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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Type 'demo()' for some demos, 'help()' for on-line help, or
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> x <- array(list(98.6,0,98,0,106.8,0,96.7,0,100.2,0,107.7,0,92,0,98.4,0,107.4,0,117.7,0,105.7,0,97.5,0,99.9,0,98.2,0,104.5,0,100.8,0,101.5,0,103.9,0,99.6,0,98.4,0,112.7,0,118.4,0,108.1,0,105.4,0,114.6,0,106.9,0,115.9,0,109.8,0,101.8,0,114.2,0,110.8,0,108.4,0,127.5,1,128.6,1,116.6,1,127.4,1,105,1,108.3,1,125,1,111.6,1,106.5,1,130.3,1,115,1,116.1,1,134,1,126.5,1,125.8,1,136.4,1,114.9,1,110.9,1,125.5,1,116.8,1,116.8,1,125.5,1,104.2,1,115.1,1,132.8,1,123.3,1,124.8,1,122,1,117.4,1,117.9,1,137.4,1,114.6,1,124.7,1,129.6,1,109.4,1,120.9,1,134.9,1,136.3,1,133.2,1,127.2,1),dim=c(2,72),dimnames=list(c('Y','D'),1:72))
> y <- array(NA,dim=c(2,72),dimnames=list(c('Y','D'),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
Y D M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 98.6 0 1 0 0 0 0 0 0 0 0 0 0 1
2 98.0 0 0 1 0 0 0 0 0 0 0 0 0 2
3 106.8 0 0 0 1 0 0 0 0 0 0 0 0 3
4 96.7 0 0 0 0 1 0 0 0 0 0 0 0 4
5 100.2 0 0 0 0 0 1 0 0 0 0 0 0 5
6 107.7 0 0 0 0 0 0 1 0 0 0 0 0 6
7 92.0 0 0 0 0 0 0 0 1 0 0 0 0 7
8 98.4 0 0 0 0 0 0 0 0 1 0 0 0 8
9 107.4 0 0 0 0 0 0 0 0 0 1 0 0 9
10 117.7 0 0 0 0 0 0 0 0 0 0 1 0 10
11 105.7 0 0 0 0 0 0 0 0 0 0 0 1 11
12 97.5 0 0 0 0 0 0 0 0 0 0 0 0 12
13 99.9 0 1 0 0 0 0 0 0 0 0 0 0 13
14 98.2 0 0 1 0 0 0 0 0 0 0 0 0 14
15 104.5 0 0 0 1 0 0 0 0 0 0 0 0 15
16 100.8 0 0 0 0 1 0 0 0 0 0 0 0 16
17 101.5 0 0 0 0 0 1 0 0 0 0 0 0 17
18 103.9 0 0 0 0 0 0 1 0 0 0 0 0 18
19 99.6 0 0 0 0 0 0 0 1 0 0 0 0 19
20 98.4 0 0 0 0 0 0 0 0 1 0 0 0 20
21 112.7 0 0 0 0 0 0 0 0 0 1 0 0 21
22 118.4 0 0 0 0 0 0 0 0 0 0 1 0 22
23 108.1 0 0 0 0 0 0 0 0 0 0 0 1 23
24 105.4 0 0 0 0 0 0 0 0 0 0 0 0 24
25 114.6 0 1 0 0 0 0 0 0 0 0 0 0 25
26 106.9 0 0 1 0 0 0 0 0 0 0 0 0 26
27 115.9 0 0 0 1 0 0 0 0 0 0 0 0 27
28 109.8 0 0 0 0 1 0 0 0 0 0 0 0 28
29 101.8 0 0 0 0 0 1 0 0 0 0 0 0 29
30 114.2 0 0 0 0 0 0 1 0 0 0 0 0 30
31 110.8 0 0 0 0 0 0 0 1 0 0 0 0 31
32 108.4 0 0 0 0 0 0 0 0 1 0 0 0 32
33 127.5 1 0 0 0 0 0 0 0 0 1 0 0 33
34 128.6 1 0 0 0 0 0 0 0 0 0 1 0 34
35 116.6 1 0 0 0 0 0 0 0 0 0 0 1 35
36 127.4 1 0 0 0 0 0 0 0 0 0 0 0 36
37 105.0 1 1 0 0 0 0 0 0 0 0 0 0 37
38 108.3 1 0 1 0 0 0 0 0 0 0 0 0 38
39 125.0 1 0 0 1 0 0 0 0 0 0 0 0 39
40 111.6 1 0 0 0 1 0 0 0 0 0 0 0 40
41 106.5 1 0 0 0 0 1 0 0 0 0 0 0 41
42 130.3 1 0 0 0 0 0 1 0 0 0 0 0 42
43 115.0 1 0 0 0 0 0 0 1 0 0 0 0 43
44 116.1 1 0 0 0 0 0 0 0 1 0 0 0 44
45 134.0 1 0 0 0 0 0 0 0 0 1 0 0 45
46 126.5 1 0 0 0 0 0 0 0 0 0 1 0 46
47 125.8 1 0 0 0 0 0 0 0 0 0 0 1 47
48 136.4 1 0 0 0 0 0 0 0 0 0 0 0 48
49 114.9 1 1 0 0 0 0 0 0 0 0 0 0 49
50 110.9 1 0 1 0 0 0 0 0 0 0 0 0 50
51 125.5 1 0 0 1 0 0 0 0 0 0 0 0 51
52 116.8 1 0 0 0 1 0 0 0 0 0 0 0 52
53 116.8 1 0 0 0 0 1 0 0 0 0 0 0 53
54 125.5 1 0 0 0 0 0 1 0 0 0 0 0 54
55 104.2 1 0 0 0 0 0 0 1 0 0 0 0 55
56 115.1 1 0 0 0 0 0 0 0 1 0 0 0 56
57 132.8 1 0 0 0 0 0 0 0 0 1 0 0 57
