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.
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Natural language support but running in an English locale
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> x <- array(list(5.81,0,5.76,0,5.99,0,6.12,0,6.03,0,6.25,0,5.80,0,5.67,0,5.89,0,5.91,0,5.86,0,6.07,0,6.27,0,6.68,0,6.77,0,6.71,0,6.62,0,6.50,0,5.89,0,6.05,0,6.43,0,6.47,0,6.62,0,6.77,0,6.70,0,6.95,0,6.73,0,7.07,0,7.28,0,7.32,0,6.76,0,6.93,0,6.99,0,7.16,0,7.28,0,7.08,0,7.34,0,7.87,0,6.28,1,6.30,1,6.36,1,6.28,1,5.89,1,6.04,1,5.96,1,6.10,1,6.26,1,6.02,1,6.25,1,6.41,1,6.22,1,6.57,1,6.18,1,6.26,1,6.10,1,6.02,1,6.06,1,6.35,1,6.21,1,6.48,1,6.74,1,6.53,1,6.80,1,6.75,1,6.56,1,6.66,1,6.18,1,6.40,1,6.43,1,6.54,1,6.44,1,6.64,1,6.82,1,6.97,1,7.00,1,6.91,1,6.74,1,6.98,1,6.37,1,6.56,1,6.63,1,6.87,1,6.68,1,6.75,1,6.84,1,7.15,1,7.09,1,6.97,1,7.15,1),dim=c(2,89),dimnames=list(c('Y','X'),1:89))
> y <- array(NA,dim=c(2,89),dimnames=list(c('Y','X'),1:89))
> 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 5.81 0
2 5.76 0
3 5.99 0
4 6.12 0
5 6.03 0
6 6.25 0
7 5.80 0
8 5.67 0
9 5.89 0
10 5.91 0
11 5.86 0
12 6.07 0
13 6.27 0
14 6.68 0
15 6.77 0
16 6.71 0
17 6.62 0
18 6.50 0
19 5.89 0
20 6.05 0
21 6.43 0
22 6.47 0
23 6.62 0
24 6.77 0
25 6.70 0
26 6.95 0
27 6.73 0
28 7.07 0
29 7.28 0
30 7.32 0
31 6.76 0
32 6.93 0
33 6.99 0
34 7.16 0
35 7.28 0
36 7.08 0
37 7.34 0
38 7.87 0
39 6.28 1
40 6.30 1
41 6.36 1
42 6.28 1
43 5.89 1
44 6.04 1
45 5.96 1
46 6.10 1
47 6.26 1
48 6.02 1
49 6.25 1
50 6.41 1
51 6.22 1
52 6.57 1
53 6.18 1
54 6.26 1
55 6.10 1
56 6.02 1
57 6.06 1
58 6.35 1
59 6.21 1
60 6.48 1
61 6.74 1
62 6.53 1
63 6.80 1
64 6.75 1
65 6.56 1
66 6.66 1
67 6.18 1
68 6.40 1
69 6.43 1
70 6.54 1
71 6.44 1
72 6.64 1
73 6.82 1
74 6.97 1
75 7.00 1
76 6.91 1
77 6.74 1
78 6.98 1
79 6.37 1
80 6.56 1
81 6.63 1
82 6.87 1
83 6.68 1
84 6.75 1
85 6.84 1
86 7.15 1
87 7.09 1
88 6.97 1
89 7.15 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
6.53684 -0.03194
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-0.8668 -0.3249 0.0251 0.2951 1.3332
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 6.53684 0.07190 90.922 <2e-16 ***
X -0.03194 0.09498 -0.336 0.737
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.4432 on 87 degrees of freedom
Multiple R-squared: 0.001298, Adjusted R-squared: -0.01018
F-statistic: 0.1131 on 1 and 87 DF, p-value: 0.7375
> 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,] 0.082726646 0.1654532921 0.9172733540
[2,] 0.081681534 0.1633630684 0.9183184658
[3,] 0.052096501 0.1041930030 0.9479034985
[4,] 0.056193868 0.1123877362 0.9438061319
[5,] 0.030248336 0.0604966722 0.9697516639
[6,] 0.016118136 0.0322362718 0.9838818641
[7,] 0.009486311 0.0189726213 0.9905136893
[8,] 0.006621569 0.0132431372 0.9933784314
[9,] 0.011728508 0.0234570167 0.9882714916
[10,] 0.124368905 0.2487378096 0.8756310952
[11,] 0.342153515 0.6843070300 0.6578464850
[12,] 0.474885404 0.9497708087 0.5251145957
[13,] 0.522060299 0.9558794023 0.4779397012
[14,] 0.514904837 0.9701903251 0.4850951626
[15,] 0.580421981 0.8391560372 0.4195780186
[16,] 0.612019237 0.7759615268 0.3879807634
[17,] 0.621725078 0.7565498440 0.3782749220
[18,] 0.640532867 0.7189342669 0.3594671335
[19,] 0.684360511 0.6312789787 0.3156394893
[20,] 0.753363796 0.4932724086 0.2466362043
[21,] 0.790932150 0.4181357001 0.2090678501
