 32 33 34 35 36
3.207802795 -2.054697205 1.455085404 1.569371118 -3.844914596 2.512228261
37 38 39 40 41 42
-3.577562112 -2.252562112 2.947437888 1.384937888 -3.152562112 2.034937888
43 44 45 46 47 48
3.172437888 2.509937888 5.419720497 -0.665993789 -0.380279503 4.376863354
49 50 51 52 53 54
-3.912927019 -4.487927019 -4.687927019 -2.950427019 -5.387927019 2.499572981
55 56 57 58 59 60
-6.062927019 -2.025427019 1.484355590 -7.101358696 2.484355590 3.641498447
61 62 63 64 65 66
-2.248291925 -1.423291925 2.676708075 -4.985791925 4.576708075 1.364208075
67 68 69 70 71 72
-2.998291925 1.239208075 0.848990683 1.263276398 2.548990683 0.306133540
73 74 75 76 77 78
1.516343168 -0.358656832 3.241343168 -1.821156832 1.541343168 1.628843168
79 80 81 82 83 84
1.766343168 1.903843168 -3.386374224 3.327911491 1.213625776 -3.429231366
85 86 87 88 89 90
2.880978261 4.305978261 -4.994021739 4.843478261 -1.494021739 -2.106521739
91 92
1.830978261 -2.931521739
> postscript(file="/var/www/html/freestat/rcomp/tmp/6raym1229040984.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 = 92
Frequency = 1
lag(myerror, k = 1) myerror
0 5.009510870 NA
1 5.034510870 5.009510870
2 5.534510870 5.034510870
3 -1.127989130 5.534510870
4 2.834510870 -1.127989130
5 0.322010870 2.834510870
6 -2.040489130 0.322010870
7 2.097010870 -2.040489130
8 -4.693206522 2.097010870
9 -0.678920807 -4.693206522
10 0.006793478 -0.678920807
11 -3.736063665 0.006793478
12 -1.625854037 -3.736063665
13 -1.500854037 -1.625854037
14 -2.200854037 -1.500854037
15 2.136645963 -2.200854037
16 1.799145963 2.136645963
17 -3.013354037 1.799145963
18 1.124145963 -3.013354037
19 -0.738354037 1.124145963
20 -1.128571429 -0.738354037
21 2.285714286 -1.128571429
22 -2.028571429 2.285714286
23 -3.671428571 -2.028571429
24 1.957802795 -3.671428571
25 0.682802795 1.957802795
26 -2.517197205 0.682802795
27 2.520302795 -2.517197205
28 -0.717197205 2.520302795
29 -2.729697205 -0.717197205
30 3.207802795 -2.729697205
31 -2.054697205 3.207802795
32 1.455085404 -2.054697205
33 1.569371118 1.455085404
34 -3.844914596 1.569371118
35 2.512228261 -3.844914596
36 -3.577562112 2.512228261
37 -2.252562112 -3.577562112
38 2.947437888 -2.252562112
39 1.384937888 2.947437888
40 -3.152562112 1.384937888
41 2.034937888 -3.152562112
42 3.172437888 2.034937888
43 2.509937888 3.172437888
44 5.419720497 2.509937888
45 -0.665993789 5.419720497
46 -0.380279503 -0.665993789
47 4.376863354 -0.380279503
48 -3.912927019 4.376863354
49 -4.487927019 -3.912927019
50 -4.687927019 -4.487927019
51 -2.950427019 -4.687927019
52 -5.387927019 -2.950427019
53 2.499572981 -5.387927019
54 -6.062927019 2.499572981
55 -2.025427019 -6.062927019
56 1.484355590 -2.025427019
57 -7.101358696 1.484355590
58 2.484355590 -7.101358696
59 3.641498447 2.484355590
60 -2.248291925 3.641498447
61 -1.423291925 -2.248291925
62 2.676708075 -1.423291925
63 -4.985791925 2.676708075
64 4.576708075 -4.985791925
65 1.364208075 4.576708075
66 -2.998291925 1.364208075
67 1.239208075 -2.998291925
68 0.848990683 1.239208075
69 1.263276398 0.848990683
70 2.548990683 1.263276398
71 0.306133540 2.548990683
72 1.516343168 0.306133540
73 -0.358656832 1.516343168
74 3.241343168 -0.358656832
75 -1.821156832 3.241343168
76 1.541343168 -1.821156832
77 1.628843168 1.541343168
78 1.766343168 1.628843168
79 1.903843168 1.766343168
80 -3.386374224 1.903843168
81 3.327911491 -3.386374224
82 1.213625776 3.327911491
83 -3.429231366 1.213625776
84 2.880978261 -3.429231366
85 4.305978261 2.880978261
86 -4.994021739 4.305978261