58 123.3 1 0 0 0 0 0 0 0 0 0 1 0 58
59 124.8 1 0 0 0 0 0 0 0 0 0 0 1 59
60 122.0 1 0 0 0 0 0 0 0 0 0 0 0 60
61 117.4 1 1 0 0 0 0 0 0 0 0 0 0 61
62 117.9 1 0 1 0 0 0 0 0 0 0 0 0 62
63 137.4 1 0 0 1 0 0 0 0 0 0 0 0 63
64 114.6 1 0 0 0 1 0 0 0 0 0 0 0 64
65 124.7 1 0 0 0 0 1 0 0 0 0 0 0 65
66 129.6 1 0 0 0 0 0 1 0 0 0 0 0 66
67 109.4 1 0 0 0 0 0 0 1 0 0 0 0 67
68 120.9 1 0 0 0 0 0 0 0 1 0 0 0 68
69 134.9 1 0 0 0 0 0 0 0 0 1 0 0 69
70 136.3 1 0 0 0 0 0 0 0 0 0 1 0 70
71 133.2 1 0 0 0 0 0 0 0 0 0 0 1 71
72 127.2 1 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) D M1 M2 M3 M4
1.038e+02 5.362e+00 -6.906e+00 -8.890e+00 3.310e+00 -7.773e+00
M5 M6 M7 M8 M9 M10
-7.856e+00 1.810e+00 -1.184e+01 -7.740e+00 6.417e+00 6.383e+00
M11 t
-6.246e-15 2.833e-01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-9.74231 -2.40288 -0.04744 2.49295 13.59615
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.038e+02 2.464e+00 42.140 < 2e-16 ***
D 5.362e+00 2.413e+00 2.222 0.030206 *
M1 -6.906e+00 2.962e+00 -2.331 0.023233 *
M2 -8.890e+00 2.957e+00 -3.006 0.003908 **
M3 3.310e+00 2.953e+00 1.121 0.266983
M4 -7.773e+00 2.951e+00 -2.634 0.010790 *
M5 -7.856e+00 2.949e+00 -2.664 0.009976 **
M6 1.810e+00 2.948e+00 0.614 0.541620
M7 -1.184e+01 2.949e+00 -4.015 0.000173 ***
M8 -7.740e+00 2.951e+00 -2.623 0.011114 *
M9 6.417e+00 2.946e+00 2.178 0.033499 *
M10 6.383e+00 2.944e+00 2.169 0.034228 *
M11 -6.246e-15 2.942e+00 -2.12e-15 1.000000
t 2.833e-01 5.777e-02 4.904 7.93e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5.094 on 58 degrees of freedom
Multiple R-squared: 0.847, Adjusted R-squared: 0.8127
F-statistic: 24.69 on 13 and 58 DF, p-value: < 2.2e-16
> 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,] 0.051841883 0.10368377 0.94815812
[2,] 0.049960014 0.09992003 0.95003999
[3,] 0.090106430 0.18021286 0.90989357
[4,] 0.045196505 0.09039301 0.95480350
[5,] 0.035610293 0.07122059 0.96438971
[6,] 0.016106551 0.03221310 0.98389345
[7,] 0.007760993 0.01552199 0.99223901
[8,] 0.018214738 0.03642948 0.98178526
[9,] 0.160694085 0.32138817 0.83930592
[10,] 0.121856006 0.24371201 0.87814399
[11,] 0.102846676 0.20569335 0.89715332
[12,] 0.086904368 0.17380874 0.91309563
[13,] 0.098666584 0.19733317 0.90133342
[14,] 0.088669056 0.17733811 0.91133094
[15,] 0.143190992 0.28638198 0.85680901
[16,] 0.103900383 0.20780077 0.89609962
[17,] 0.069384458 0.13876892 0.93061554
[18,] 0.066606413 0.13321283 0.93339359
[19,] 0.060558636 0.12111727 0.93944136
[20,] 0.138627878 0.27725576 0.86137212
[21,] 0.419289155 0.83857831 0.58071085
[22,] 0.393365403 0.78673081 0.60663460
[23,] 0.330834050 0.66166810 0.66916595
[24,] 0.272834629 0.54566926 0.72716537
[25,] 0.404644427 0.80928885 0.59535557
[26,] 0.431963661 0.86392732 0.56803634
[27,] 0.533890738 0.93221852 0.46610926
[28,] 0.447840619 0.89568124 0.55215938
[29,] 0.415778004 0.83155601 0.58422200
[30,] 0.368244386 0.73648877 0.63175561
[31,] 0.291963063 0.58392613 0.70803694
[32,] 0.955960569 0.08807886 0.04403943
[33,] 0.939413333 0.12117333 0.06058667
