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(100,0,100,0,100,0,100.1,0,100,0,100,0,99.8,0,100,0,99.9,0,99.2,0,98.7,0,98.7,0,98.9,1,99.2,1,99.8,1,100.5,1,100.1,1,100.5,1,98.4,1,98.6,1,99,1,99.1,1,98.9,1,98.5,1,96.9,1,96.8,1,97,1,97,1,96.9,1,97.1,1,97.2,1,97.9,1,98.9,1,99.2,1,99.5,1,99.3,1,99.9,1,100,1,100.3,1,100.5,1,100.7,1,100.9,1,100.8,1,100.9,1,101,1,100.3,1,100.1,1,99.8,1,99.9,1,99.9,1,100.2,1,99.7,1,100.4,1,100.9,1,101.3,1,101.4,1,101.3,1,100.9,1,100.9,1,100.9,1,101.1,1,101.1,1,101.3,1,101.8,1,102.9,1,103.2,1,103.3,1,104.5,1,105,1,104.9,1,104.9,1,105.4,1,106,1,105.7,1,105.9,1,106.2,1,106.4,1,106.9,1,107.3,1,107.9,1,109.2,1,110.2,1,110.2,1,110.5,1,110.6,1,110.8,1,111.3,1,111.1,1,111.2,1,111.2,1,111.1,1,111.5,1,112.1,1,111.4,1),dim=c(2,94),dimnames=list(c('y','x'),1:94))
> y <- array(NA,dim=c(2,94),dimnames=list(c('y','x'),1:94))
> 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 x M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 100.0 0 1 0 0 0 0 0 0 0 0 0 0 1
2 100.0 0 0 1 0 0 0 0 0 0 0 0 0 2
3 100.0 0 0 0 1 0 0 0 0 0 0 0 0 3
4 100.1 0 0 0 0 1 0 0 0 0 0 0 0 4
5 100.0 0 0 0 0 0 1 0 0 0 0 0 0 5
6 100.0 0 0 0 0 0 0 1 0 0 0 0 0 6
7 99.8 0 0 0 0 0 0 0 1 0 0 0 0 7
8 100.0 0 0 0 0 0 0 0 0 1 0 0 0 8
9 99.9 0 0 0 0 0 0 0 0 0 1 0 0 9
10 99.2 0 0 0 0 0 0 0 0 0 0 1 0 10
11 98.7 0 0 0 0 0 0 0 0 0 0 0 1 11
12 98.7 0 0 0 0 0 0 0 0 0 0 0 0 12
13 98.9 1 1 0 0 0 0 0 0 0 0 0 0 13
14 99.2 1 0 1 0 0 0 0 0 0 0 0 0 14
15 99.8 1 0 0 1 0 0 0 0 0 0 0 0 15
16 100.5 1 0 0 0 1 0 0 0 0 0 0 0 16
17 100.1 1 0 0 0 0 1 0 0 0 0 0 0 17
18 100.5 1 0 0 0 0 0 1 0 0 0 0 0 18
19 98.4 1 0 0 0 0 0 0 1 0 0 0 0 19
20 98.6 1 0 0 0 0 0 0 0 1 0 0 0 20
21 99.0 1 0 0 0 0 0 0 0 0 1 0 0 21
22 99.1 1 0 0 0 0 0 0 0 0 0 1 0 22
23 98.9 1 0 0 0 0 0 0 0 0 0 0 1 23
24 98.5 1 0 0 0 0 0 0 0 0 0 0 0 24
25 96.9 1 1 0 0 0 0 0 0 0 0 0 0 25
26 96.8 1 0 1 0 0 0 0 0 0 0 0 0 26
27 97.0 1 0 0 1 0 0 0 0 0 0 0 0 27
28 97.0 1 0 0 0 1 0 0 0 0 0 0 0 28
29 96.9 1 0 0 0 0 1 0 0 0 0 0 0 29
30 97.1 1 0 0 0 0 0 1 0 0 0 0 0 30
31 97.2 1 0 0 0 0 0 0 1 0 0 0 0 31
32 97.9 1 0 0 0 0 0 0 0 1 0 0 0 32
33 98.9 1 0 0 0 0 0 0 0 0 1 0 0 33
34 99.2 1 0 0 0 0 0 0 0 0 0 1 0 34
35 99.5 1 0 0 0 0 0 0 0 0 0 0 1 35
36 99.3 1 0 0 0 0 0 0 0 0 0 0 0 36
37 99.9 1 1 0 0 0 0 0 0 0 0 0 0 37
38 100.0 1 0 1 0 0 0 0 0 0 0 0 0 38
39 100.3 1 0 0 1 0 0 0 0 0 0 0 0 39
40 100.5 1 0 0 0 1 0 0 0 0 0 0 0 40
41 100.7 1 0 0 0 0 1 0 0 0 0 0 0 41
42 100.9 1 0 0 0 0 0 1 0 0 0 0 0 42
43 100.8 1 0 0 0 0 0 0 1 0 0 0 0 43
44 100.9 1 0 0 0 0 0 0 0 1 0 0 0 44
45 101.0 1 0 0 0 0 0 0 0 0 1 0 0 45
46 100.3 1 0 0 0 0 0 0 0 0 0 1 0 46
47 100.1 1 0 0 0 0 0 0 0 0 0 0 1 47
48 99.8 1 0 0 0 0 0 0 0 0 0 0 0 48
49 99.9 1 1 0 0 0 0 0 0 0 0 0 0 49
50 99.9 1 0 1 0 0 0 0 0 0 0 0 0 50
51 100.2 1 0 0 1 0 0 0 0 0 0 0 0 51
52 99.7 1 0 0 0 1 0 0 0 0 0 0 0 52
53 100.4 1 0 0 0 0 1 0 0 0 0 0 0 53
54 100.9 1 0 0 0 0 0 1 0 0 0 0 0 54
