R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(-3.3,0,-3.5,0,-3.5,0,-8.4,0,-15.7,0,-18.7,0,-22.8,0,-20.7,0,-14,0,-6.3,0,0.7,0,0.2,0,0.8,0,1.2,0,4.5,0,0.4,0,5.9,0,6.5,0,12.8,0,4.2,0,-3.3,0,-12.5,0,-16.3,0,-10.5,0,-11.8,0,-11.4,0,-17.7,0,-17.3,0,-18.6,0,-17.9,0,-21.4,0,-19.4,0,-15.5,0,-7.7,0,-0.7,0,-1.6,0,1.4,0,0.7,0,9.5,0,1.4,0,4.1,0,6.6,0,18.4,0,16.9,0,9.2,0,-4.3,0,-5.9,0,-7.7,0,-5.4,0,-2.3,0,-4.8,0,2.3,0,-5.2,0,-10,0,-17.1,0,-14.4,0,-3.9,0,3.7,0,6.5,0,0.9,0,-4.1,0,-7,0,-12.2,0,-2.5,0,4.4,0,13.7,0,12.3,0,13.4,0,2.2,0,1.7,0,-7.2,0,-4.8,0,-2.9,0,-2.4,0,-2.5,0,-5.3,0,-7.1,0,-8,0,-8.9,1,-7.7,1,-1.1,1,4,1,9.6,1,10.9,1,13,1,14.9,1,20.1,1,10.8,1,11,1,3.8,1,10.8,1,7.6,1,10.2,1,2.2,1,-0.1,1,-1.7,1,-4.8,1),dim=c(2,97),dimnames=list(c('Registraties','Dummies'),1:97))
> y <- array(NA,dim=c(2,97),dimnames=list(c('Registraties','Dummies'),1:97))
> 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
Registraties Dummies
1 -3.3 0
2 -3.5 0
3 -3.5 0
4 -8.4 0
5 -15.7 0
6 -18.7 0
7 -22.8 0
8 -20.7 0
9 -14.0 0
10 -6.3 0
11 0.7 0
12 0.2 0
13 0.8 0
14 1.2 0
15 4.5 0
16 0.4 0
17 5.9 0
18 6.5 0
19 12.8 0
20 4.2 0
21 -3.3 0
22 -12.5 0
23 -16.3 0
24 -10.5 0
25 -11.8 0
26 -11.4 0
27 -17.7 0
28 -17.3 0
29 -18.6 0
30 -17.9 0
31 -21.4 0
32 -19.4 0
33 -15.5 0
34 -7.7 0
35 -0.7 0
36 -1.6 0
37 1.4 0
38 0.7 0
39 9.5 0
40 1.4 0
41 4.1 0
42 6.6 0
43 18.4 0
44 16.9 0
45 9.2 0
46 -4.3 0
47 -5.9 0
48 -7.7 0
49 -5.4 0
50 -2.3 0
51 -4.8 0
52 2.3 0
53 -5.2 0
54 -10.0 0
55 -17.1 0
56 -14.4 0
57 -3.9 0
58 3.7 0
59 6.5 0
60 0.9 0
61 -4.1 0
62 -7.0 0
63 -12.2 0
64 -2.5 0
65 4.4 0
66 13.7 0
67 12.3 0
68 13.4 0
69 2.2 0
70 1.7 0
71 -7.2 0
72 -4.8 0
73 -2.9 0
74 -2.4 0
75 -2.5 0
76 -5.3 0
77 -7.1 0
78 -8.0 0
79 -8.9 1
80 -7.7 1
81 -1.1 1
82 4.0 1
83 9.6 1
84 10.9 1
85 13.0 1
86 14.9 1
87 20.1 1
88 10.8 1
89 11.0 1
90 3.8 1
91 10.8 1
92 7.6 1
93 10.2 1
94 2.2 1
95 -0.1 1
96 -1.7 1
97 -4.8 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dummies
-3.859 9.364
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-18.941 -6.605 0.359 5.395 22.259
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -3.859 1.047 -3.686 0.000380 ***
Dummies 9.364 2.366 3.958 0.000146 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 9.247 on 95 degrees of freedom
Multiple R-squared: 0.1416, Adjusted R-squared: 0.1325
F-statistic: 15.67 on 1 and 95 DF, p-value: 0.0001457
> 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,] 0.2724835 0.54496695 0.727516525
[2,] 0.3843851 0.76877019 0.615614904
[3,] 0.5503636 0.89927276 0.449636381
[4,] 0.5675227 0.86495456 0.432477282
[5,] 0.4632428 0.92648555 0.536757227
[6,] 0.3958059 0.79161179 0.604194107
[7,] 0.4648116 0.92962329 0.535188356
[8,] 0.4837610 0.96752199 0.516239007
[9,] 0.4934571 0.98691423 0.506542883
[10,] 0.4939272 0.98785439 0.506072807
[11,] 0.5453635 0.90927305 0.454636524
[12,] 0.5085013 0.98299747 0.491498737
