R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
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(1,1,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,1,0,0,0,1,0,0,1,1,0,0,0,1,0,0,1,1,0,0,1,1,1,0,1,1,0,0,0,0,0,0,1,1,1,0,0,1,0,0,0,0,0,0,0,1,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,1,0,0,0,1,0,0,0,1,0,0,1,1,0,0,0,1,0,0,0,1,0,0,1,0,0,0,0,1,0,0,0,1,0,0,1,0,0,0,0,1,1,0,0,1,0,0,0,1,0,0,1,1,0,0,0,1,0,0,0,1,0,0,0,1,0,0,0,1,0,0,0,1,0,0,0,1,0,0,1,1,0,0,1,0,1,0,0,0,0,0,0,1,1,0,0,1,0,1,1,0,0,0,0,1,0,0,0,1,0,0,0,1,0,0,1,0,1,0,1,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,1,0,0,0,1,0,1,1,1,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0),dim=c(4,86),dimnames=list(c('Treatment4weken','treatment2weken','CorrectAnalysis4weken','CorrectAnalysis2weken'),1:86))
> y <- array(NA,dim=c(4,86),dimnames=list(c('Treatment4weken','treatment2weken','CorrectAnalysis4weken','CorrectAnalysis2weken'),1:86))
> 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 = '3'
> par3 <- 'No Linear Trend'
> par2 <- 'Do not include Seasonal Dummies'
> par1 <- '3'
> #'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, 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
CorrectAnalysis4weken Treatment4weken treatment2weken CorrectAnalysis2weken
1 0 1 1 0
2 0 0 0 0
3 0 0 1 0
4 0 0 1 0
5 0 0 1 0
6 0 0 0 0
7 0 0 1 0
8 0 1 1 0
9 0 0 0 0
10 0 0 1 0
11 0 1 0 0
12 0 0 1 0
13 0 0 1 0
14 0 1 1 0
15 0 0 1 0
16 0 1 1 0
17 1 1 1 0
18 0 1 1 0
19 0 0 0 0
20 1 1 1 0
21 0 0 1 0
22 0 0 0 0
23 0 0 1 0
24 0 0 1 0
25 0 1 0 0
26 0 0 0 0
27 0 0 1 0
28 0 0 0 0
29 0 0 1 0
30 0 0 1 0
31 0 0 1 0
32 0 0 1 0
33 0 0 1 0
34 0 1 1 0
35 0 0 1 0
36 0 0 1 0
37 0 1 0 0
38 0 0 1 0
39 0 0 1 0
40 0 1 0 0
41 1 0 1 0
42 0 0 1 0
43 0 0 1 0
44 0 1 1 0
45 0 0 1 0
46 0 0 1 0
47 0 0 1 0
48 0 0 1 0
49 0 0 1 0
50 0 0 1 0
51 0 1 1 0
52 1 1 0 0
53 0 0 0 0
54 1 0 1 0
55 0 0 1 1
56 0 1 0 0
57 0 0 1 0
58 0 0 1 0
59 0 0 1 0
60 1 1 0 0
61 0 1 0 0
62 0 0 0 0
63 0 0 1 0
64 0 1 1 0
65 0 0 1 0
66 0 0 1 1
67 1 1 1 1
68 0 0 1 0
69 0 0 0 0
70 0 0 0 0
71 0 0 0 0
72 1 0 0 0
73 0 0 0 0
74 1 1 1 0
75 0 0 0 0
76 0 0 0 1
77 0 0 0 0
78 0 1 1 0
79 0 0 0 0
80 0 0 1 0
81 0 0 1 0
82 0 0 1 0
83 0 0 0 0
84 0 0 1 0
85 0 1 1 0
86 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Treatment4weken treatment2weken
0.0404475 0.2138858 -0.0004033
CorrectAnalysis2weken
0.1563835
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.25433 -0.04045 -0.04004 -0.04004 0.95996
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.0404475 0.0599346 0.675 0.502
Treatment4weken 0.2138858 0.0722149 2.962 0.004 **
treatment2weken -0.0004033 0.0682538 -0.006 0.995
CorrectAnalysis2weken 0.1563835 0.1518171 1.030 0.306
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.2963 on 82 degrees of freedom
Multiple R-squared: 0.1067, Adjusted R-squared: 0.07397
