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(95.2,0,95.00,0,94.00,0,92.2,0,91.00,0,91.2,0,103.4,1,105.00,0,104.6,0,103.8,0,101.8,0,102.4,0,103.8,0,103.4,0,102.00,0,101.8,0,100.2,0,101.4,0,113.8,0,116.00,0,115.6,0,113.00,0,109.4,0,111.00,0,112.4,0,112.2,0,111.00,0,108.8,0,107.4,0,108.6,0,118.8,0,122.2,1,122.6,0,122.2,0,118.8,0,119.00,0,118.2,0,117.8,0,116.8,0,114.6,0,113.4,0,113.8,0,124.2,0,125.8,0,125.6,0,122.4,0,119.00,0,119.4,0,118.6,0,118.00,0,116.00,0,114.8,0,114.6,0,114.6,0,124.00,0,125.2,0,124.00,0,117.6,1,113.2,0,111.4,0,112.2,0,109.8,0,106.4,0,105.2,0,102.2,0,99.8,0,111.00,0,113.00,0,108.4,0,105.4,0,102.00,0,102.8,0),dim=c(2,72),dimnames=list(c('Werkloosheid','Dumivariabele'),1:72))
> y <- array(NA,dim=c(2,72),dimnames=list(c('Werkloosheid','Dumivariabele'),1:72))
> 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 = 'Include Monthly 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
Werkloosheid Dumivariabele M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 95.2 0 1 0 0 0 0 0 0 0 0 0 0 1
2 95.0 0 0 1 0 0 0 0 0 0 0 0 0 2
3 94.0 0 0 0 1 0 0 0 0 0 0 0 0 3
4 92.2 0 0 0 0 1 0 0 0 0 0 0 0 4
5 91.0 0 0 0 0 0 1 0 0 0 0 0 0 5
6 91.2 0 0 0 0 0 0 1 0 0 0 0 0 6
7 103.4 1 0 0 0 0 0 0 1 0 0 0 0 7
8 105.0 0 0 0 0 0 0 0 0 1 0 0 0 8
9 104.6 0 0 0 0 0 0 0 0 0 1 0 0 9
10 103.8 0 0 0 0 0 0 0 0 0 0 1 0 10
11 101.8 0 0 0 0 0 0 0 0 0 0 0 1 11
12 102.4 0 0 0 0 0 0 0 0 0 0 0 0 12
13 103.8 0 1 0 0 0 0 0 0 0 0 0 0 13
14 103.4 0 0 1 0 0 0 0 0 0 0 0 0 14
15 102.0 0 0 0 1 0 0 0 0 0 0 0 0 15
16 101.8 0 0 0 0 1 0 0 0 0 0 0 0 16
17 100.2 0 0 0 0 0 1 0 0 0 0 0 0 17
18 101.4 0 0 0 0 0 0 1 0 0 0 0 0 18
19 113.8 0 0 0 0 0 0 0 1 0 0 0 0 19
20 116.0 0 0 0 0 0 0 0 0 1 0 0 0 20
21 115.6 0 0 0 0 0 0 0 0 0 1 0 0 21
22 113.0 0 0 0 0 0 0 0 0 0 0 1 0 22
23 109.4 0 0 0 0 0 0 0 0 0 0 0 1 23
24 111.0 0 0 0 0 0 0 0 0 0 0 0 0 24
25 112.4 0 1 0 0 0 0 0 0 0 0 0 0 25
26 112.2 0 0 1 0 0 0 0 0 0 0 0 0 26
27 111.0 0 0 0 1 0 0 0 0 0 0 0 0 27
28 108.8 0 0 0 0 1 0 0 0 0 0 0 0 28
29 107.4 0 0 0 0 0 1 0 0 0 0 0 0 29
30 108.6 0 0 0 0 0 0 1 0 0 0 0 0 30
31 118.8 0 0 0 0 0 0 0 1 0 0 0 0 31
32 122.2 1 0 0 0 0 0 0 0 1 0 0 0 32