[22,] 0.862575256 0.2748494873 0.1374247436
[23,] 0.882517834 0.2349643312 0.1174821656
[24,] 0.930318872 0.1393622569 0.0696811284
[25,] 0.971327877 0.0573442453 0.0286721226
[26,] 0.987840582 0.0243188363 0.0121594181
[27,] 0.988267062 0.0234658764 0.0117329382
[28,] 0.989378455 0.0212430895 0.0106215448
[29,] 0.990796280 0.0184074402 0.0092037201
[30,] 0.992961220 0.0140775595 0.0070387798
[31,] 0.995095594 0.0098088114 0.0049044057
[32,] 0.996151972 0.0076960553 0.0038480276
[33,] 0.997744283 0.0045114338 0.0022557169
[34,] 0.999403560 0.0011928808 0.0005964404
[35,] 0.999075383 0.0018492344 0.0009246172
[36,] 0.998571451 0.0028570974 0.0014285487
[37,] 0.997753151 0.0044936982 0.0022468491
[38,] 0.996715938 0.0065681244 0.0032840622
[39,] 0.997746089 0.0045078211 0.0022539105
[40,] 0.997797999 0.0044040020 0.0022020010
[41,] 0.998330453 0.0033390950 0.0016695475
[42,] 0.998294305 0.0034113897 0.0017056949
[43,] 0.997764691 0.0044706182 0.0022353091
[44,] 0.998288451 0.0034230990 0.0017115495
[45,] 0.997899300 0.0042014000 0.0021007000
[46,] 0.996980808 0.0060383843 0.0030191922
[47,] 0.996609452 0.0067810969 0.0033905484
[48,] 0.995071233 0.0098575338 0.0049287669
[49,] 0.995078151 0.0098436976 0.0049218488
[50,] 0.994432093 0.0111358133 0.0055679066
[51,] 0.995975899 0.0080482013 0.0040241007
[52,] 0.998201440 0.0035971200 0.0017985600
[53,] 0.999297358 0.0014052843 0.0007026421
[54,] 0.999257799 0.0014844019 0.0007422009
[55,] 0.999586818 0.0008263641 0.0004131820
[56,] 0.999454037 0.0010919252 0.0005459626
[57,] 0.999146322 0.0017073562 0.0008536781
[58,] 0.998768306 0.0024633885 0.0012316942
[59,] 0.998148972 0.0037020556 0.0018510278
[60,] 0.997054648 0.0058907033 0.0029453516
[61,] 0.995586096 0.0088278071 0.0044139036
[62,] 0.992953849 0.0140923025 0.0070461512
[63,] 0.997255043 0.0054899133 0.0027449567
[64,] 0.997638526 0.0047229488 0.0023614744
[65,] 0.997971746 0.0040565084 0.0020282542
[66,] 0.997560338 0.0048793241 0.0024396620
[67,] 0.998322059 0.0033558822 0.0016779411
[68,] 0.997562780 0.0048744395 0.0024372197
[69,] 0.995433283 0.0091334341 0.0045667170
[70,] 0.992694441 0.0146111175 0.0073055587
[71,] 0.989116092 0.0217678166 0.0108839083
[72,] 0.980984389 0.0380312230 0.0190156115
[73,] 0.966581694 0.0668366121 0.0334183060
[74,] 0.948813711 0.1023725784 0.0511862892
[75,] 0.974003501 0.0519929988 0.0259964994
[76,] 0.976087845 0.0478243107 0.0239121553
[77,] 0.975561975 0.0488760506 0.0244380253
[78,] 0.945726570 0.1085468594 0.0542734297
[79,] 0.944500813 0.1109983748 0.0554991874
[80,] 0.943948147 0.1121037055 0.0560518527
> postscript(file="/var/www/html/freestat/rcomp/tmp/103r21290878356.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/203r21290878356.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/303r21290878356.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4td841290878356.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5td841290878356.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 = 89
Frequency = 1
1 2 3 4 5 6
-0.72684211 -0.77684211 -0.54684211 -0.41684211 -0.50684211 -0.28684211
7 8 9 10 11 12
-0.73684211 -0.86684211 -0.64684211 -0.62684211 -0.67684211 -0.46684211
13 14 15 16 17 18
-0.26684211 0.14315789 0.23315789 0.17315789 0.08315789 -0.03684211
19 20 21 22 23 24
-0.64684211 -0.48684211 -0.10684211 -0.06684211 0.08315789 0.23315789