[13,] 0.5580769 0.88384615 0.441923074
[14,] 0.6013830 0.79723401 0.398617003
[15,] 0.7550598 0.48988034 0.244940169
[16,] 0.7386097 0.52278056 0.261390282
[17,] 0.6759508 0.64809833 0.324049167
[18,] 0.6609692 0.67806157 0.339030787
[19,] 0.6959006 0.60819882 0.304099409
[20,] 0.6576855 0.68462909 0.342314544
[21,] 0.6297175 0.74056504 0.370282521
[22,] 0.5968235 0.80635306 0.403176530
[23,] 0.6499437 0.70011265 0.350056324
[24,] 0.6917594 0.61648128 0.308240642
[25,] 0.7505598 0.49888034 0.249440171
[26,] 0.7941289 0.41174229 0.205871147
[27,] 0.8771099 0.24578016 0.122890081
[28,] 0.9201296 0.15974074 0.079870371
[29,] 0.9315479 0.13690411 0.068452057
[30,] 0.9158917 0.16821654 0.084108269
[31,] 0.9006207 0.19875864 0.099379320
[32,] 0.8804342 0.23913167 0.119565833
[33,] 0.8677861 0.26442786 0.132213932
[34,] 0.8497342 0.30053161 0.150265805
[35,] 0.8937582 0.21248360 0.106241801
[36,] 0.8779871 0.24402585 0.122012925
[37,] 0.8734022 0.25319567 0.126597834
[38,] 0.8837191 0.23256189 0.116280945
[39,] 0.9711933 0.05761331 0.028806656
[40,] 0.9934959 0.01300813 0.006504067
[41,] 0.9956276 0.00874471 0.004372355
[42,] 0.9933705 0.01325908 0.006629539
[43,] 0.9904197 0.01916055 0.009580275
[44,] 0.9872161 0.02556783 0.012783914
[45,] 0.9819533 0.03609338 0.018046689
[46,] 0.9744439 0.05111211 0.025556053
[47,] 0.9648214 0.07035726 0.035178631
[48,] 0.9567669 0.08646619 0.043233094
[49,] 0.9424083 0.11518339 0.057591697
[50,] 0.9358631 0.12827376 0.064136882
[51,] 0.9619514 0.07609715 0.038048574
[52,] 0.9730186 0.05396286 0.026981430
[53,] 0.9634072 0.07318551 0.036592753
[54,] 0.9559436 0.08811280 0.044056399
[55,] 0.9552012 0.08959755 0.044798777
[56,] 0.9410462 0.11790753 0.058953766
[57,] 0.9224063 0.15518746 0.077593732
[58,] 0.9075175 0.18496492 0.092482459
[59,] 0.9221266 0.15574688 0.077873441
[60,] 0.8988513 0.20229735 0.101148676
[61,] 0.8811966 0.23760685 0.118803425
[62,] 0.9330124 0.13397515 0.066987573
[63,] 0.9632791 0.07344176 0.036720881
[64,] 0.9882801 0.02343985 0.011719927
[65,] 0.9856051 0.02878975 0.014394874
[66,] 0.9824969 0.03500618 0.017503091
[67,] 0.9741095 0.05178107 0.025890535
[68,] 0.9610966 0.07780683 0.038903415
[69,] 0.9439016 0.11219676 0.056098381
[70,] 0.9224934 0.15501320 0.077506599
[71,] 0.8968675 0.20626506 0.103132530
[72,] 0.8600073 0.27998546 0.139992731
[73,] 0.8133945 0.37321101 0.186605506
[74,] 0.7576549 0.48469020 0.242345101
[75,] 0.8411531 0.31769381 0.158846904
[76,] 0.9117567 0.17648663 0.088243316
[77,] 0.9134432 0.17311357 0.086556783
[78,] 0.8848937 0.23021252 0.115106258
[79,] 0.8442854 0.31142918 0.155714588
[80,] 0.7976706 0.40465872 0.202329360
[81,] 0.7626806 0.47463877 0.237319385
[82,] 0.7586417 0.48271665 0.241358324
[83,] 0.9021221 0.19575577 0.097877883
[84,] 0.8790952 0.24180953 0.120904763
[85,] 0.8657537 0.26849267 0.134246336
[86,] 0.7712960 0.45740810 0.228704048