33 122.6 0 0 0 0 0 0 0 0 0 1 0 0 33
34 122.2 0 0 0 0 0 0 0 0 0 0 1 0 34
35 118.8 0 0 0 0 0 0 0 0 0 0 0 1 35
36 119.0 0 0 0 0 0 0 0 0 0 0 0 0 36
37 118.2 0 1 0 0 0 0 0 0 0 0 0 0 37
38 117.8 0 0 1 0 0 0 0 0 0 0 0 0 38
39 116.8 0 0 0 1 0 0 0 0 0 0 0 0 39
40 114.6 0 0 0 0 1 0 0 0 0 0 0 0 40
41 113.4 0 0 0 0 0 1 0 0 0 0 0 0 41
42 113.8 0 0 0 0 0 0 1 0 0 0 0 0 42
43 124.2 0 0 0 0 0 0 0 1 0 0 0 0 43
44 125.8 0 0 0 0 0 0 0 0 1 0 0 0 44
45 125.6 0 0 0 0 0 0 0 0 0 1 0 0 45
46 122.4 0 0 0 0 0 0 0 0 0 0 1 0 46
47 119.0 0 0 0 0 0 0 0 0 0 0 0 1 47
48 119.4 0 0 0 0 0 0 0 0 0 0 0 0 48
49 118.6 0 1 0 0 0 0 0 0 0 0 0 0 49
50 118.0 0 0 1 0 0 0 0 0 0 0 0 0 50
51 116.0 0 0 0 1 0 0 0 0 0 0 0 0 51
52 114.8 0 0 0 0 1 0 0 0 0 0 0 0 52
53 114.6 0 0 0 0 0 1 0 0 0 0 0 0 53
54 114.6 0 0 0 0 0 0 1 0 0 0 0 0 54
55 124.0 0 0 0 0 0 0 0 1 0 0 0 0 55
56 125.2 0 0 0 0 0 0 0 0 1 0 0 0 56
57 124.0 0 0 0 0 0 0 0 0 0 1 0 0 57
58 117.6 1 0 0 0 0 0 0 0 0 0 1 0 58
59 113.2 0 0 0 0 0 0 0 0 0 0 0 1 59
60 111.4 0 0 0 0 0 0 0 0 0 0 0 0 60
61 112.2 0 1 0 0 0 0 0 0 0 0 0 0 61
62 109.8 0 0 1 0 0 0 0 0 0 0 0 0 62
63 106.4 0 0 0 1 0 0 0 0 0 0 0 0 63
64 105.2 0 0 0 0 1 0 0 0 0 0 0 0 64
65 102.2 0 0 0 0 0 1 0 0 0 0 0 0 65
66 99.8 0 0 0 0 0 0 1 0 0 0 0 0 66
67 111.0 0 0 0 0 0 0 0 1 0 0 0 0 67
68 113.0 0 0 0 0 0 0 0 0 1 0 0 0 68
69 108.4 0 0 0 0 0 0 0 0 0 1 0 0 69
70 105.4 0 0 0 0 0 0 0 0 0 0 1 0 70
71 102.0 0 0 0 0 0 0 0 0 0 0 0 1 71
72 102.8 0 0 0 0 0 0 0 0 0 0 0 0 72
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Dumivariabele M1 M2 M3
103.4989 -0.5541 1.0313 0.1527 -1.6926
M4 M5 M6 M7 M8
-3.3379 -4.9498 -5.0284 5.8520 7.6734
M9 M10 M11 t
6.3358 3.5162 -0.1214 0.1786
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-14.117 -6.455 1.965 6.021 9.172
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 103.49885 3.60099 28.742 < 2e-16 ***
Dumivariabele -0.55409 4.80896 -0.115 0.908669
M1 1.03125 4.40687 0.234 0.815801
M2 0.15265 4.40231 0.035 0.972457
M3 -1.69261 4.39818 -0.385 0.701761
M4 -3.33788 4.39448 -0.760 0.450594
M5 -4.94981 4.39122 -1.127 0.264297
M6 -5.02841 4.38839 -1.146 0.256566
M7 5.85201 4.45605 1.313 0.194263
M8 7.67341 4.45463 1.723 0.090295 .
