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(106.7,0,110.2,0,125.9,0,100.1,0,106.4,0,114.8,0,81.3,0,87,0,104.2,0,108,0,105,0,94.5,0,92,0,95.9,0,108.8,0,103.4,0,102.1,0,110.1,0,83.2,0,82.7,0,106.8,0,113.7,0,102.5,0,96.6,0,92.1,0,95.6,0,102.3,0,98.6,0,98.2,0,104.5,0,84,0,73.8,0,103.9,0,106,0,97.2,0,102.6,0,89,0,93.8,0,116.7,1,106.8,1,98.5,1,118.7,1,90,1,91.9,1,113.3,1,113.1,1,104.1,1,108.7,1,96.7,1,101,1,116.9,1,105.8,1,99,1,129.4,1,83,1,88.9,1,115.9,1,104.2,1,113.4,1,112.2,1,100.8,1,107.3,1,126.6,1,102.9,1,117.9,1,128.8,1,87.5,1,93.8,1,122.7,1,126.2,1,124.6,1,116.7,1,115.2,1,111.1,1,129.9,1,113.3,1,118.5,1,133.5,1,102.1,1,102.4,1),dim=c(2,80),dimnames=list(c('y','x'),1:80))
> y <- array(NA,dim=c(2,80),dimnames=list(c('y','x'),1:80))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal 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
1 106.7 0
2 110.2 0
3 125.9 0
4 100.1 0
5 106.4 0
6 114.8 0
7 81.3 0
8 87.0 0
9 104.2 0
10 108.0 0
11 105.0 0
12 94.5 0
13 92.0 0
14 95.9 0
15 108.8 0
16 103.4 0
17 102.1 0
18 110.1 0
19 83.2 0
20 82.7 0
21 106.8 0
22 113.7 0
23 102.5 0
24 96.6 0
25 92.1 0
26 95.6 0
27 102.3 0
28 98.6 0
29 98.2 0
30 104.5 0
31 84.0 0
32 73.8 0
33 103.9 0
34 106.0 0
35 97.2 0
36 102.6 0
37 89.0 0
38 93.8 0
39 116.7 1
40 106.8 1
41 98.5 1
42 118.7 1
43 90.0 1
44 91.9 1
45 113.3 1
46 113.1 1
47 104.1 1
48 108.7 1
49 96.7 1
50 101.0 1
51 116.9 1
52 105.8 1
53 99.0 1
54 129.4 1
55 83.0 1
56 88.9 1
57 115.9 1
58 104.2 1
59 113.4 1
60 112.2 1
61 100.8 1
62 107.3 1
63 126.6 1
64 102.9 1
65 117.9 1
66 128.8 1
67 87.5 1
68 93.8 1
69 122.7 1
70 126.2 1
71 124.6 1
72 116.7 1
73 115.2 1
74 111.1 1
75 129.9 1
76 113.3 1
77 118.5 1
78 133.5 1
79 102.1 1
80 102.4 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x
99.57 10.20
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-26.762 -7.491 2.486 7.135 26.334
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 99.566 1.901 52.387 < 2e-16 ***
x 10.196 2.623 3.887 0.000212 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 11.72 on 78 degrees of freedom
Multiple R-squared: 0.1623, Adjusted R-squared: 0.1515
F-statistic: 15.11 on 1 and 78 DF, p-value: 0.0002117
> 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,] 0.57299127 0.85401746 0.42700873
[2,] 0.44122328 0.88244656 0.55877672
[3,] 0.86759339 0.26481322 0.13240661
[4,] 0.90613335 0.18773330 0.09386665
[5,] 0.85190610 0.29618779 0.14809390
[6,] 0.79360688 0.41278625 0.20639312
[7,] 0.71743462 0.56513075 0.28256538
[8,] 0.67647877 0.64704246 0.32352123
[9,] 0.65413691 0.69172617 0.34586309
[10,] 0.58900926 0.82198149 0.41099074
[11,] 0.53374178 0.93251644 0.46625822
[12,] 0.45103462 0.90206925 0.54896538
[13,] 0.37093846 0.74187691 0.62906154
[14,] 0.33685839 0.67371677 0.66314161
[15,] 0.45524577 0.91049154 0.54475423
[16,] 0.55701401 0.88597198 0.44298599
[17,] 0.50421763 0.99156474 0.49578237