[87,] 0.7648615 0.47027702 0.235138511
[88,] 0.6911789 0.61764215 0.308821074
> postscript(file="/var/www/html/rcomp/tmp/1i83i1227777240.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2r53h1227777240.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3fczx1227777240.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4tmlg1227777240.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5tgy11227777240.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 = 97
Frequency = 1
1 2 3 4 5 6
0.55897436 0.35897436 0.35897436 -4.54102564 -11.84102564 -14.84102564
7 8 9 10 11 12
-18.94102564 -16.84102564 -10.14102564 -2.44102564 4.55897436 4.05897436
13 14 15 16 17 18
4.65897436 5.05897436 8.35897436 4.25897436 9.75897436 10.35897436
19 20 21 22 23 24
16.65897436 8.05897436 0.55897436 -8.64102564 -12.44102564 -6.64102564
25 26 27 28 29 30
-7.94102564 -7.54102564 -13.84102564 -13.44102564 -14.74102564 -14.04102564
31 32 33 34 35 36
-17.54102564 -15.54102564 -11.64102564 -3.84102564 3.15897436 2.25897436
37 38 39 40 41 42
5.25897436 4.55897436 13.35897436 5.25897436 7.95897436 10.45897436
43 44 45 46 47 48
22.25897436 20.75897436 13.05897436 -0.44102564 -2.04102564 -3.84102564
49 50 51 52 53 54
-1.54102564 1.55897436 -0.94102564 6.15897436 -1.34102564 -6.14102564
55 56 57 58 59 60
-13.24102564 -10.54102564 -0.04102564 7.55897436 10.35897436 4.75897436
61 62 63 64 65 66
-0.24102564 -3.14102564 -8.34102564 1.35897436 8.25897436 17.55897436
67 68 69 70 71 72
16.15897436 17.25897436 6.05897436 5.55897436 -3.34102564 -0.94102564
73 74 75 76 77 78
0.95897436 1.45897436 1.35897436 -1.44102564 -3.24102564 -4.14102564
79 80 81 82 83 84
-14.40526316 -13.20526316 -6.60526316 -1.50526316 4.09473684 5.39473684
85 86 87 88 89 90
7.49473684 9.39473684 14.59473684 5.29473684 5.49473684 -1.70526316
91 92 93 94 95 96
5.29473684 2.09473684 4.69473684 -3.30526316 -5.60526316 -7.20526316
97
-10.30526316
> postscript(file="/var/www/html/rcomp/tmp/6dlvr1227777240.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 = 97
Frequency = 1
lag(myerror, k = 1) myerror
0 0.55897436 NA
1 0.35897436 0.55897436
2 0.35897436 0.35897436
3 -4.54102564 0.35897436
4 -11.84102564 -4.54102564
5 -14.84102564 -11.84102564
6 -18.94102564 -14.84102564
7 -16.84102564 -18.94102564
8 -10.14102564 -16.84102564
9 -2.44102564 -10.14102564
10 4.55897436 -2.44102564
11 4.05897436 4.55897436
12 4.65897436 4.05897436
13 5.05897436 4.65897436
14 8.35897436 5.05897436
15 4.25897436 8.35897436
16 9.75897436 4.25897436
17 10.35897436 9.75897436
18 16.65897436 10.35897436
19 8.05897436 16.65897436
20 0.55897436 8.05897436
21 -8.64102564 0.55897436
22 -12.44102564 -8.64102564
23 -6.64102564 -12.44102564
24 -7.94102564 -6.64102564
25 -7.54102564 -7.94102564
26 -13.84102564 -7.54102564
27 -13.44102564 -13.84102564
28 -14.74102564 -13.44102564
29 -14.04102564 -14.74102564
30 -17.54102564 -14.04102564
31 -15.54102564 -17.54102564