[34,] 0.904566930 0.19086614 0.09543307
[35,] 0.904706679 0.19058664 0.09529332
[36,] 0.957903702 0.08419260 0.04209630
[37,] 0.913454952 0.17309010 0.08654505
[38,] 0.844649578 0.31070084 0.15535042
[39,] 0.757554657 0.48489069 0.24244534
> postscript(file="/var/www/html/freestat/rcomp/tmp/1yz7d1227547524.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2ncbe1227547524.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3vgs01227547524.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4joyo1227547524.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5hzsa1227547524.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
1.38076923 2.48076923 -1.20256410 -0.50256410 2.79743590 0.34743590
7 8 9 10 11 12
-1.98589744 0.03076923 -5.40897436 4.64102564 -1.25897436 -9.74230769
13 14 15 16 17 18
-0.71923077 -0.71923077 -6.90256410 0.19743590 0.69743590 -6.85256410
19 20 21 22 23 24
2.21410256 -3.36923077 -3.50897436 1.94102564 -2.25897436 -5.24230769
25 26 27 28 29 30
10.58076923 4.58076923 1.09743590 5.79743590 -2.40256410 0.04743590
31 32 33 34 35 36
10.01410256 3.23076923 2.52948718 3.37948718 -2.52051282 7.99615385
37 38 39 40 41 42
-7.78076923 -2.78076923 1.43589744 -1.16410256 -6.46410256 7.38589744
43 44 45 46 47 48
5.45256410 2.16923077 5.62948718 -2.12051282 3.27948718 13.59615385
49 50 51 52 53 54
-1.28076923 -3.58076923 -1.46410256 0.63589744 0.43589744 -0.81410256
55 56 57 58 59 60
-8.74743590 -2.23076923 1.02948718 -8.72051282 -1.12051282 -4.20384615
61 62 63 64 65 66
-2.18076923 0.01923077 7.03589744 -4.96410256 4.93589744 -0.11410256
67 68 69 70 71 72
-6.94743590 0.16923077 -0.27051282 0.87948718 3.87948718 -2.40384615
> postscript(file="/var/www/html/freestat/rcomp/tmp/6ks411227547524.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 1.38076923 NA
1 2.48076923 1.38076923
2 -1.20256410 2.48076923
3 -0.50256410 -1.20256410
4 2.79743590 -0.50256410
5 0.34743590 2.79743590
6 -1.98589744 0.34743590
7 0.03076923 -1.98589744
8 -5.40897436 0.03076923
9 4.64102564 -5.40897436
10 -1.25897436 4.64102564
11 -9.74230769 -1.25897436
12 -0.71923077 -9.74230769
13 -0.71923077 -0.71923077
14 -6.90256410 -0.71923077
15 0.19743590 -6.90256410
16 0.69743590 0.19743590
17 -6.85256410 0.69743590
18 2.21410256 -6.85256410
19 -3.36923077 2.21410256
20 -3.50897436 -3.36923077
21 1.94102564 -3.50897436
22 -2.25897436 1.94102564
23 -5.24230769 -2.25897436
24 10.58076923 -5.24230769
25 4.58076923 10.58076923
26 1.09743590 4.58076923
27 5.79743590 1.09743590
28 -2.40256410 5.79743590
29 0.04743590 -2.40256410
30 10.01410256 0.04743590
31 3.23076923 10.01410256
32 2.52948718 3.23076923
33 3.37948718 2.52948718
34 -2.52051282 3.37948718
35 7.99615385 -2.52051282
36 -7.78076923 7.99615385
37 -2.78076923 -7.78076923
38 1.43589744 -2.78076923
39 -1.16410256 1.43589744
40 -6.46410256 -1.16410256
41 7.38589744 -6.46410256
42 5.45256410 7.38589744
43 2.16923077 5.45256410
44 5.62948718 2.16923077
45 -2.12051282 5.62948718
46 3.27948718 -2.12051282
47 13.59615385 3.27948718
48 -1.28076923 13.59615385