M9 6.33580 4.38250 1.446 0.153643
M10 3.51621 4.45309 0.790 0.432971
M11 -0.12140 4.38076 -0.028 0.977987
t 0.17860 0.04373 4.085 0.000137 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7.587 on 58 degrees of freedom
Multiple R-squared: 0.4106, Adjusted R-squared: 0.2785
F-statistic: 3.108 on 13 and 58 DF, p-value: 0.001491
> 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,] 9.281522e-04 1.856304e-03 0.9990718
[2,] 3.092471e-04 6.184942e-04 0.9996908
[3,] 3.235678e-05 6.471356e-05 0.9999676
[4,] 2.632873e-05 5.265747e-05 0.9999737
[5,] 1.112941e-05 2.225883e-05 0.9999889
[6,] 1.870003e-06 3.740005e-06 0.9999981
[7,] 1.133874e-06 2.267748e-06 0.9999989
[8,] 2.525550e-07 5.051100e-07 0.9999997
[9,] 7.587109e-08 1.517422e-07 0.9999999
[10,] 1.998546e-08 3.997093e-08 1.0000000
[11,] 5.176997e-09 1.035399e-08 1.0000000
[12,] 5.590914e-09 1.118183e-08 1.0000000
[13,] 5.797482e-09 1.159496e-08 1.0000000
[14,] 3.259177e-09 6.518354e-09 1.0000000
[15,] 1.028110e-07 2.056220e-07 0.9999999
[16,] 1.151464e-07 2.302928e-07 0.9999999
[17,] 8.633360e-08 1.726672e-07 0.9999999
[18,] 3.774220e-08 7.548440e-08 1.0000000
[19,] 1.541236e-08 3.082472e-08 1.0000000
[20,] 6.854350e-09 1.370870e-08 1.0000000
[21,] 5.254962e-08 1.050992e-07 0.9999999
[22,] 2.286033e-07 4.572066e-07 0.9999998
[23,] 3.960151e-07 7.920302e-07 0.9999996
[24,] 2.292810e-06 4.585619e-06 0.9999977
[25,] 1.070993e-05 2.141985e-05 0.9999893
[26,] 4.343555e-05 8.687109e-05 0.9999566
[27,] 5.619411e-04 1.123882e-03 0.9994381
[28,] 1.122112e-02 2.244225e-02 0.9887789
[29,] 4.898820e-02 9.797639e-02 0.9510118
[30,] 1.205921e-01 2.411842e-01 0.8794079
[31,] 2.862946e-01 5.725893e-01 0.7137054
[32,] 4.888763e-01 9.777526e-01 0.5111237
[33,] 7.508418e-01 4.983165e-01 0.2491582
[34,] 8.446858e-01 3.106284e-01 0.1553142
[35,] 8.677206e-01 2.645588e-01 0.1322794
[36,] 8.814271e-01 2.371457e-01 0.1185729
[37,] 8.072495e-01 3.855011e-01 0.1927505
[38,] 7.743667e-01 4.512665e-01 0.2256333
[39,] 6.637856e-01 6.724288e-01 0.3362144
> postscript(file="/var/www/html/rcomp/tmp/1pr6p1228490759.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2obl21228490759.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3gesp1228490759.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4cg2f1228490759.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5qerd1228490759.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 = 72
Frequency = 1
1 2 3 4 5 6
-9.5087040 -9.0087040 -8.3420373 -8.6753706 -8.4420373 -8.3420373
7 8 9 10 11 12
-6.6469632 -7.6010521 -6.8420373 -5.0010521 -3.5420373 -3.2420373
13 14 15 16 17 18
-3.0518890 -2.7518890 -2.4852224 -1.2185557 -1.3852224 -0.2852224
19 20 21 22 23 24
1.0557628 1.2557628 2.0147776 2.0557628 1.9147776 3.2147776
25 26 27 28 29 30
3.4049259 3.9049259 4.3715925 3.6382592 3.6715925 4.7715925
31 32 33 34 35 36
3.9125777 5.8666667 6.8715925 9.1125777 9.1715925 9.0715925
37 38 39 40 41 42
7.0617408 7.3617408 8.0284075 7.2950741 7.5284075 7.8284075
43 44 45 46 47 48
7.1693926 6.7693926 7.7284075 7.1693926 7.2284075 7.3284075
49 50 51 52 53 54
5.3185557 5.4185557 5.0852224 5.3518890 6.5852224 6.4852224
55 56 57 58 59 60
4.8262076 4.0262076 3.9852224 0.7802965 -0.7147776 -2.8147776
61 62 63 64 65 66
-3.2246294 -4.9246294 -6.6579627 -6.3912960 -7.9579627 -10.4579627
67 68 69 70 71 72
-10.3169775 -10.3169775 -13.7579627 -14.1169775 -14.0579627 -13.5579627
> postscript(file="/var/www/html/rcomp/tmp/6opwg1228490759.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 = 72