F-statistic: 3.263 on 3 and 82 DF, p-value: 0.02551
> 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,] 0.000000000 0.000000000 1.0000000
[2,] 0.000000000 0.000000000 1.0000000
[3,] 0.000000000 0.000000000 1.0000000
[4,] 0.000000000 0.000000000 1.0000000
[5,] 0.000000000 0.000000000 1.0000000
[6,] 0.000000000 0.000000000 1.0000000
[7,] 0.000000000 0.000000000 1.0000000
[8,] 0.000000000 0.000000000 1.0000000
[9,] 0.000000000 0.000000000 1.0000000
[10,] 0.000000000 0.000000000 1.0000000
[11,] 0.202811894 0.405623788 0.7971881
[12,] 0.167914291 0.335828583 0.8320857
[13,] 0.118768491 0.237536981 0.8812315
[14,] 0.544145039 0.911709922 0.4558550
[15,] 0.465156637 0.930313274 0.5348434
[16,] 0.389938375 0.779876749 0.6100616
[17,] 0.318463080 0.636926160 0.6815369
[18,] 0.253974591 0.507949183 0.7460254
[19,] 0.222888374 0.445776748 0.7771116
[20,] 0.173393612 0.346787224 0.8266064
[21,] 0.130688904 0.261377809 0.8693111
[22,] 0.097060798 0.194121596 0.9029392
[23,] 0.069806112 0.139612224 0.9301939
[24,] 0.049013784 0.098027568 0.9509862
[25,] 0.033600592 0.067201185 0.9663994
[26,] 0.022491541 0.044983082 0.9775085
[27,] 0.014702227 0.029404454 0.9852978
[28,] 0.013043574 0.026087148 0.9869564
[29,] 0.008305758 0.016611516 0.9916942
[30,] 0.005167928 0.010335856 0.9948321
[31,] 0.004057163 0.008114325 0.9959428
[32,] 0.002443815 0.004887630 0.9975562
[33,] 0.001438675 0.002877351 0.9985613
[34,] 0.001127483 0.002254967 0.9988725
[35,] 0.094625934 0.189251868 0.9053741
[36,] 0.070604357 0.141208714 0.9293956
[37,] 0.051562581 0.103125161 0.9484374
[38,] 0.048106066 0.096212133 0.9518939
[39,] 0.034229298 0.068458596 0.9657707
[40,] 0.023818626 0.047637251 0.9761814
[41,] 0.016203062 0.032406124 0.9837969
[42,] 0.010771688 0.021543377 0.9892283
[43,] 0.006995592 0.013991183 0.9930044
[44,] 0.004436805 0.008873611 0.9955632
[45,] 0.004279622 0.008559244 0.9957204
[46,] 0.041464183 0.082928365 0.9585358
[47,] 0.029077495 0.058154991 0.9709225
[48,] 0.337154340 0.674308680 0.6628457
[49,] 0.289352761 0.578705521 0.7106472
[50,] 0.308674474 0.617348949 0.6913255
[51,] 0.252240000 0.504480000 0.7477600
[52,] 0.201434957 0.402869914 0.7985650
[53,] 0.157014586 0.314029173 0.8429854
[54,] 0.368312577 0.736625154 0.6316874
[55,] 0.384079219 0.768158438 0.6159208
[56,] 0.319056062 0.638112123 0.6809439
[57,] 0.256863251 0.513726503 0.7431367
[58,] 0.281008376 0.562016751 0.7189916
[59,] 0.220938677 0.441877354 0.7790613
[60,] 0.180393783 0.360787566 0.8196062
[61,] 0.299390656 0.598781312 0.7006093
[62,] 0.232437053 0.464874106 0.7675629
[63,] 0.178201868 0.356403736 0.8217981
[64,] 0.132665712 0.265331424 0.8673343
[65,] 0.096034393 0.192068787 0.9039656
[66,] 0.715794538 0.568410923 0.2842055
[67,] 0.621763662 0.756472675 0.3782363