25 26 27 28 29 30
0.16315789 0.41315789 0.19315789 0.53315789 0.74315789 0.78315789
31 32 33 34 35 36
0.22315789 0.39315789 0.45315789 0.62315789 0.74315789 0.54315789
37 38 39 40 41 42
0.80315789 1.33315789 -0.22490196 -0.20490196 -0.14490196 -0.22490196
43 44 45 46 47 48
-0.61490196 -0.46490196 -0.54490196 -0.40490196 -0.24490196 -0.48490196
49 50 51 52 53 54
-0.25490196 -0.09490196 -0.28490196 0.06509804 -0.32490196 -0.24490196
55 56 57 58 59 60
-0.40490196 -0.48490196 -0.44490196 -0.15490196 -0.29490196 -0.02490196
61 62 63 64 65 66
0.23509804 0.02509804 0.29509804 0.24509804 0.05509804 0.15509804
67 68 69 70 71 72
-0.32490196 -0.10490196 -0.07490196 0.03509804 -0.06490196 0.13509804
73 74 75 76 77 78
0.31509804 0.46509804 0.49509804 0.40509804 0.23509804 0.47509804
79 80 81 82 83 84
-0.13490196 0.05509804 0.12509804 0.36509804 0.17509804 0.24509804
85 86 87 88 89
0.33509804 0.64509804 0.58509804 0.46509804 0.64509804
> postscript(file="/var/www/html/freestat/rcomp/tmp/6td841290878356.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 = 89
Frequency = 1
lag(myerror, k = 1) myerror
0 -0.72684211 NA
1 -0.77684211 -0.72684211
2 -0.54684211 -0.77684211
3 -0.41684211 -0.54684211
4 -0.50684211 -0.41684211
5 -0.28684211 -0.50684211
6 -0.73684211 -0.28684211
7 -0.86684211 -0.73684211
8 -0.64684211 -0.86684211
9 -0.62684211 -0.64684211
10 -0.67684211 -0.62684211
11 -0.46684211 -0.67684211
12 -0.26684211 -0.46684211
13 0.14315789 -0.26684211
14 0.23315789 0.14315789
15 0.17315789 0.23315789
16 0.08315789 0.17315789
17 -0.03684211 0.08315789
18 -0.64684211 -0.03684211
19 -0.48684211 -0.64684211
20 -0.10684211 -0.48684211
21 -0.06684211 -0.10684211
22 0.08315789 -0.06684211
23 0.23315789 0.08315789
24 0.16315789 0.23315789
25 0.41315789 0.16315789
26 0.19315789 0.41315789
27 0.53315789 0.19315789
28 0.74315789 0.53315789
29 0.78315789 0.74315789
30 0.22315789 0.78315789
31 0.39315789 0.22315789
32 0.45315789 0.39315789
33 0.62315789 0.45315789
34 0.74315789 0.62315789
35 0.54315789 0.74315789
36 0.80315789 0.54315789
37 1.33315789 0.80315789
38 -0.22490196 1.33315789
39 -0.20490196 -0.22490196
40 -0.14490196 -0.20490196
41 -0.22490196 -0.14490196
42 -0.61490196 -0.22490196
43 -0.46490196 -0.61490196
44 -0.54490196 -0.46490196
45 -0.40490196 -0.54490196
46 -0.24490196 -0.40490196
47 -0.48490196 -0.24490196
48 -0.25490196 -0.48490196
49 -0.09490196 -0.25490196
50 -0.28490196 -0.09490196
51 0.06509804 -0.28490196
52 -0.32490196 0.06509804
53 -0.24490196 -0.32490196
54 -0.40490196 -0.24490196
55 -0.48490196 -0.40490196
56 -0.44490196 -0.48490196
57 -0.15490196 -0.44490196
58 -0.29490196 -0.15490196
59 -0.02490196 -0.29490196
60 0.23509804 -0.02490196
61 0.02509804 0.23509804
62 0.29509804 0.02509804
63 0.24509804 0.29509804
64 0.05509804 0.24509804
65 0.15509804 0.05509804
66 -0.32490196 0.15509804
67 -0.10490196 -0.32490196
68 -0.07490196 -0.10490196
69 0.03509804 -0.07490196
70 -0.06490196 0.03509804
71 0.13509804 -0.06490196
72 0.31509804 0.13509804
73 0.46509804 0.31509804
74 0.49509804 0.46509804
75 0.40509804 0.49509804
76 0.23509804 0.40509804
77 0.47509804 0.23509804
78 -0.13490196 0.47509804
79 0.05509804 -0.13490196
80 0.12509804 0.05509804
81 0.36509804 0.12509804
82 0.17509804 0.36509804
83 0.24509804 0.17509804
84 0.33509804 0.24509804
85 0.64509804 0.33509804
86 0.58509804 0.64509804