49 -3.58076923 -1.28076923
50 -1.46410256 -3.58076923
51 0.63589744 -1.46410256
52 0.43589744 0.63589744
53 -0.81410256 0.43589744
54 -8.74743590 -0.81410256
55 -2.23076923 -8.74743590
56 1.02948718 -2.23076923
57 -8.72051282 1.02948718
58 -1.12051282 -8.72051282
59 -4.20384615 -1.12051282
60 -2.18076923 -4.20384615
61 0.01923077 -2.18076923
62 7.03589744 0.01923077
63 -4.96410256 7.03589744
64 4.93589744 -4.96410256
65 -0.11410256 4.93589744
66 -6.94743590 -0.11410256
67 0.16923077 -6.94743590
68 -0.27051282 0.16923077
69 0.87948718 -0.27051282
70 3.87948718 0.87948718
71 -2.40384615 3.87948718
72 NA -2.40384615
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 2.48076923 1.38076923
[2,] -1.20256410 2.48076923
[3,] -0.50256410 -1.20256410
[4,] 2.79743590 -0.50256410
[5,] 0.34743590 2.79743590
[6,] -1.98589744 0.34743590
[7,] 0.03076923 -1.98589744
[8,] -5.40897436 0.03076923
[9,] 4.64102564 -5.40897436
[10,] -1.25897436 4.64102564
[11,] -9.74230769 -1.25897436
[12,] -0.71923077 -9.74230769
[13,] -0.71923077 -0.71923077
[14,] -6.90256410 -0.71923077
[15,] 0.19743590 -6.90256410
[16,] 0.69743590 0.19743590
[17,] -6.85256410 0.69743590
[18,] 2.21410256 -6.85256410
[19,] -3.36923077 2.21410256
[20,] -3.50897436 -3.36923077
[21,] 1.94102564 -3.50897436
[22,] -2.25897436 1.94102564
[23,] -5.24230769 -2.25897436
[24,] 10.58076923 -5.24230769
[25,] 4.58076923 10.58076923
[26,] 1.09743590 4.58076923
[27,] 5.79743590 1.09743590
[28,] -2.40256410 5.79743590
[29,] 0.04743590 -2.40256410
[30,] 10.01410256 0.04743590
[31,] 3.23076923 10.01410256
[32,] 2.52948718 3.23076923
[33,] 3.37948718 2.52948718
[34,] -2.52051282 3.37948718
[35,] 7.99615385 -2.52051282
[36,] -7.78076923 7.99615385
[37,] -2.78076923 -7.78076923
[38,] 1.43589744 -2.78076923
[39,] -1.16410256 1.43589744
[40,] -6.46410256 -1.16410256
[41,] 7.38589744 -6.46410256
[42,] 5.45256410 7.38589744
[43,] 2.16923077 5.45256410
[44,] 5.62948718 2.16923077
[45,] -2.12051282 5.62948718
[46,] 3.27948718 -2.12051282
[47,] 13.59615385 3.27948718
[48,] -1.28076923 13.59615385
[49,] -3.58076923 -1.28076923
[50,] -1.46410256 -3.58076923
[51,] 0.63589744 -1.46410256
[52,] 0.43589744 0.63589744
[53,] -0.81410256 0.43589744
[54,] -8.74743590 -0.81410256
[55,] -2.23076923 -8.74743590
[56,] 1.02948718 -2.23076923
[57,] -8.72051282 1.02948718
[58,] -1.12051282 -8.72051282
[59,] -4.20384615 -1.12051282
[60,] -2.18076923 -4.20384615
[61,] 0.01923077 -2.18076923
[62,] 7.03589744 0.01923077
[63,] -4.96410256 7.03589744
[64,] 4.93589744 -4.96410256
[65,] -0.11410256 4.93589744
[66,] -6.94743590 -0.11410256
[67,] 0.16923077 -6.94743590
[68,] -0.27051282 0.16923077
[69,] 0.87948718 -0.27051282
[70,] 3.87948718 0.87948718
[71,] -2.40384615 3.87948718
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 2.48076923 1.38076923
2 -1.20256410 2.48076923
3 -0.50256410 -1.20256410
4 2.79743590 -0.50256410
5 0.34743590 2.79743590
6 -1.98589744 0.34743590
7 0.03076923 -1.98589744
8 -5.40897436 0.03076923
9 4.64102564 -5.40897436
10 -1.25897436 4.64102564
