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(0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,1,1,0,0,0,0,0,0,0,1,0,1,0,1,0,0,0,0,0,0,0,0,1,0,1,0,0),dim=c(2,68),dimnames=list(c('T20','CorrectAnalysis
'),1:68))
> y <- array(NA,dim=c(2,68),dimnames=list(c('T20','CorrectAnalysis
'),1:68))
> 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 = 'Do not include Seasonal Dummies'
> par1 = '2'
> par3 <- 'Linear Trend'
> par2 <- 'Do not include Seasonal Dummies'
> par1 <- '2'
> #'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
CorrectAnalysis\r T20 t
1 0 0 1
2 0 1 2
3 0 0 3
4 0 0 4
5 0 0 5
6 0 1 6
7 0 0 7
8 0 0 8
9 0 1 9
10 0 0 10
11 0 1 11
12 0 0 12
13 0 0 13
14 0 0 14
15 0 0 15
16 0 0 16
17 0 0 17
18 0 0 18
19 0 1 19
20 0 0 20
21 0 0 21
22 0 1 22
23 0 0 23
24 0 0 24
25 0 1 25
26 0 1 26
27 0 0 27
28 0 1 28
29 0 0 29
30 0 0 30
31 0 0 31
32 0 0 32
33 0 0 33
34 0 0 34
35 0 0 35
36 0 0 36
37 0 1 37
38 0 0 38
39 0 0 39
40 0 1 40
41 0 0 41
42 0 0 42
43 0 0 43
44 0 0 44
45 0 0 45
46 0 0 46
47 0 0 47
48 0 0 48
49 0 0 49
50 0 0 50
51 0 0 51
52 0 1 52
53 0 1 53
54 0 0 54
55 1 0 55
56 0 1 56
57 0 0 57
58 0 0 58
59 0 0 59
60 0 1 60
61 0 1 61
62 0 1 62
63 0 0 63
64 0 0 64
65 0 0 65
66 1 0 66
67 1 0 67
68 0 0 68
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) T20 t
-0.052298 -0.054446 0.003189
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.16457 -0.08785 -0.04178 0.02126 0.87689
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.052298 0.050955 -1.026 0.3085
T20 -0.054446 0.055575 -0.980 0.3309
t 0.003189 0.001226 2.601 0.0115 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.1984 on 65 degrees of freedom
Multiple R-squared: 0.1082, Adjusted R-squared: 0.08078
F-statistic: 3.944 on 2 and 65 DF, p-value: 0.02418
> 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,] 0.000000e+00 0.000000e+00 1.0000000
[2,] 0.000000e+00 0.000000e+00 1.0000000
[3,] 0.000000e+00 0.000000e+00 1.0000000
[4,] 0.000000e+00 0.000000e+00 1.0000000
[5,] 0.000000e+00 0.000000e+00 1.0000000
[6,] 0.000000e+00 0.000000e+00 1.0000000
[7,] 0.000000e+00 0.000000e+00 1.0000000
[8,] 0.000000e+00 0.000000e+00 1.0000000
[9,] 0.000000e+00 0.000000e+00 1.0000000
[10,] 0.000000e+00 0.000000e+00 1.0000000
[11,] 0.000000e+00 0.000000e+00 1.0000000
[12,] 0.000000e+00 0.000000e+00 1.0000000
[13,] 0.000000e+00 0.000000e+00 1.0000000
[14,] 0.000000e+00 0.000000e+00 1.0000000
[15,] 0.000000e+00 0.000000e+00 1.0000000
[16,] 0.000000e+00 0.000000e+00 1.0000000
[17,] 0.000000e+00 0.000000e+00 1.0000000
[18,] 0.000000e+00 0.000000e+00 1.0000000
[19,] 0.000000e+00 0.000000e+00 1.0000000
[20,] 0.000000e+00 0.000000e+00 1.0000000
[21,] 0.000000e+00 0.000000e+00 1.0000000
[22,] 0.000000e+00 0.000000e+00 1.0000000
[23,] 0.000000e+00 0.000000e+00 1.0000000
[24,] 0.000000e+00 0.000000e+00 1.0000000
[25,] 0.000000e+00 0.000000e+00 1.0000000
[26,] 0.000000e+00 0.000000e+00 1.0000000
[27,] 0.000000e+00 0.000000e+00 1.0000000
[28,] 0.000000e+00 0.000000e+00 1.0000000
[29,] 0.000000e+00 0.000000e+00 1.0000000
[30,] 0.000000e+00 0.000000e+00 1.0000000
[31,] 0.000000e+00 0.000000e+00 1.0000000
[32,] 0.000000e+00 0.000000e+00 1.0000000
[33,] 0.000000e+00 0.000000e+00 1.0000000
[34,] 0.000000e+00 0.000000e+00 1.0000000
[35,] 0.000000e+00 0.000000e+00 1.0000000
[36,] 0.000000e+00 0.000000e+00 1.0000000
[37,] 0.000000e+00 0.000000e+00 1.0000000
[38,] 0.000000e+00 0.000000e+00 1.0000000