87 0.46509804 0.58509804
88 0.64509804 0.46509804
89 NA 0.64509804
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.77684211 -0.72684211
[2,] -0.54684211 -0.77684211
[3,] -0.41684211 -0.54684211
[4,] -0.50684211 -0.41684211
[5,] -0.28684211 -0.50684211
[6,] -0.73684211 -0.28684211
[7,] -0.86684211 -0.73684211
[8,] -0.64684211 -0.86684211
[9,] -0.62684211 -0.64684211
[10,] -0.67684211 -0.62684211
[11,] -0.46684211 -0.67684211
[12,] -0.26684211 -0.46684211
[13,] 0.14315789 -0.26684211
[14,] 0.23315789 0.14315789
[15,] 0.17315789 0.23315789
[16,] 0.08315789 0.17315789
[17,] -0.03684211 0.08315789
[18,] -0.64684211 -0.03684211
[19,] -0.48684211 -0.64684211
[20,] -0.10684211 -0.48684211
[21,] -0.06684211 -0.10684211
[22,] 0.08315789 -0.06684211
[23,] 0.23315789 0.08315789
[24,] 0.16315789 0.23315789
[25,] 0.41315789 0.16315789
[26,] 0.19315789 0.41315789
[27,] 0.53315789 0.19315789
[28,] 0.74315789 0.53315789
[29,] 0.78315789 0.74315789
[30,] 0.22315789 0.78315789
[31,] 0.39315789 0.22315789
[32,] 0.45315789 0.39315789
[33,] 0.62315789 0.45315789
[34,] 0.74315789 0.62315789
[35,] 0.54315789 0.74315789
[36,] 0.80315789 0.54315789
[37,] 1.33315789 0.80315789
[38,] -0.22490196 1.33315789
[39,] -0.20490196 -0.22490196
[40,] -0.14490196 -0.20490196
[41,] -0.22490196 -0.14490196
[42,] -0.61490196 -0.22490196
[43,] -0.46490196 -0.61490196
[44,] -0.54490196 -0.46490196
[45,] -0.40490196 -0.54490196
[46,] -0.24490196 -0.40490196
[47,] -0.48490196 -0.24490196
[48,] -0.25490196 -0.48490196
[49,] -0.09490196 -0.25490196
[50,] -0.28490196 -0.09490196
[51,] 0.06509804 -0.28490196
[52,] -0.32490196 0.06509804
[53,] -0.24490196 -0.32490196
[54,] -0.40490196 -0.24490196
[55,] -0.48490196 -0.40490196
[56,] -0.44490196 -0.48490196
[57,] -0.15490196 -0.44490196
[58,] -0.29490196 -0.15490196
[59,] -0.02490196 -0.29490196
[60,] 0.23509804 -0.02490196
[61,] 0.02509804 0.23509804
[62,] 0.29509804 0.02509804
[63,] 0.24509804 0.29509804
[64,] 0.05509804 0.24509804
[65,] 0.15509804 0.05509804
[66,] -0.32490196 0.15509804
[67,] -0.10490196 -0.32490196
[68,] -0.07490196 -0.10490196
[69,] 0.03509804 -0.07490196
[70,] -0.06490196 0.03509804
[71,] 0.13509804 -0.06490196
[72,] 0.31509804 0.13509804
[73,] 0.46509804 0.31509804
[74,] 0.49509804 0.46509804
[75,] 0.40509804 0.49509804
[76,] 0.23509804 0.40509804
[77,] 0.47509804 0.23509804
[78,] -0.13490196 0.47509804
[79,] 0.05509804 -0.13490196
[80,] 0.12509804 0.05509804
[81,] 0.36509804 0.12509804
[82,] 0.17509804 0.36509804
[83,] 0.24509804 0.17509804
[84,] 0.33509804 0.24509804
[85,] 0.64509804 0.33509804
[86,] 0.58509804 0.64509804
[87,] 0.46509804 0.58509804
[88,] 0.64509804 0.46509804
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.77684211 -0.72684211
2 -0.54684211 -0.77684211
3 -0.41684211 -0.54684211
4 -0.50684211 -0.41684211
5 -0.28684211 -0.50684211
6 -0.73684211 -0.28684211
7 -0.86684211 -0.73684211
8 -0.64684211 -0.86684211
9 -0.62684211 -0.64684211
10 -0.67684211 -0.62684211
11 -0.46684211 -0.67684211
12 -0.26684211 -0.46684211
13 0.14315789 -0.26684211
14 0.23315789 0.14315789
15 0.17315789 0.23315789
16 0.08315789 0.17315789
17 -0.03684211 0.08315789
18 -0.64684211 -0.03684211
19 -0.48684211 -0.64684211
20 -0.10684211 -0.48684211
21 -0.06684211 -0.10684211
22 0.08315789 -0.06684211
23 0.23315789 0.08315789
24 0.16315789 0.23315789
25 0.41315789 0.16315789