[18,] 0.52544688 0.94910623 0.47455312
[19,] 0.45728118 0.91456236 0.54271882
[20,] 0.39600276 0.79200553 0.60399724
[21,] 0.36200281 0.72400562 0.63799719
[22,] 0.30774807 0.61549615 0.69225193
[23,] 0.25327294 0.50654589 0.74672706
[24,] 0.20291542 0.40583084 0.79708458
[25,] 0.15972938 0.31945875 0.84027062
[26,] 0.13136256 0.26272512 0.86863744
[27,] 0.16198018 0.32396035 0.83801982
[28,] 0.35809778 0.71619555 0.64190222
[29,] 0.30674875 0.61349751 0.69325125
[30,] 0.27195209 0.54390418 0.72804791
[31,] 0.22167052 0.44334104 0.77832948
[32,] 0.18670914 0.37341828 0.81329086
[33,] 0.16789169 0.33578338 0.83210831
[34,] 0.13504471 0.27008941 0.86495529
[35,] 0.10651638 0.21303277 0.89348362
[36,] 0.08524448 0.17048897 0.91475552
[37,] 0.08205006 0.16410011 0.91794994
[38,] 0.07348379 0.14696758 0.92651621
[39,] 0.11561960 0.23123921 0.88438040
[40,] 0.14240667 0.28481334 0.85759333
[41,] 0.11862059 0.23724119 0.88137941
[42,] 0.09522771 0.19045542 0.90477229
[43,] 0.07381219 0.14762438 0.92618781
[44,] 0.05406864 0.10813728 0.94593136
[45,] 0.05409353 0.10818706 0.94590647
[46,] 0.04466962 0.08933923 0.95533038
[47,] 0.03814518 0.07629036 0.96185482
[48,] 0.02736128 0.05472256 0.97263872
[49,] 0.02472642 0.04945283 0.97527358
[50,] 0.04937339 0.09874678 0.95062661
[51,] 0.16563148 0.33126296 0.83436852
[52,] 0.29056282 0.58112565 0.70943718
[53,] 0.24954857 0.49909714 0.75045143
[54,] 0.21858505 0.43717009 0.78141495
[55,] 0.17507010 0.35014019 0.82492990
[56,] 0.13550809 0.27101619 0.86449191
[57,] 0.13295262 0.26590524 0.86704738
[58,] 0.10579589 0.21159179 0.89420411
[59,] 0.12344192 0.24688383 0.87655808
[60,] 0.11225673 0.22451346 0.88774327
[61,] 0.08553381 0.17106762 0.91446619
[62,] 0.11030691 0.22061382 0.88969309
[63,] 0.33140950 0.66281901 0.66859050
[64,] 0.58364994 0.83270012 0.41635006
[65,] 0.52217419 0.95565162 0.47782581
[66,] 0.50441547 0.99116907 0.49558453
[67,] 0.46417748 0.92835497 0.53582252
[68,] 0.35323707 0.70647414 0.64676293
[69,] 0.24586725 0.49173450 0.75413275
[70,] 0.16256920 0.32513839 0.83743080
[71,] 0.18323464 0.36646927 0.81676536
> postscript(file="/var/www/html/freestat/rcomp/tmp/1ignl1227566948.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2kr9n1227566948.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3is7f1227566948.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4hbfv1227566948.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5y3se1227566948.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 = 80
Frequency = 1
1 2 3 4 5 6
7.1342105 10.6342105 26.3342105 0.5342105 6.8342105 15.2342105
7 8 9 10 11 12
-18.2657895 -12.5657895 4.6342105 8.4342105 5.4342105 -5.0657895
13 14 15 16 17 18
-7.5657895 -3.6657895 9.2342105 3.8342105 2.5342105 10.5342105
19 20 21 22 23 24
-16.3657895 -16.8657895 7.2342105 14.1342105 2.9342105 -2.9657895