[39,] 0.000000e+00 0.000000e+00 1.0000000
[40,] 0.000000e+00 0.000000e+00 1.0000000
[41,] 0.000000e+00 0.000000e+00 1.0000000
[42,] 0.000000e+00 0.000000e+00 1.0000000
[43,] 0.000000e+00 0.000000e+00 1.0000000
[44,] 0.000000e+00 0.000000e+00 1.0000000
[45,] 0.000000e+00 0.000000e+00 1.0000000
[46,] 0.000000e+00 0.000000e+00 1.0000000
[47,] 0.000000e+00 0.000000e+00 1.0000000
[48,] 0.000000e+00 0.000000e+00 1.0000000
[49,] 0.000000e+00 0.000000e+00 1.0000000
[50,] 8.891194e-07 1.778239e-06 0.9999991
[51,] 5.220517e-07 1.044103e-06 0.9999995
[52,] 2.128343e-07 4.256687e-07 0.9999998
[53,] 8.230736e-08 1.646147e-07 0.9999999
[54,] 3.709017e-08 7.418034e-08 1.0000000
[55,] 1.210210e-08 2.420419e-08 1.0000000
[56,] 3.024947e-09 6.049894e-09 1.0000000
[57,] 5.839941e-10 1.167988e-09 1.0000000
> postscript(file="/var/wessaorg/rcomp/tmp/1vjgu1356023875.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2cb5o1356023875.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3n5i61356023875.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/4mdib1356023875.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5hsmh1356023875.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 = 68
Frequency = 1
1 2 3 4 5 6
0.049108641 0.100365662 0.042730262 0.039541073 0.036351884 0.087608905
7 8 9 10 11 12
0.029973505 0.026784316 0.078041337 0.020405937 0.071662959 0.014027559
13 14 15 16 17 18
0.010838370 0.007649180 0.004459991 0.001270802 -0.001918388 -0.005107577
19 20 21 22 23 24
0.046149445 -0.011485955 -0.014675145 0.036581877 -0.021053523 -0.024242712
25 26 27 28 29 30
0.027014309 0.023825120 -0.033810280 0.017446741 -0.040188659 -0.043377848
31 32 33 34 35 36
-0.046567037 -0.049756227 -0.052945416 -0.056134605 -0.059323794 -0.062512984
37 38 39 40 41 42
-0.011255962 -0.068891362 -0.072080551 -0.020823530 -0.078458930 -0.081648119
43 44 45 46 47 48
-0.084837309 -0.088026498 -0.091215687 -0.094404876 -0.097594066 -0.100783255
49 50 51 52 53 54
-0.103972444 -0.107161633 -0.110350823 -0.059093801 -0.062282990 -0.119918391
55 56 57 58 59 60
0.876892420 -0.071850558 -0.129485958 -0.132675148 -0.135864337 -0.084607315
61 62 63 64 65 66
-0.087796505 -0.090985694 -0.148621094 -0.151810283 -0.154999473 0.841811338
67 68
0.838622149 -0.164567040
> postscript(file="/var/wessaorg/rcomp/tmp/6um521356023875.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 = 68
Frequency = 1
lag(myerror, k = 1) myerror
0 0.049108641 NA
1 0.100365662 0.049108641
2 0.042730262 0.100365662
3 0.039541073 0.042730262
4 0.036351884 0.039541073
5 0.087608905 0.036351884
6 0.029973505 0.087608905
7 0.026784316 0.029973505
8 0.078041337 0.026784316
9 0.020405937 0.078041337
10 0.071662959 0.020405937
11 0.014027559 0.071662959
12 0.010838370 0.014027559
13 0.007649180 0.010838370
14 0.004459991 0.007649180
15 0.001270802 0.004459991
16 -0.001918388 0.001270802
17 -0.005107577 -0.001918388
18 0.046149445 -0.005107577
19 -0.011485955 0.046149445
20 -0.014675145 -0.011485955
21 0.036581877 -0.014675145
22 -0.021053523 0.036581877
23 -0.024242712 -0.021053523
24 0.027014309 -0.024242712
25 0.023825120 0.027014309
26 -0.033810280 0.023825120
27 0.017446741 -0.033810280
28 -0.040188659 0.017446741
29 -0.043377848 -0.040188659
30 -0.046567037 -0.043377848
31 -0.049756227 -0.046567037
32 -0.052945416 -0.049756227
33 -0.056134605 -0.052945416
34 -0.059323794 -0.056134605