26 0.19315789 0.41315789
27 0.53315789 0.19315789
28 0.74315789 0.53315789
29 0.78315789 0.74315789
30 0.22315789 0.78315789
31 0.39315789 0.22315789
32 0.45315789 0.39315789
33 0.62315789 0.45315789
34 0.74315789 0.62315789
35 0.54315789 0.74315789
36 0.80315789 0.54315789
37 1.33315789 0.80315789
38 -0.22490196 1.33315789
39 -0.20490196 -0.22490196
40 -0.14490196 -0.20490196
41 -0.22490196 -0.14490196
42 -0.61490196 -0.22490196
43 -0.46490196 -0.61490196
44 -0.54490196 -0.46490196
45 -0.40490196 -0.54490196
46 -0.24490196 -0.40490196
47 -0.48490196 -0.24490196
48 -0.25490196 -0.48490196
49 -0.09490196 -0.25490196
50 -0.28490196 -0.09490196
51 0.06509804 -0.28490196
52 -0.32490196 0.06509804
53 -0.24490196 -0.32490196
54 -0.40490196 -0.24490196
55 -0.48490196 -0.40490196
56 -0.44490196 -0.48490196
57 -0.15490196 -0.44490196
58 -0.29490196 -0.15490196
59 -0.02490196 -0.29490196
60 0.23509804 -0.02490196
61 0.02509804 0.23509804
62 0.29509804 0.02509804
63 0.24509804 0.29509804
64 0.05509804 0.24509804
65 0.15509804 0.05509804
66 -0.32490196 0.15509804
67 -0.10490196 -0.32490196
68 -0.07490196 -0.10490196
69 0.03509804 -0.07490196
70 -0.06490196 0.03509804
71 0.13509804 -0.06490196
72 0.31509804 0.13509804
73 0.46509804 0.31509804
74 0.49509804 0.46509804
75 0.40509804 0.49509804
76 0.23509804 0.40509804
77 0.47509804 0.23509804
78 -0.13490196 0.47509804
79 0.05509804 -0.13490196
80 0.12509804 0.05509804
81 0.36509804 0.12509804
82 0.17509804 0.36509804
83 0.24509804 0.17509804
84 0.33509804 0.24509804
85 0.64509804 0.33509804
86 0.58509804 0.64509804
87 0.46509804 0.58509804
88 0.64509804 0.46509804
> 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/74m7q1290878356.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8wdos1290878356.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9wdos1290878356.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10wdos1290878356.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/110w5y1290878356.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/12memm1290878356.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/13sf0g1290878356.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/14l6011290878356.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/1567yp1290878356.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/16kzwx1290878356.tab")
+ }
>
> try(system("convert tmp/103r21290878356.ps tmp/103r21290878356.png",intern=TRUE))
character(0)
> try(system("convert tmp/203r21290878356.ps tmp/203r21290878356.png",intern=TRUE))
character(0)
> try(system("convert tmp/303r21290878356.ps tmp/303r21290878356.png",intern=TRUE))
character(0)
> try(system("convert tmp/4td841290878356.ps tmp/4td841290878356.png",intern=TRUE))
character(0)
> try(system("convert tmp/5td841290878356.ps tmp/5td841290878356.png",intern=TRUE))
character(0)
> try(system("convert tmp/6td841290878356.ps tmp/6td841290878356.png",intern=TRUE))
character(0)
> try(system("convert tmp/74m7q1290878356.ps tmp/74m7q1290878356.png",intern=TRUE))
character(0)
> try(system("convert tmp/8wdos1290878356.ps tmp/8wdos1290878356.png",intern=TRUE))
character(0)
> try(system("convert tmp/9wdos1290878356.ps tmp/9wdos1290878356.png",intern=TRUE))
character(0)
> try(system("convert tmp/10wdos1290878356.ps tmp/10wdos1290878356.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
4.143 2.455 4.508