[68,] 1.000000000 0.000000000 0.0000000
[69,] 1.000000000 0.000000000 0.0000000
[70,] 1.000000000 0.000000000 0.0000000
[71,] 1.000000000 0.000000000 0.0000000
[72,] 1.000000000 0.000000000 0.0000000
[73,] 1.000000000 0.000000000 0.0000000
> postscript(file="/var/wessaorg/rcomp/tmp/1v49m1356094300.ps",horizontal=F,onefile=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2g9ud1356094300.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3baod1356094300.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/49x3g1356094300.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5ecrp1356094300.ps",horizontal=F,onefile=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 = 86
Frequency = 1
1 2 3 4 5 6
-0.25392999 -0.04044750 -0.04004417 -0.04004417 -0.04004417 -0.04044750
7 8 9 10 11 12
-0.04004417 -0.25392999 -0.04044750 -0.04004417 -0.25433332 -0.04004417
13 14 15 16 17 18
-0.04004417 -0.25392999 -0.04004417 -0.25392999 0.74607001 -0.25392999
19 20 21 22 23 24
-0.04044750 0.74607001 -0.04004417 -0.04044750 -0.04004417 -0.04004417
25 26 27 28 29 30
-0.25433332 -0.04044750 -0.04004417 -0.04044750 -0.04004417 -0.04004417
31 32 33 34 35 36
-0.04004417 -0.04004417 -0.04004417 -0.25392999 -0.04004417 -0.04004417
37 38 39 40 41 42
-0.25433332 -0.04004417 -0.04004417 -0.25433332 0.95995583 -0.04004417
43 44 45 46 47 48
-0.04004417 -0.25392999 -0.04004417 -0.04004417 -0.04004417 -0.04004417
49 50 51 52 53 54
-0.04004417 -0.04004417 -0.25392999 0.74566668 -0.04044750 0.95995583
55 56 57 58 59 60
-0.19642771 -0.25433332 -0.04004417 -0.04004417 -0.04004417 0.74566668
61 62 63 64 65 66
-0.25433332 -0.04044750 -0.04004417 -0.25392999 -0.04004417 -0.19642771
67 68 69 70 71 72
0.58968646 -0.04004417 -0.04044750 -0.04044750 -0.04044750 0.95955250
73 74 75 76 77 78
-0.04044750 0.74607001 -0.04044750 -0.19683104 -0.04044750 -0.25392999
79 80 81 82 83 84
-0.04044750 -0.04004417 -0.04004417 -0.04004417 -0.04044750 -0.04004417
85 86
-0.25392999 -0.04044750
> postscript(file="/var/wessaorg/rcomp/tmp/6g3q81356094300.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 86
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.25392999 NA
1 -0.04044750 -0.25392999
2 -0.04004417 -0.04044750
3 -0.04004417 -0.04004417
4 -0.04004417 -0.04004417
5 -0.04044750 -0.04004417
6 -0.04004417 -0.04044750
7 -0.25392999 -0.04004417
8 -0.04044750 -0.25392999
9 -0.04004417 -0.04044750
10 -0.25433332 -0.04004417
11 -0.04004417 -0.25433332
12 -0.04004417 -0.04004417
13 -0.25392999 -0.04004417
14 -0.04004417 -0.25392999
15 -0.25392999 -0.04004417
16 0.74607001 -0.25392999
17 -0.25392999 0.74607001
18 -0.04044750 -0.25392999
19 0.74607001 -0.04044750
20 -0.04004417 0.74607001
21 -0.04044750 -0.04004417
22 -0.04004417 -0.04044750
23 -0.04004417 -0.04004417
24 -0.25433332 -0.04004417