87 4.843478261 -4.994021739
88 -1.494021739 4.843478261
89 -2.106521739 -1.494021739
90 1.830978261 -2.106521739
91 -2.931521739 1.830978261
92 NA -2.931521739
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 5.034510870 5.009510870
[2,] 5.534510870 5.034510870
[3,] -1.127989130 5.534510870
[4,] 2.834510870 -1.127989130
[5,] 0.322010870 2.834510870
[6,] -2.040489130 0.322010870
[7,] 2.097010870 -2.040489130
[8,] -4.693206522 2.097010870
[9,] -0.678920807 -4.693206522
[10,] 0.006793478 -0.678920807
[11,] -3.736063665 0.006793478
[12,] -1.625854037 -3.736063665
[13,] -1.500854037 -1.625854037
[14,] -2.200854037 -1.500854037
[15,] 2.136645963 -2.200854037
[16,] 1.799145963 2.136645963
[17,] -3.013354037 1.799145963
[18,] 1.124145963 -3.013354037
[19,] -0.738354037 1.124145963
[20,] -1.128571429 -0.738354037
[21,] 2.285714286 -1.128571429
[22,] -2.028571429 2.285714286
[23,] -3.671428571 -2.028571429
[24,] 1.957802795 -3.671428571
[25,] 0.682802795 1.957802795
[26,] -2.517197205 0.682802795
[27,] 2.520302795 -2.517197205
[28,] -0.717197205 2.520302795
[29,] -2.729697205 -0.717197205
[30,] 3.207802795 -2.729697205
[31,] -2.054697205 3.207802795
[32,] 1.455085404 -2.054697205
[33,] 1.569371118 1.455085404
[34,] -3.844914596 1.569371118
[35,] 2.512228261 -3.844914596
[36,] -3.577562112 2.512228261
[37,] -2.252562112 -3.577562112
[38,] 2.947437888 -2.252562112
[39,] 1.384937888 2.947437888
[40,] -3.152562112 1.384937888
[41,] 2.034937888 -3.152562112
[42,] 3.172437888 2.034937888
[43,] 2.509937888 3.172437888
[44,] 5.419720497 2.509937888
[45,] -0.665993789 5.419720497
[46,] -0.380279503 -0.665993789
[47,] 4.376863354 -0.380279503
[48,] -3.912927019 4.376863354
[49,] -4.487927019 -3.912927019
[50,] -4.687927019 -4.487927019
[51,] -2.950427019 -4.687927019
[52,] -5.387927019 -2.950427019
[53,] 2.499572981 -5.387927019
[54,] -6.062927019 2.499572981
[55,] -2.025427019 -6.062927019
[56,] 1.484355590 -2.025427019
[57,] -7.101358696 1.484355590
[58,] 2.484355590 -7.101358696
[59,] 3.641498447 2.484355590
[60,] -2.248291925 3.641498447
[61,] -1.423291925 -2.248291925
[62,] 2.676708075 -1.423291925
[63,] -4.985791925 2.676708075
[64,] 4.576708075 -4.985791925
[65,] 1.364208075 4.576708075
[66,] -2.998291925 1.364208075
[67,] 1.239208075 -2.998291925
[68,] 0.848990683 1.239208075
[69,] 1.263276398 0.848990683
[70,] 2.548990683 1.263276398
[71,] 0.306133540 2.548990683
[72,] 1.516343168 0.306133540
[73,] -0.358656832 1.516343168
[74,] 3.241343168 -0.358656832
[75,] -1.821156832 3.241343168
[76,] 1.541343168 -1.821156832
[77,] 1.628843168 1.541343168
[78,] 1.766343168 1.628843168
[79,] 1.903843168 1.766343168
[80,] -3.386374224 1.903843168
[81,] 3.327911491 -3.386374224
[82,] 1.213625776 3.327911491
[83,] -3.429231366 1.213625776
[84,] 2.880978261 -3.429231366
[85,] 4.305978261 2.880978261
[86,] -4.994021739 4.305978261
[87,] 4.843478261 -4.994021739
[88,] -1.494021739 4.843478261
[89,] -2.106521739 -1.494021739
[90,] 1.830978261 -2.106521739
[91,] -2.931521739 1.830978261
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 5.034510870 5.009510870
2 5.534510870 5.034510870
3 -1.127989130 5.534510870
4 2.834510870 -1.127989130
5 0.322010870 2.834510870
6 -2.040489130 0.322010870
7 2.097010870 -2.040489130
8 -4.693206522 2.097010870
9 -0.678920807 -4.693206522
10 0.006793478 -0.678920807
11 -3.736063665 0.006793478
12 -1.625854037 -3.736063665
13 -1.500854037 -1.625854037
14 -2.200854037 -1.500854037
15 2.136645963 -2.200854037
16 1.799145963 2.136645963