Frequency = 1
lag(myerror, k = 1) myerror
0 -9.5087040 NA
1 -9.0087040 -9.5087040
2 -8.3420373 -9.0087040
3 -8.6753706 -8.3420373
4 -8.4420373 -8.6753706
5 -8.3420373 -8.4420373
6 -6.6469632 -8.3420373
7 -7.6010521 -6.6469632
8 -6.8420373 -7.6010521
9 -5.0010521 -6.8420373
10 -3.5420373 -5.0010521
11 -3.2420373 -3.5420373
12 -3.0518890 -3.2420373
13 -2.7518890 -3.0518890
14 -2.4852224 -2.7518890
15 -1.2185557 -2.4852224
16 -1.3852224 -1.2185557
17 -0.2852224 -1.3852224
18 1.0557628 -0.2852224
19 1.2557628 1.0557628
20 2.0147776 1.2557628
21 2.0557628 2.0147776
22 1.9147776 2.0557628
23 3.2147776 1.9147776
24 3.4049259 3.2147776
25 3.9049259 3.4049259
26 4.3715925 3.9049259
27 3.6382592 4.3715925
28 3.6715925 3.6382592
29 4.7715925 3.6715925
30 3.9125777 4.7715925
31 5.8666667 3.9125777
32 6.8715925 5.8666667
33 9.1125777 6.8715925
34 9.1715925 9.1125777
35 9.0715925 9.1715925
36 7.0617408 9.0715925
37 7.3617408 7.0617408
38 8.0284075 7.3617408
39 7.2950741 8.0284075
40 7.5284075 7.2950741
41 7.8284075 7.5284075
42 7.1693926 7.8284075
43 6.7693926 7.1693926
44 7.7284075 6.7693926
45 7.1693926 7.7284075
46 7.2284075 7.1693926
47 7.3284075 7.2284075
48 5.3185557 7.3284075
49 5.4185557 5.3185557
50 5.0852224 5.4185557
51 5.3518890 5.0852224
52 6.5852224 5.3518890
53 6.4852224 6.5852224
54 4.8262076 6.4852224
55 4.0262076 4.8262076
56 3.9852224 4.0262076
57 0.7802965 3.9852224
58 -0.7147776 0.7802965
59 -2.8147776 -0.7147776
60 -3.2246294 -2.8147776
61 -4.9246294 -3.2246294
62 -6.6579627 -4.9246294
63 -6.3912960 -6.6579627
64 -7.9579627 -6.3912960
65 -10.4579627 -7.9579627
66 -10.3169775 -10.4579627
67 -10.3169775 -10.3169775
68 -13.7579627 -10.3169775
69 -14.1169775 -13.7579627
70 -14.0579627 -14.1169775
71 -13.5579627 -14.0579627
72 NA -13.5579627
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -9.0087040 -9.5087040
[2,] -8.3420373 -9.0087040
[3,] -8.6753706 -8.3420373
[4,] -8.4420373 -8.6753706
[5,] -8.3420373 -8.4420373
[6,] -6.6469632 -8.3420373
[7,] -7.6010521 -6.6469632
[8,] -6.8420373 -7.6010521
[9,] -5.0010521 -6.8420373
[10,] -3.5420373 -5.0010521
[11,] -3.2420373 -3.5420373
[12,] -3.0518890 -3.2420373
[13,] -2.7518890 -3.0518890
[14,] -2.4852224 -2.7518890
[15,] -1.2185557 -2.4852224
[16,] -1.3852224 -1.2185557
[17,] -0.2852224 -1.3852224
[18,] 1.0557628 -0.2852224
[19,] 1.2557628 1.0557628
[20,] 2.0147776 1.2557628
[21,] 2.0557628 2.0147776
[22,] 1.9147776 2.0557628
[23,] 3.2147776 1.9147776
[24,] 3.4049259 3.2147776
[25,] 3.9049259 3.4049259
[26,] 4.3715925 3.9049259
[27,] 3.6382592 4.3715925
[28,] 3.6715925 3.6382592
[29,] 4.7715925 3.6715925
[30,] 3.9125777 4.7715925
[31,] 5.8666667 3.9125777
[32,] 6.8715925 5.8666667
[33,] 9.1125777 6.8715925
[34,] 9.1715925 9.1125777
[35,] 9.0715925 9.1715925
[36,] 7.0617408 9.0715925
[37,] 7.3617408 7.0617408
[38,] 8.0284075 7.3617408
[39,] 7.2950741 8.0284075
[40,] 7.5284075 7.2950741
[41,] 7.8284075 7.5284075
[42,] 7.1693926 7.8284075
[43,] 6.7693926 7.1693926
[44,] 7.7284075 6.7693926
[45,] 7.1693926 7.7284075
[46,] 7.2284075 7.1693926
[47,] 7.3284075 7.2284075
[48,] 5.3185557 7.3284075
[49,] 5.4185557 5.3185557
[50,] 5.0852224 5.4185557
[51,] 5.3518890 5.0852224
[52,] 6.5852224 5.3518890
[53,] 6.4852224 6.5852224
[54,] 4.8262076 6.4852224
[55,] 4.0262076 4.8262076
[56,] 3.9852224 4.0262076
[57,] 0.7802965 3.9852224
[58,] -0.7147776 0.7802965
[59,] -2.8147776 -0.7147776
[60,] -3.2246294 -2.8147776
[61,] -4.9246294 -3.2246294