32 -11.64102564 -15.54102564
33 -3.84102564 -11.64102564
34 3.15897436 -3.84102564
35 2.25897436 3.15897436
36 5.25897436 2.25897436
37 4.55897436 5.25897436
38 13.35897436 4.55897436
39 5.25897436 13.35897436
40 7.95897436 5.25897436
41 10.45897436 7.95897436
42 22.25897436 10.45897436
43 20.75897436 22.25897436
44 13.05897436 20.75897436
45 -0.44102564 13.05897436
46 -2.04102564 -0.44102564
47 -3.84102564 -2.04102564
48 -1.54102564 -3.84102564
49 1.55897436 -1.54102564
50 -0.94102564 1.55897436
51 6.15897436 -0.94102564
52 -1.34102564 6.15897436
53 -6.14102564 -1.34102564
54 -13.24102564 -6.14102564
55 -10.54102564 -13.24102564
56 -0.04102564 -10.54102564
57 7.55897436 -0.04102564
58 10.35897436 7.55897436
59 4.75897436 10.35897436
60 -0.24102564 4.75897436
61 -3.14102564 -0.24102564
62 -8.34102564 -3.14102564
63 1.35897436 -8.34102564
64 8.25897436 1.35897436
65 17.55897436 8.25897436
66 16.15897436 17.55897436
67 17.25897436 16.15897436
68 6.05897436 17.25897436
69 5.55897436 6.05897436
70 -3.34102564 5.55897436
71 -0.94102564 -3.34102564
72 0.95897436 -0.94102564
73 1.45897436 0.95897436
74 1.35897436 1.45897436
75 -1.44102564 1.35897436
76 -3.24102564 -1.44102564
77 -4.14102564 -3.24102564
78 -14.40526316 -4.14102564
79 -13.20526316 -14.40526316
80 -6.60526316 -13.20526316
81 -1.50526316 -6.60526316
82 4.09473684 -1.50526316
83 5.39473684 4.09473684
84 7.49473684 5.39473684
85 9.39473684 7.49473684
86 14.59473684 9.39473684
87 5.29473684 14.59473684
88 5.49473684 5.29473684
89 -1.70526316 5.49473684
90 5.29473684 -1.70526316
91 2.09473684 5.29473684
92 4.69473684 2.09473684
93 -3.30526316 4.69473684
94 -5.60526316 -3.30526316
95 -7.20526316 -5.60526316
96 -10.30526316 -7.20526316
97 NA -10.30526316
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.35897436 0.55897436
[2,] 0.35897436 0.35897436
[3,] -4.54102564 0.35897436
[4,] -11.84102564 -4.54102564
[5,] -14.84102564 -11.84102564
[6,] -18.94102564 -14.84102564
[7,] -16.84102564 -18.94102564
[8,] -10.14102564 -16.84102564
[9,] -2.44102564 -10.14102564
[10,] 4.55897436 -2.44102564
[11,] 4.05897436 4.55897436
[12,] 4.65897436 4.05897436
[13,] 5.05897436 4.65897436
[14,] 8.35897436 5.05897436
[15,] 4.25897436 8.35897436
[16,] 9.75897436 4.25897436
[17,] 10.35897436 9.75897436
[18,] 16.65897436 10.35897436
[19,] 8.05897436 16.65897436
[20,] 0.55897436 8.05897436
[21,] -8.64102564 0.55897436
[22,] -12.44102564 -8.64102564
[23,] -6.64102564 -12.44102564
[24,] -7.94102564 -6.64102564
[25,] -7.54102564 -7.94102564
[26,] -13.84102564 -7.54102564
[27,] -13.44102564 -13.84102564
[28,] -14.74102564 -13.44102564
[29,] -14.04102564 -14.74102564
[30,] -17.54102564 -14.04102564
[31,] -15.54102564 -17.54102564
[32,] -11.64102564 -15.54102564
[33,] -3.84102564 -11.64102564
[34,] 3.15897436 -3.84102564
[35,] 2.25897436 3.15897436
[36,] 5.25897436 2.25897436
[37,] 4.55897436 5.25897436