17 -3.013354037 1.799145963
18 1.124145963 -3.013354037
19 -0.738354037 1.124145963
20 -1.128571429 -0.738354037
21 2.285714286 -1.128571429
22 -2.028571429 2.285714286
23 -3.671428571 -2.028571429
24 1.957802795 -3.671428571
25 0.682802795 1.957802795
26 -2.517197205 0.682802795
27 2.520302795 -2.517197205
28 -0.717197205 2.520302795
29 -2.729697205 -0.717197205
30 3.207802795 -2.729697205
31 -2.054697205 3.207802795
32 1.455085404 -2.054697205
33 1.569371118 1.455085404
34 -3.844914596 1.569371118
35 2.512228261 -3.844914596
36 -3.577562112 2.512228261
37 -2.252562112 -3.577562112
38 2.947437888 -2.252562112
39 1.384937888 2.947437888
40 -3.152562112 1.384937888
41 2.034937888 -3.152562112
42 3.172437888 2.034937888
43 2.509937888 3.172437888
44 5.419720497 2.509937888
45 -0.665993789 5.419720497
46 -0.380279503 -0.665993789
47 4.376863354 -0.380279503
48 -3.912927019 4.376863354
49 -4.487927019 -3.912927019
50 -4.687927019 -4.487927019
51 -2.950427019 -4.687927019
52 -5.387927019 -2.950427019
53 2.499572981 -5.387927019
54 -6.062927019 2.499572981
55 -2.025427019 -6.062927019
56 1.484355590 -2.025427019
57 -7.101358696 1.484355590
58 2.484355590 -7.101358696
59 3.641498447 2.484355590
60 -2.248291925 3.641498447
61 -1.423291925 -2.248291925
62 2.676708075 -1.423291925
63 -4.985791925 2.676708075
64 4.576708075 -4.985791925
65 1.364208075 4.576708075
66 -2.998291925 1.364208075
67 1.239208075 -2.998291925
68 0.848990683 1.239208075
69 1.263276398 0.848990683
70 2.548990683 1.263276398
71 0.306133540 2.548990683
72 1.516343168 0.306133540
73 -0.358656832 1.516343168
74 3.241343168 -0.358656832
75 -1.821156832 3.241343168
76 1.541343168 -1.821156832
77 1.628843168 1.541343168
78 1.766343168 1.628843168
79 1.903843168 1.766343168
80 -3.386374224 1.903843168
81 3.327911491 -3.386374224
82 1.213625776 3.327911491
83 -3.429231366 1.213625776
84 2.880978261 -3.429231366
85 4.305978261 2.880978261
86 -4.994021739 4.305978261
87 4.843478261 -4.994021739
88 -1.494021739 4.843478261
89 -2.106521739 -1.494021739
90 1.830978261 -2.106521739
91 -2.931521739 1.830978261
> 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/7oggz1229040984.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8k6hm1229040984.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9xgpe1229040984.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10ylbf1229040984.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11v9kc1229040984.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/122lz71229040984.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/13ipgf1229040984.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/14t8yd1229040984.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/159fbw1229040984.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/16lvcm1229040984.tab")
+ }
>
> system("convert tmp/1zns01229040984.ps tmp/1zns01229040984.png")
> system("convert tmp/23ujf1229040984.ps tmp/23ujf1229040984.png")
> system("convert tmp/3q6mh1229040984.ps tmp/3q6mh1229040984.png")
> system("convert tmp/469bf1229040984.ps tmp/469bf1229040984.png")
> system("convert tmp/5ygtg1229040984.ps tmp/5ygtg1229040984.png")
> system("convert tmp/6raym1229040984.ps tmp/6raym1229040984.png")
> system("convert tmp/7oggz1229040984.ps tmp/7oggz1229040984.png")
> system("convert tmp/8k6hm1229040984.ps tmp/8k6hm1229040984.png")
> system("convert tmp/9xgpe1229040984.ps tmp/9xgpe1229040984.png")
> system("convert tmp/10ylbf1229040984.ps tmp/10ylbf1229040984.png")
>
>
> proc.time()
user system elapsed
4.404 2.663 5.035