25 26 27 28 29 30
-7.4657895 -3.9657895 2.7342105 -0.9657895 -1.3657895 4.9342105
31 32 33 34 35 36
-15.5657895 -25.7657895 4.3342105 6.4342105 -2.3657895 3.0342105
37 38 39 40 41 42
-10.5657895 -5.7657895 6.9380952 -2.9619048 -11.2619048 8.9380952
43 44 45 46 47 48
-19.7619048 -17.8619048 3.5380952 3.3380952 -5.6619048 -1.0619048
49 50 51 52 53 54
-13.0619048 -8.7619048 7.1380952 -3.9619048 -10.7619048 19.6380952
55 56 57 58 59 60
-26.7619048 -20.8619048 6.1380952 -5.5619048 3.6380952 2.4380952
61 62 63 64 65 66
-8.9619048 -2.4619048 16.8380952 -6.8619048 8.1380952 19.0380952
67 68 69 70 71 72
-22.2619048 -15.9619048 12.9380952 16.4380952 14.8380952 6.9380952
73 74 75 76 77 78
5.4380952 1.3380952 20.1380952 3.5380952 8.7380952 23.7380952
79 80
-7.6619048 -7.3619048
> postscript(file="/var/www/html/freestat/rcomp/tmp/6xlpk1227566948.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 = 80
Frequency = 1
lag(myerror, k = 1) myerror
0 7.1342105 NA
1 10.6342105 7.1342105
2 26.3342105 10.6342105
3 0.5342105 26.3342105
4 6.8342105 0.5342105
5 15.2342105 6.8342105
6 -18.2657895 15.2342105
7 -12.5657895 -18.2657895
8 4.6342105 -12.5657895
9 8.4342105 4.6342105
10 5.4342105 8.4342105
11 -5.0657895 5.4342105
12 -7.5657895 -5.0657895
13 -3.6657895 -7.5657895
14 9.2342105 -3.6657895
15 3.8342105 9.2342105
16 2.5342105 3.8342105
17 10.5342105 2.5342105
18 -16.3657895 10.5342105
19 -16.8657895 -16.3657895
20 7.2342105 -16.8657895
21 14.1342105 7.2342105
22 2.9342105 14.1342105
23 -2.9657895 2.9342105
24 -7.4657895 -2.9657895
25 -3.9657895 -7.4657895
26 2.7342105 -3.9657895
27 -0.9657895 2.7342105
28 -1.3657895 -0.9657895
29 4.9342105 -1.3657895
30 -15.5657895 4.9342105
31 -25.7657895 -15.5657895
32 4.3342105 -25.7657895
33 6.4342105 4.3342105
34 -2.3657895 6.4342105
35 3.0342105 -2.3657895
36 -10.5657895 3.0342105
37 -5.7657895 -10.5657895
38 6.9380952 -5.7657895
39 -2.9619048 6.9380952
40 -11.2619048 -2.9619048
41 8.9380952 -11.2619048
42 -19.7619048 8.9380952
43 -17.8619048 -19.7619048
44 3.5380952 -17.8619048
45 3.3380952 3.5380952
46 -5.6619048 3.3380952
47 -1.0619048 -5.6619048
48 -13.0619048 -1.0619048
49 -8.7619048 -13.0619048
50 7.1380952 -8.7619048
51 -3.9619048 7.1380952
52 -10.7619048 -3.9619048
53 19.6380952 -10.7619048
54 -26.7619048 19.6380952
55 -20.8619048 -26.7619048
56 6.1380952 -20.8619048
57 -5.5619048 6.1380952
58 3.6380952 -5.5619048
59 2.4380952 3.6380952
60 -8.9619048 2.4380952
61 -2.4619048 -8.9619048
62 16.8380952 -2.4619048
63 -6.8619048 16.8380952
64 8.1380952 -6.8619048
65 19.0380952 8.1380952
66 -22.2619048 19.0380952
67 -15.9619048 -22.2619048
68 12.9380952 -15.9619048
69 16.4380952 12.9380952
70 14.8380952 16.4380952
71 6.9380952 14.8380952
72 5.4380952 6.9380952
73 1.3380952 5.4380952
74 20.1380952 1.3380952
75 3.5380952 20.1380952
76 8.7380952 3.5380952
77 23.7380952 8.7380952