35 -0.062512984 -0.059323794
36 -0.011255962 -0.062512984
37 -0.068891362 -0.011255962
38 -0.072080551 -0.068891362
39 -0.020823530 -0.072080551
40 -0.078458930 -0.020823530
41 -0.081648119 -0.078458930
42 -0.084837309 -0.081648119
43 -0.088026498 -0.084837309
44 -0.091215687 -0.088026498
45 -0.094404876 -0.091215687
46 -0.097594066 -0.094404876
47 -0.100783255 -0.097594066
48 -0.103972444 -0.100783255
49 -0.107161633 -0.103972444
50 -0.110350823 -0.107161633
51 -0.059093801 -0.110350823
52 -0.062282990 -0.059093801
53 -0.119918391 -0.062282990
54 0.876892420 -0.119918391
55 -0.071850558 0.876892420
56 -0.129485958 -0.071850558
57 -0.132675148 -0.129485958
58 -0.135864337 -0.132675148
59 -0.084607315 -0.135864337
60 -0.087796505 -0.084607315
61 -0.090985694 -0.087796505
62 -0.148621094 -0.090985694
63 -0.151810283 -0.148621094
64 -0.154999473 -0.151810283
65 0.841811338 -0.154999473
66 0.838622149 0.841811338
67 -0.164567040 0.838622149
68 NA -0.164567040
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.100365662 0.049108641
[2,] 0.042730262 0.100365662
[3,] 0.039541073 0.042730262
[4,] 0.036351884 0.039541073
[5,] 0.087608905 0.036351884
[6,] 0.029973505 0.087608905
[7,] 0.026784316 0.029973505
[8,] 0.078041337 0.026784316
[9,] 0.020405937 0.078041337
[10,] 0.071662959 0.020405937
[11,] 0.014027559 0.071662959
[12,] 0.010838370 0.014027559
[13,] 0.007649180 0.010838370
[14,] 0.004459991 0.007649180
[15,] 0.001270802 0.004459991
[16,] -0.001918388 0.001270802
[17,] -0.005107577 -0.001918388
[18,] 0.046149445 -0.005107577
[19,] -0.011485955 0.046149445
[20,] -0.014675145 -0.011485955
[21,] 0.036581877 -0.014675145
[22,] -0.021053523 0.036581877
[23,] -0.024242712 -0.021053523
[24,] 0.027014309 -0.024242712
[25,] 0.023825120 0.027014309
[26,] -0.033810280 0.023825120
[27,] 0.017446741 -0.033810280
[28,] -0.040188659 0.017446741
[29,] -0.043377848 -0.040188659
[30,] -0.046567037 -0.043377848
[31,] -0.049756227 -0.046567037
[32,] -0.052945416 -0.049756227
[33,] -0.056134605 -0.052945416
[34,] -0.059323794 -0.056134605
[35,] -0.062512984 -0.059323794
[36,] -0.011255962 -0.062512984
[37,] -0.068891362 -0.011255962
[38,] -0.072080551 -0.068891362
[39,] -0.020823530 -0.072080551
[40,] -0.078458930 -0.020823530
[41,] -0.081648119 -0.078458930
[42,] -0.084837309 -0.081648119
[43,] -0.088026498 -0.084837309
[44,] -0.091215687 -0.088026498
[45,] -0.094404876 -0.091215687
[46,] -0.097594066 -0.094404876
[47,] -0.100783255 -0.097594066
[48,] -0.103972444 -0.100783255
[49,] -0.107161633 -0.103972444
[50,] -0.110350823 -0.107161633
[51,] -0.059093801 -0.110350823
[52,] -0.062282990 -0.059093801
[53,] -0.119918391 -0.062282990
[54,] 0.876892420 -0.119918391
[55,] -0.071850558 0.876892420
[56,] -0.129485958 -0.071850558
[57,] -0.132675148 -0.129485958
[58,] -0.135864337 -0.132675148
[59,] -0.084607315 -0.135864337
[60,] -0.087796505 -0.084607315
[61,] -0.090985694 -0.087796505
[62,] -0.148621094 -0.090985694
[63,] -0.151810283 -0.148621094
[64,] -0.154999473 -0.151810283
[65,] 0.841811338 -0.154999473
[66,] 0.838622149 0.841811338
[67,] -0.164567040 0.838622149
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.100365662 0.049108641
2 0.042730262 0.100365662
3 0.039541073 0.042730262
4 0.036351884 0.039541073
5 0.087608905 0.036351884
6 0.029973505 0.087608905
7 0.026784316 0.029973505
8 0.078041337 0.026784316
9 0.020405937 0.078041337