25 -0.04044750 -0.25433332
26 -0.04004417 -0.04044750
27 -0.04044750 -0.04004417
28 -0.04004417 -0.04044750
29 -0.04004417 -0.04004417
30 -0.04004417 -0.04004417
31 -0.04004417 -0.04004417
32 -0.04004417 -0.04004417
33 -0.25392999 -0.04004417
34 -0.04004417 -0.25392999
35 -0.04004417 -0.04004417
36 -0.25433332 -0.04004417
37 -0.04004417 -0.25433332
38 -0.04004417 -0.04004417
39 -0.25433332 -0.04004417
40 0.95995583 -0.25433332
41 -0.04004417 0.95995583
42 -0.04004417 -0.04004417
43 -0.25392999 -0.04004417
44 -0.04004417 -0.25392999
45 -0.04004417 -0.04004417
46 -0.04004417 -0.04004417
47 -0.04004417 -0.04004417
48 -0.04004417 -0.04004417
49 -0.04004417 -0.04004417
50 -0.25392999 -0.04004417
51 0.74566668 -0.25392999
52 -0.04044750 0.74566668
53 0.95995583 -0.04044750
54 -0.19642771 0.95995583
55 -0.25433332 -0.19642771
56 -0.04004417 -0.25433332
57 -0.04004417 -0.04004417
58 -0.04004417 -0.04004417
59 0.74566668 -0.04004417
60 -0.25433332 0.74566668
61 -0.04044750 -0.25433332
62 -0.04004417 -0.04044750
63 -0.25392999 -0.04004417
64 -0.04004417 -0.25392999
65 -0.19642771 -0.04004417
66 0.58968646 -0.19642771
67 -0.04004417 0.58968646
68 -0.04044750 -0.04004417
69 -0.04044750 -0.04044750
70 -0.04044750 -0.04044750
71 0.95955250 -0.04044750
72 -0.04044750 0.95955250
73 0.74607001 -0.04044750
74 -0.04044750 0.74607001
75 -0.19683104 -0.04044750
76 -0.04044750 -0.19683104
77 -0.25392999 -0.04044750
78 -0.04044750 -0.25392999
79 -0.04004417 -0.04044750
80 -0.04004417 -0.04004417
81 -0.04004417 -0.04004417
82 -0.04044750 -0.04004417
83 -0.04004417 -0.04044750
84 -0.25392999 -0.04004417
85 -0.04044750 -0.25392999
86 NA -0.04044750
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.04044750 -0.25392999
[2,] -0.04004417 -0.04044750
[3,] -0.04004417 -0.04004417
[4,] -0.04004417 -0.04004417
[5,] -0.04044750 -0.04004417
[6,] -0.04004417 -0.04044750
[7,] -0.25392999 -0.04004417
[8,] -0.04044750 -0.25392999
[9,] -0.04004417 -0.04044750
[10,] -0.25433332 -0.04004417
[11,] -0.04004417 -0.25433332
[12,] -0.04004417 -0.04004417
[13,] -0.25392999 -0.04004417
[14,] -0.04004417 -0.25392999
[15,] -0.25392999 -0.04004417
[16,] 0.74607001 -0.25392999
[17,] -0.25392999 0.74607001
[18,] -0.04044750 -0.25392999
[19,] 0.74607001 -0.04044750
[20,] -0.04004417 0.74607001
[21,] -0.04044750 -0.04004417
[22,] -0.04004417 -0.04044750
[23,] -0.04004417 -0.04004417
[24,] -0.25433332 -0.04004417
[25,] -0.04044750 -0.25433332
[26,] -0.04004417 -0.04044750
[27,] -0.04044750 -0.04004417
[28,] -0.04004417 -0.04044750
[29,] -0.04004417 -0.04004417
[30,] -0.04004417 -0.04004417
[31,] -0.04004417 -0.04004417
[32,] -0.04004417 -0.04004417
[33,] -0.25392999 -0.04004417
[34,] -0.04004417 -0.25392999
[35,] -0.04004417 -0.04004417
[36,] -0.25433332 -0.04004417
[37,] -0.04004417 -0.25433332