[62,] -6.6579627 -4.9246294
[63,] -6.3912960 -6.6579627
[64,] -7.9579627 -6.3912960
[65,] -10.4579627 -7.9579627
[66,] -10.3169775 -10.4579627
[67,] -10.3169775 -10.3169775
[68,] -13.7579627 -10.3169775
[69,] -14.1169775 -13.7579627
[70,] -14.0579627 -14.1169775
[71,] -13.5579627 -14.0579627
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -9.0087040 -9.5087040
2 -8.3420373 -9.0087040
3 -8.6753706 -8.3420373
4 -8.4420373 -8.6753706
5 -8.3420373 -8.4420373
6 -6.6469632 -8.3420373
7 -7.6010521 -6.6469632
8 -6.8420373 -7.6010521
9 -5.0010521 -6.8420373
10 -3.5420373 -5.0010521
11 -3.2420373 -3.5420373
12 -3.0518890 -3.2420373
13 -2.7518890 -3.0518890
14 -2.4852224 -2.7518890
15 -1.2185557 -2.4852224
16 -1.3852224 -1.2185557
17 -0.2852224 -1.3852224
18 1.0557628 -0.2852224
19 1.2557628 1.0557628
20 2.0147776 1.2557628
21 2.0557628 2.0147776
22 1.9147776 2.0557628
23 3.2147776 1.9147776
24 3.4049259 3.2147776
25 3.9049259 3.4049259
26 4.3715925 3.9049259
27 3.6382592 4.3715925
28 3.6715925 3.6382592
29 4.7715925 3.6715925
30 3.9125777 4.7715925
31 5.8666667 3.9125777
32 6.8715925 5.8666667
33 9.1125777 6.8715925
34 9.1715925 9.1125777
35 9.0715925 9.1715925
36 7.0617408 9.0715925
37 7.3617408 7.0617408
38 8.0284075 7.3617408
39 7.2950741 8.0284075
40 7.5284075 7.2950741
41 7.8284075 7.5284075
42 7.1693926 7.8284075
43 6.7693926 7.1693926
44 7.7284075 6.7693926
45 7.1693926 7.7284075
46 7.2284075 7.1693926
47 7.3284075 7.2284075
48 5.3185557 7.3284075
49 5.4185557 5.3185557
50 5.0852224 5.4185557
51 5.3518890 5.0852224
52 6.5852224 5.3518890
53 6.4852224 6.5852224
54 4.8262076 6.4852224
55 4.0262076 4.8262076
56 3.9852224 4.0262076
57 0.7802965 3.9852224
58 -0.7147776 0.7802965
59 -2.8147776 -0.7147776
60 -3.2246294 -2.8147776
61 -4.9246294 -3.2246294
62 -6.6579627 -4.9246294
63 -6.3912960 -6.6579627
64 -7.9579627 -6.3912960
65 -10.4579627 -7.9579627
66 -10.3169775 -10.4579627
67 -10.3169775 -10.3169775
68 -13.7579627 -10.3169775
69 -14.1169775 -13.7579627
70 -14.0579627 -14.1169775
71 -13.5579627 -14.0579627
> 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/7auax1228490759.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/818mw1228490759.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9ptpw1228490759.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10cdv31228490759.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ucvh1228490759.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/12qkhp1228490759.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/13d1741228490759.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/14p8qf1228490759.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/15k5q81228490759.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/16bt961228490760.tab")
+ }
>
> system("convert tmp/1pr6p1228490759.ps tmp/1pr6p1228490759.png")
> system("convert tmp/2obl21228490759.ps tmp/2obl21228490759.png")
> system("convert tmp/3gesp1228490759.ps tmp/3gesp1228490759.png")
> system("convert tmp/4cg2f1228490759.ps tmp/4cg2f1228490759.png")
> system("convert tmp/5qerd1228490759.ps tmp/5qerd1228490759.png")
> system("convert tmp/6opwg1228490759.ps tmp/6opwg1228490759.png")
> system("convert tmp/7auax1228490759.ps tmp/7auax1228490759.png")
> system("convert tmp/818mw1228490759.ps tmp/818mw1228490759.png")
> system("convert tmp/9ptpw1228490759.ps tmp/9ptpw1228490759.png")
> system("convert tmp/10cdv31228490759.ps tmp/10cdv31228490759.png")
>
>
> proc.time()
user system elapsed
2.474 1.568 3.103