78 -7.6619048 23.7380952
79 -7.3619048 -7.6619048
80 NA -7.3619048
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 10.6342105 7.1342105
[2,] 26.3342105 10.6342105
[3,] 0.5342105 26.3342105
[4,] 6.8342105 0.5342105
[5,] 15.2342105 6.8342105
[6,] -18.2657895 15.2342105
[7,] -12.5657895 -18.2657895
[8,] 4.6342105 -12.5657895
[9,] 8.4342105 4.6342105
[10,] 5.4342105 8.4342105
[11,] -5.0657895 5.4342105
[12,] -7.5657895 -5.0657895
[13,] -3.6657895 -7.5657895
[14,] 9.2342105 -3.6657895
[15,] 3.8342105 9.2342105
[16,] 2.5342105 3.8342105
[17,] 10.5342105 2.5342105
[18,] -16.3657895 10.5342105
[19,] -16.8657895 -16.3657895
[20,] 7.2342105 -16.8657895
[21,] 14.1342105 7.2342105
[22,] 2.9342105 14.1342105
[23,] -2.9657895 2.9342105
[24,] -7.4657895 -2.9657895
[25,] -3.9657895 -7.4657895
[26,] 2.7342105 -3.9657895
[27,] -0.9657895 2.7342105
[28,] -1.3657895 -0.9657895
[29,] 4.9342105 -1.3657895
[30,] -15.5657895 4.9342105
[31,] -25.7657895 -15.5657895
[32,] 4.3342105 -25.7657895
[33,] 6.4342105 4.3342105
[34,] -2.3657895 6.4342105
[35,] 3.0342105 -2.3657895
[36,] -10.5657895 3.0342105
[37,] -5.7657895 -10.5657895
[38,] 6.9380952 -5.7657895
[39,] -2.9619048 6.9380952
[40,] -11.2619048 -2.9619048
[41,] 8.9380952 -11.2619048
[42,] -19.7619048 8.9380952
[43,] -17.8619048 -19.7619048
[44,] 3.5380952 -17.8619048
[45,] 3.3380952 3.5380952
[46,] -5.6619048 3.3380952
[47,] -1.0619048 -5.6619048
[48,] -13.0619048 -1.0619048
[49,] -8.7619048 -13.0619048
[50,] 7.1380952 -8.7619048
[51,] -3.9619048 7.1380952
[52,] -10.7619048 -3.9619048
[53,] 19.6380952 -10.7619048
[54,] -26.7619048 19.6380952
[55,] -20.8619048 -26.7619048
[56,] 6.1380952 -20.8619048
[57,] -5.5619048 6.1380952
[58,] 3.6380952 -5.5619048
[59,] 2.4380952 3.6380952
[60,] -8.9619048 2.4380952
[61,] -2.4619048 -8.9619048
[62,] 16.8380952 -2.4619048
[63,] -6.8619048 16.8380952
[64,] 8.1380952 -6.8619048
[65,] 19.0380952 8.1380952
[66,] -22.2619048 19.0380952
[67,] -15.9619048 -22.2619048
[68,] 12.9380952 -15.9619048
[69,] 16.4380952 12.9380952
[70,] 14.8380952 16.4380952
[71,] 6.9380952 14.8380952
[72,] 5.4380952 6.9380952
[73,] 1.3380952 5.4380952
[74,] 20.1380952 1.3380952
[75,] 3.5380952 20.1380952
[76,] 8.7380952 3.5380952
[77,] 23.7380952 8.7380952
[78,] -7.6619048 23.7380952
[79,] -7.3619048 -7.6619048
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 10.6342105 7.1342105
2 26.3342105 10.6342105
3 0.5342105 26.3342105
4 6.8342105 0.5342105
5 15.2342105 6.8342105
6 -18.2657895 15.2342105
7 -12.5657895 -18.2657895
8 4.6342105 -12.5657895
9 8.4342105 4.6342105
10 5.4342105 8.4342105
11 -5.0657895 5.4342105
12 -7.5657895 -5.0657895
13 -3.6657895 -7.5657895
14 9.2342105 -3.6657895
15 3.8342105 9.2342105
16 2.5342105 3.8342105
17 10.5342105 2.5342105
18 -16.3657895 10.5342105
19 -16.8657895 -16.3657895
20 7.2342105 -16.8657895
21 14.1342105 7.2342105
22 2.9342105 14.1342105