11 -9.74230769 -1.25897436
12 -0.71923077 -9.74230769
13 -0.71923077 -0.71923077
14 -6.90256410 -0.71923077
15 0.19743590 -6.90256410
16 0.69743590 0.19743590
17 -6.85256410 0.69743590
18 2.21410256 -6.85256410
19 -3.36923077 2.21410256
20 -3.50897436 -3.36923077
21 1.94102564 -3.50897436
22 -2.25897436 1.94102564
23 -5.24230769 -2.25897436
24 10.58076923 -5.24230769
25 4.58076923 10.58076923
26 1.09743590 4.58076923
27 5.79743590 1.09743590
28 -2.40256410 5.79743590
29 0.04743590 -2.40256410
30 10.01410256 0.04743590
31 3.23076923 10.01410256
32 2.52948718 3.23076923
33 3.37948718 2.52948718
34 -2.52051282 3.37948718
35 7.99615385 -2.52051282
36 -7.78076923 7.99615385
37 -2.78076923 -7.78076923
38 1.43589744 -2.78076923
39 -1.16410256 1.43589744
40 -6.46410256 -1.16410256
41 7.38589744 -6.46410256
42 5.45256410 7.38589744
43 2.16923077 5.45256410
44 5.62948718 2.16923077
45 -2.12051282 5.62948718
46 3.27948718 -2.12051282
47 13.59615385 3.27948718
48 -1.28076923 13.59615385
49 -3.58076923 -1.28076923
50 -1.46410256 -3.58076923
51 0.63589744 -1.46410256
52 0.43589744 0.63589744
53 -0.81410256 0.43589744
54 -8.74743590 -0.81410256
55 -2.23076923 -8.74743590
56 1.02948718 -2.23076923
57 -8.72051282 1.02948718
58 -1.12051282 -8.72051282
59 -4.20384615 -1.12051282
60 -2.18076923 -4.20384615
61 0.01923077 -2.18076923
62 7.03589744 0.01923077
63 -4.96410256 7.03589744
64 4.93589744 -4.96410256
65 -0.11410256 4.93589744
66 -6.94743590 -0.11410256
67 0.16923077 -6.94743590
68 -0.27051282 0.16923077
69 0.87948718 -0.27051282
70 3.87948718 0.87948718
71 -2.40384615 3.87948718
> 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/7eyh91227547524.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8wb7o1227547524.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9n6721227547524.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/106un41227547524.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11dtzz1227547524.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/12s3p11227547524.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/1318uz1227547524.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/14i3ck1227547524.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/15e0u71227547524.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/16ihut1227547525.tab")
+ }
>
> system("convert tmp/1yz7d1227547524.ps tmp/1yz7d1227547524.png")
> system("convert tmp/2ncbe1227547524.ps tmp/2ncbe1227547524.png")
> system("convert tmp/3vgs01227547524.ps tmp/3vgs01227547524.png")
> system("convert tmp/4joyo1227547524.ps tmp/4joyo1227547524.png")
> system("convert tmp/5hzsa1227547524.ps tmp/5hzsa1227547524.png")
> system("convert tmp/6ks411227547524.ps tmp/6ks411227547524.png")
> system("convert tmp/7eyh91227547524.ps tmp/7eyh91227547524.png")
> system("convert tmp/8wb7o1227547524.ps tmp/8wb7o1227547524.png")
> system("convert tmp/9n6721227547524.ps tmp/9n6721227547524.png")
> system("convert tmp/106un41227547524.ps tmp/106un41227547524.png")
>
>
> proc.time()
user system elapsed
3.936 2.547 4.559