[38,] 13.35897436 4.55897436
[39,] 5.25897436 13.35897436
[40,] 7.95897436 5.25897436
[41,] 10.45897436 7.95897436
[42,] 22.25897436 10.45897436
[43,] 20.75897436 22.25897436
[44,] 13.05897436 20.75897436
[45,] -0.44102564 13.05897436
[46,] -2.04102564 -0.44102564
[47,] -3.84102564 -2.04102564
[48,] -1.54102564 -3.84102564
[49,] 1.55897436 -1.54102564
[50,] -0.94102564 1.55897436
[51,] 6.15897436 -0.94102564
[52,] -1.34102564 6.15897436
[53,] -6.14102564 -1.34102564
[54,] -13.24102564 -6.14102564
[55,] -10.54102564 -13.24102564
[56,] -0.04102564 -10.54102564
[57,] 7.55897436 -0.04102564
[58,] 10.35897436 7.55897436
[59,] 4.75897436 10.35897436
[60,] -0.24102564 4.75897436
[61,] -3.14102564 -0.24102564
[62,] -8.34102564 -3.14102564
[63,] 1.35897436 -8.34102564
[64,] 8.25897436 1.35897436
[65,] 17.55897436 8.25897436
[66,] 16.15897436 17.55897436
[67,] 17.25897436 16.15897436
[68,] 6.05897436 17.25897436
[69,] 5.55897436 6.05897436
[70,] -3.34102564 5.55897436
[71,] -0.94102564 -3.34102564
[72,] 0.95897436 -0.94102564
[73,] 1.45897436 0.95897436
[74,] 1.35897436 1.45897436
[75,] -1.44102564 1.35897436
[76,] -3.24102564 -1.44102564
[77,] -4.14102564 -3.24102564
[78,] -14.40526316 -4.14102564
[79,] -13.20526316 -14.40526316
[80,] -6.60526316 -13.20526316
[81,] -1.50526316 -6.60526316
[82,] 4.09473684 -1.50526316
[83,] 5.39473684 4.09473684
[84,] 7.49473684 5.39473684
[85,] 9.39473684 7.49473684
[86,] 14.59473684 9.39473684
[87,] 5.29473684 14.59473684
[88,] 5.49473684 5.29473684
[89,] -1.70526316 5.49473684
[90,] 5.29473684 -1.70526316
[91,] 2.09473684 5.29473684
[92,] 4.69473684 2.09473684
[93,] -3.30526316 4.69473684
[94,] -5.60526316 -3.30526316
[95,] -7.20526316 -5.60526316
[96,] -10.30526316 -7.20526316
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.35897436 0.55897436
2 0.35897436 0.35897436
3 -4.54102564 0.35897436
4 -11.84102564 -4.54102564
5 -14.84102564 -11.84102564
6 -18.94102564 -14.84102564
7 -16.84102564 -18.94102564
8 -10.14102564 -16.84102564
9 -2.44102564 -10.14102564
10 4.55897436 -2.44102564
11 4.05897436 4.55897436
12 4.65897436 4.05897436
13 5.05897436 4.65897436
14 8.35897436 5.05897436
15 4.25897436 8.35897436
16 9.75897436 4.25897436
17 10.35897436 9.75897436
18 16.65897436 10.35897436
19 8.05897436 16.65897436
20 0.55897436 8.05897436
21 -8.64102564 0.55897436
22 -12.44102564 -8.64102564
23 -6.64102564 -12.44102564
24 -7.94102564 -6.64102564
25 -7.54102564 -7.94102564
26 -13.84102564 -7.54102564
27 -13.44102564 -13.84102564
28 -14.74102564 -13.44102564
29 -14.04102564 -14.74102564
30 -17.54102564 -14.04102564
31 -15.54102564 -17.54102564
32 -11.64102564 -15.54102564
33 -3.84102564 -11.64102564
34 3.15897436 -3.84102564
35 2.25897436 3.15897436
36 5.25897436 2.25897436
37 4.55897436 5.25897436
38 13.35897436 4.55897436
39 5.25897436 13.35897436
40 7.95897436 5.25897436
41 10.45897436 7.95897436