23 -2.9657895 2.9342105
24 -7.4657895 -2.9657895
25 -3.9657895 -7.4657895
26 2.7342105 -3.9657895
27 -0.9657895 2.7342105
28 -1.3657895 -0.9657895
29 4.9342105 -1.3657895
30 -15.5657895 4.9342105
31 -25.7657895 -15.5657895
32 4.3342105 -25.7657895
33 6.4342105 4.3342105
34 -2.3657895 6.4342105
35 3.0342105 -2.3657895
36 -10.5657895 3.0342105
37 -5.7657895 -10.5657895
38 6.9380952 -5.7657895
39 -2.9619048 6.9380952
40 -11.2619048 -2.9619048
41 8.9380952 -11.2619048
42 -19.7619048 8.9380952
43 -17.8619048 -19.7619048
44 3.5380952 -17.8619048
45 3.3380952 3.5380952
46 -5.6619048 3.3380952
47 -1.0619048 -5.6619048
48 -13.0619048 -1.0619048
49 -8.7619048 -13.0619048
50 7.1380952 -8.7619048
51 -3.9619048 7.1380952
52 -10.7619048 -3.9619048
53 19.6380952 -10.7619048
54 -26.7619048 19.6380952
55 -20.8619048 -26.7619048
56 6.1380952 -20.8619048
57 -5.5619048 6.1380952
58 3.6380952 -5.5619048
59 2.4380952 3.6380952
60 -8.9619048 2.4380952
61 -2.4619048 -8.9619048
62 16.8380952 -2.4619048
63 -6.8619048 16.8380952
64 8.1380952 -6.8619048
65 19.0380952 8.1380952
66 -22.2619048 19.0380952
67 -15.9619048 -22.2619048
68 12.9380952 -15.9619048
69 16.4380952 12.9380952
70 14.8380952 16.4380952
71 6.9380952 14.8380952
72 5.4380952 6.9380952
73 1.3380952 5.4380952
74 20.1380952 1.3380952
75 3.5380952 20.1380952
76 8.7380952 3.5380952
77 23.7380952 8.7380952
78 -7.6619048 23.7380952
79 -7.3619048 -7.6619048
> 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/7kkug1227566948.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/89s7s1227566948.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/92i4b1227566948.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10cvfo1227566948.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/111l8s1227566948.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/12mjpi1227566948.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/13uanq1227566948.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/14znt61227566948.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/152zfo1227566948.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/16r3fh1227566948.tab")
+ }
>
> system("convert tmp/1ignl1227566948.ps tmp/1ignl1227566948.png")
> system("convert tmp/2kr9n1227566948.ps tmp/2kr9n1227566948.png")
> system("convert tmp/3is7f1227566948.ps tmp/3is7f1227566948.png")
> system("convert tmp/4hbfv1227566948.ps tmp/4hbfv1227566948.png")
> system("convert tmp/5y3se1227566948.ps tmp/5y3se1227566948.png")
> system("convert tmp/6xlpk1227566948.ps tmp/6xlpk1227566948.png")
> system("convert tmp/7kkug1227566948.ps tmp/7kkug1227566948.png")
> system("convert tmp/89s7s1227566948.ps tmp/89s7s1227566948.png")
> system("convert tmp/92i4b1227566948.ps tmp/92i4b1227566948.png")
> system("convert tmp/10cvfo1227566948.ps tmp/10cvfo1227566948.png")
>
>
> proc.time()
user system elapsed
3.916 2.512 4.215