[38,] -0.04004417 -0.04004417
[39,] -0.25433332 -0.04004417
[40,] 0.95995583 -0.25433332
[41,] -0.04004417 0.95995583
[42,] -0.04004417 -0.04004417
[43,] -0.25392999 -0.04004417
[44,] -0.04004417 -0.25392999
[45,] -0.04004417 -0.04004417
[46,] -0.04004417 -0.04004417
[47,] -0.04004417 -0.04004417
[48,] -0.04004417 -0.04004417
[49,] -0.04004417 -0.04004417
[50,] -0.25392999 -0.04004417
[51,] 0.74566668 -0.25392999
[52,] -0.04044750 0.74566668
[53,] 0.95995583 -0.04044750
[54,] -0.19642771 0.95995583
[55,] -0.25433332 -0.19642771
[56,] -0.04004417 -0.25433332
[57,] -0.04004417 -0.04004417
[58,] -0.04004417 -0.04004417
[59,] 0.74566668 -0.04004417
[60,] -0.25433332 0.74566668
[61,] -0.04044750 -0.25433332
[62,] -0.04004417 -0.04044750
[63,] -0.25392999 -0.04004417
[64,] -0.04004417 -0.25392999
[65,] -0.19642771 -0.04004417
[66,] 0.58968646 -0.19642771
[67,] -0.04004417 0.58968646
[68,] -0.04044750 -0.04004417
[69,] -0.04044750 -0.04044750
[70,] -0.04044750 -0.04044750
[71,] 0.95955250 -0.04044750
[72,] -0.04044750 0.95955250
[73,] 0.74607001 -0.04044750
[74,] -0.04044750 0.74607001
[75,] -0.19683104 -0.04044750
[76,] -0.04044750 -0.19683104
[77,] -0.25392999 -0.04044750
[78,] -0.04044750 -0.25392999
[79,] -0.04004417 -0.04044750
[80,] -0.04004417 -0.04004417
[81,] -0.04004417 -0.04004417
[82,] -0.04044750 -0.04004417
[83,] -0.04004417 -0.04044750
[84,] -0.25392999 -0.04004417
[85,] -0.04044750 -0.25392999
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.04044750 -0.25392999
2 -0.04004417 -0.04044750
3 -0.04004417 -0.04004417
4 -0.04004417 -0.04004417
5 -0.04044750 -0.04004417
6 -0.04004417 -0.04044750
7 -0.25392999 -0.04004417
8 -0.04044750 -0.25392999
9 -0.04004417 -0.04044750
10 -0.25433332 -0.04004417
11 -0.04004417 -0.25433332
12 -0.04004417 -0.04004417
13 -0.25392999 -0.04004417
14 -0.04004417 -0.25392999
15 -0.25392999 -0.04004417
16 0.74607001 -0.25392999
17 -0.25392999 0.74607001
18 -0.04044750 -0.25392999
19 0.74607001 -0.04044750
20 -0.04004417 0.74607001
21 -0.04044750 -0.04004417
22 -0.04004417 -0.04044750
23 -0.04004417 -0.04004417
24 -0.25433332 -0.04004417
25 -0.04044750 -0.25433332
26 -0.04004417 -0.04044750
27 -0.04044750 -0.04004417
28 -0.04004417 -0.04044750
29 -0.04004417 -0.04004417
30 -0.04004417 -0.04004417
31 -0.04004417 -0.04004417
32 -0.04004417 -0.04004417
33 -0.25392999 -0.04004417
34 -0.04004417 -0.25392999
35 -0.04004417 -0.04004417
36 -0.25433332 -0.04004417
37 -0.04004417 -0.25433332
38 -0.04004417 -0.04004417
39 -0.25433332 -0.04004417
40 0.95995583 -0.25433332
41 -0.04004417 0.95995583
42 -0.04004417 -0.04004417
43 -0.25392999 -0.04004417
44 -0.04004417 -0.25392999
45 -0.04004417 -0.04004417
46 -0.04004417 -0.04004417
47 -0.04004417 -0.04004417
48 -0.04004417 -0.04004417
49 -0.04004417 -0.04004417
50 -0.25392999 -0.04004417