10 0.071662959 0.020405937
11 0.014027559 0.071662959
12 0.010838370 0.014027559
13 0.007649180 0.010838370
14 0.004459991 0.007649180
15 0.001270802 0.004459991
16 -0.001918388 0.001270802
17 -0.005107577 -0.001918388
18 0.046149445 -0.005107577
19 -0.011485955 0.046149445
20 -0.014675145 -0.011485955
21 0.036581877 -0.014675145
22 -0.021053523 0.036581877
23 -0.024242712 -0.021053523
24 0.027014309 -0.024242712
25 0.023825120 0.027014309
26 -0.033810280 0.023825120
27 0.017446741 -0.033810280
28 -0.040188659 0.017446741
29 -0.043377848 -0.040188659
30 -0.046567037 -0.043377848
31 -0.049756227 -0.046567037
32 -0.052945416 -0.049756227
33 -0.056134605 -0.052945416
34 -0.059323794 -0.056134605
35 -0.062512984 -0.059323794
36 -0.011255962 -0.062512984
37 -0.068891362 -0.011255962
38 -0.072080551 -0.068891362
39 -0.020823530 -0.072080551
40 -0.078458930 -0.020823530
41 -0.081648119 -0.078458930
42 -0.084837309 -0.081648119
43 -0.088026498 -0.084837309
44 -0.091215687 -0.088026498
45 -0.094404876 -0.091215687
46 -0.097594066 -0.094404876
47 -0.100783255 -0.097594066
48 -0.103972444 -0.100783255
49 -0.107161633 -0.103972444
50 -0.110350823 -0.107161633
51 -0.059093801 -0.110350823
52 -0.062282990 -0.059093801
53 -0.119918391 -0.062282990
54 0.876892420 -0.119918391
55 -0.071850558 0.876892420
56 -0.129485958 -0.071850558
57 -0.132675148 -0.129485958
58 -0.135864337 -0.132675148
59 -0.084607315 -0.135864337
60 -0.087796505 -0.084607315
61 -0.090985694 -0.087796505
62 -0.148621094 -0.090985694
63 -0.151810283 -0.148621094
64 -0.154999473 -0.151810283
65 0.841811338 -0.154999473
66 0.838622149 0.841811338
67 -0.164567040 0.838622149
> 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/7ahny1356023875.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8pk7e1356023875.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/92bj21356023875.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10sjbj1356023875.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/114gtc1356023875.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/12590i1356023875.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/13bbcf1356023875.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/142ukp1356023875.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/157jad1356023875.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/16pujk1356023875.tab")
+ }
>
> try(system("convert tmp/1vjgu1356023875.ps tmp/1vjgu1356023875.png",intern=TRUE))
character(0)
> try(system("convert tmp/2cb5o1356023875.ps tmp/2cb5o1356023875.png",intern=TRUE))
character(0)
> try(system("convert tmp/3n5i61356023875.ps tmp/3n5i61356023875.png",intern=TRUE))
character(0)
> try(system("convert tmp/4mdib1356023875.ps tmp/4mdib1356023875.png",intern=TRUE))
character(0)
> try(system("convert tmp/5hsmh1356023875.ps tmp/5hsmh1356023875.png",intern=TRUE))
character(0)
> try(system("convert tmp/6um521356023875.ps tmp/6um521356023875.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ahny1356023875.ps tmp/7ahny1356023875.png",intern=TRUE))
character(0)
> try(system("convert tmp/8pk7e1356023875.ps tmp/8pk7e1356023875.png",intern=TRUE))
character(0)
> try(system("convert tmp/92bj21356023875.ps tmp/92bj21356023875.png",intern=TRUE))
character(0)
> try(system("convert tmp/10sjbj1356023875.ps tmp/10sjbj1356023875.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
6.540 1.278 8.213