42 22.25897436 10.45897436
43 20.75897436 22.25897436
44 13.05897436 20.75897436
45 -0.44102564 13.05897436
46 -2.04102564 -0.44102564
47 -3.84102564 -2.04102564
48 -1.54102564 -3.84102564
49 1.55897436 -1.54102564
50 -0.94102564 1.55897436
51 6.15897436 -0.94102564
52 -1.34102564 6.15897436
53 -6.14102564 -1.34102564
54 -13.24102564 -6.14102564
55 -10.54102564 -13.24102564
56 -0.04102564 -10.54102564
57 7.55897436 -0.04102564
58 10.35897436 7.55897436
59 4.75897436 10.35897436
60 -0.24102564 4.75897436
61 -3.14102564 -0.24102564
62 -8.34102564 -3.14102564
63 1.35897436 -8.34102564
64 8.25897436 1.35897436
65 17.55897436 8.25897436
66 16.15897436 17.55897436
67 17.25897436 16.15897436
68 6.05897436 17.25897436
69 5.55897436 6.05897436
70 -3.34102564 5.55897436
71 -0.94102564 -3.34102564
72 0.95897436 -0.94102564
73 1.45897436 0.95897436
74 1.35897436 1.45897436
75 -1.44102564 1.35897436
76 -3.24102564 -1.44102564
77 -4.14102564 -3.24102564
78 -14.40526316 -4.14102564
79 -13.20526316 -14.40526316
80 -6.60526316 -13.20526316
81 -1.50526316 -6.60526316
82 4.09473684 -1.50526316
83 5.39473684 4.09473684
84 7.49473684 5.39473684
85 9.39473684 7.49473684
86 14.59473684 9.39473684
87 5.29473684 14.59473684
88 5.49473684 5.29473684
89 -1.70526316 5.49473684
90 5.29473684 -1.70526316
91 2.09473684 5.29473684
92 4.69473684 2.09473684
93 -3.30526316 4.69473684
94 -5.60526316 -3.30526316
95 -7.20526316 -5.60526316
96 -10.30526316 -7.20526316
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/7us2q1227777240.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8q0jn1227777240.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9nxuo1227777240.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10w5w91227777240.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/110r2j1227777240.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/12u36k1227777240.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13ykex1227777240.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/1483mh1227777240.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/1567qy1227777240.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/16av4y1227777241.tab")
+ }
>
> system("convert tmp/1i83i1227777240.ps tmp/1i83i1227777240.png")
> system("convert tmp/2r53h1227777240.ps tmp/2r53h1227777240.png")
> system("convert tmp/3fczx1227777240.ps tmp/3fczx1227777240.png")
> system("convert tmp/4tmlg1227777240.ps tmp/4tmlg1227777240.png")
> system("convert tmp/5tgy11227777240.ps tmp/5tgy11227777240.png")
> system("convert tmp/6dlvr1227777240.ps tmp/6dlvr1227777240.png")
> system("convert tmp/7us2q1227777240.ps tmp/7us2q1227777240.png")
> system("convert tmp/8q0jn1227777240.ps tmp/8q0jn1227777240.png")
> system("convert tmp/9nxuo1227777240.ps tmp/9nxuo1227777240.png")
> system("convert tmp/10w5w91227777240.ps tmp/10w5w91227777240.png")
>
>
> proc.time()
user system elapsed
3.147 1.755 3.761