51 0.74566668 -0.25392999
52 -0.04044750 0.74566668
53 0.95995583 -0.04044750
54 -0.19642771 0.95995583
55 -0.25433332 -0.19642771
56 -0.04004417 -0.25433332
57 -0.04004417 -0.04004417
58 -0.04004417 -0.04004417
59 0.74566668 -0.04004417
60 -0.25433332 0.74566668
61 -0.04044750 -0.25433332
62 -0.04004417 -0.04044750
63 -0.25392999 -0.04004417
64 -0.04004417 -0.25392999
65 -0.19642771 -0.04004417
66 0.58968646 -0.19642771
67 -0.04004417 0.58968646
68 -0.04044750 -0.04004417
69 -0.04044750 -0.04044750
70 -0.04044750 -0.04044750
71 0.95955250 -0.04044750
72 -0.04044750 0.95955250
73 0.74607001 -0.04044750
74 -0.04044750 0.74607001
75 -0.19683104 -0.04044750
76 -0.04044750 -0.19683104
77 -0.25392999 -0.04044750
78 -0.04044750 -0.25392999
79 -0.04004417 -0.04044750
80 -0.04004417 -0.04004417
81 -0.04004417 -0.04004417
82 -0.04044750 -0.04004417
83 -0.04004417 -0.04044750
84 -0.25392999 -0.04004417
85 -0.04044750 -0.25392999
> 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/wessaorg/rcomp/tmp/7fyh71356094300.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/85wex1356094300.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9f73t1356094300.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10q5ka1356094300.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/wessaorg/rcomp/tmp/11q6241356094300.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/wessaorg/rcomp/tmp/12gnns1356094300.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/wessaorg/rcomp/tmp/13umdq1356094300.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/wessaorg/rcomp/tmp/14kuyv1356094300.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/wessaorg/rcomp/tmp/1504hc1356094300.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/wessaorg/rcomp/tmp/16m91i1356094300.tab")
+ }
>
> try(system("convert tmp/1v49m1356094300.ps tmp/1v49m1356094300.png",intern=TRUE))
character(0)
> try(system("convert tmp/2g9ud1356094300.ps tmp/2g9ud1356094300.png",intern=TRUE))
character(0)
> try(system("convert tmp/3baod1356094300.ps tmp/3baod1356094300.png",intern=TRUE))
character(0)
> try(system("convert tmp/49x3g1356094300.ps tmp/49x3g1356094300.png",intern=TRUE))
character(0)
> try(system("convert tmp/5ecrp1356094300.ps tmp/5ecrp1356094300.png",intern=TRUE))
character(0)
> try(system("convert tmp/6g3q81356094300.ps tmp/6g3q81356094300.png",intern=TRUE))
character(0)
> try(system("convert tmp/7fyh71356094300.ps tmp/7fyh71356094300.png",intern=TRUE))
character(0)
> try(system("convert tmp/85wex1356094300.ps tmp/85wex1356094300.png",intern=TRUE))
character(0)
> try(system("convert tmp/9f73t1356094300.ps tmp/9f73t1356094300.png",intern=TRUE))
character(0)
> try(system("convert tmp/10q5ka1356094300.ps tmp/10q5ka1356094300.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
6.585 1.190 8.910