55 101.3 1 0 0 0 0 0 0 1 0 0 0 0 55
56 101.4 1 0 0 0 0 0 0 0 1 0 0 0 56
57 101.3 1 0 0 0 0 0 0 0 0 1 0 0 57
58 100.9 1 0 0 0 0 0 0 0 0 0 1 0 58
59 100.9 1 0 0 0 0 0 0 0 0 0 0 1 59
60 100.9 1 0 0 0 0 0 0 0 0 0 0 0 60
61 101.1 1 1 0 0 0 0 0 0 0 0 0 0 61
62 101.1 1 0 1 0 0 0 0 0 0 0 0 0 62
63 101.3 1 0 0 1 0 0 0 0 0 0 0 0 63
64 101.8 1 0 0 0 1 0 0 0 0 0 0 0 64
65 102.9 1 0 0 0 0 1 0 0 0 0 0 0 65
66 103.2 1 0 0 0 0 0 1 0 0 0 0 0 66
67 103.3 1 0 0 0 0 0 0 1 0 0 0 0 67
68 104.5 1 0 0 0 0 0 0 0 1 0 0 0 68
69 105.0 1 0 0 0 0 0 0 0 0 1 0 0 69
70 104.9 1 0 0 0 0 0 0 0 0 0 1 0 70
71 104.9 1 0 0 0 0 0 0 0 0 0 0 1 71
72 105.4 1 0 0 0 0 0 0 0 0 0 0 0 72
73 106.0 1 1 0 0 0 0 0 0 0 0 0 0 73
74 105.7 1 0 1 0 0 0 0 0 0 0 0 0 74
75 105.9 1 0 0 1 0 0 0 0 0 0 0 0 75
76 106.2 1 0 0 0 1 0 0 0 0 0 0 0 76
77 106.4 1 0 0 0 0 1 0 0 0 0 0 0 77
78 106.9 1 0 0 0 0 0 1 0 0 0 0 0 78
79 107.3 1 0 0 0 0 0 0 1 0 0 0 0 79
80 107.9 1 0 0 0 0 0 0 0 1 0 0 0 80
81 109.2 1 0 0 0 0 0 0 0 0 1 0 0 81
82 110.2 1 0 0 0 0 0 0 0 0 0 1 0 82
83 110.2 1 0 0 0 0 0 0 0 0 0 0 1 83
84 110.5 1 0 0 0 0 0 0 0 0 0 0 0 84
85 110.6 1 1 0 0 0 0 0 0 0 0 0 0 85
86 110.8 1 0 1 0 0 0 0 0 0 0 0 0 86
87 111.3 1 0 0 1 0 0 0 0 0 0 0 0 87
88 111.1 1 0 0 0 1 0 0 0 0 0 0 0 88
89 111.2 1 0 0 0 0 1 0 0 0 0 0 0 89
90 111.2 1 0 0 0 0 0 1 0 0 0 0 0 90
91 111.1 1 0 0 0 0 0 0 1 0 0 0 0 91
92 111.5 1 0 0 0 0 0 0 0 1 0 0 0 92
93 112.1 1 0 0 0 0 0 0 0 0 1 0 0 93
94 111.4 1 0 0 0 0 0 0 0 0 0 1 0 94
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) x M1 M2 M3 M4
97.9817 -5.0488 0.7372 0.5910 0.7073 0.6736
M5 M6 M7 M8 M9 M10
0.7149 0.8062 0.4475 0.7138 1.0052 0.6840
M11 t
0.1855 0.1712
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-3.1254 -1.3503 -0.1797 1.4648 4.1544
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 97.981732 0.912832 107.338 < 2e-16 ***
x -5.048788 0.748778 -6.743 2.20e-09 ***
M1 0.737190 1.021858 0.721 0.473
M2 0.590997 1.021411 0.579 0.564
M3 0.707305 1.021047 0.693 0.490
M4 0.673613 1.020767 0.660 0.511
M5 0.714921 1.020571 0.701 0.486
M6 0.806228 1.020458 0.790 0.432
M7 0.447536 1.020430 0.439 0.662
M8 0.713844 1.020485 0.700 0.486
M9 1.005152 1.020624 0.985 0.328
M10 0.683959 1.020848 0.670 0.505
M11 0.185478 1.053875 0.176 0.861
t 0.171192 0.009252 18.504 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.972 on 80 degrees of freedom
Multiple R-squared: 0.8236, Adjusted R-squared: 0.7949
F-statistic: 28.73 on 13 and 80 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,] 2.871359e-02 5.742718e-02 0.971286409
[2,] 1.461809e-02 2.923617e-02 0.985381914
[3,] 1.226244e-02 2.452489e-02 0.987737556
[4,] 8.094039e-03 1.618808e-02 0.991905961
[5,] 3.319246e-03 6.638491e-03 0.996680754
[6,] 1.469034e-03 2.938068e-03 0.998530966
[7,] 8.431789e-04 1.686358e-03 0.999156821
[8,] 3.548584e-04 7.097169e-04 0.999645142
[9,] 1.131258e-04 2.262516e-04 0.999886874
[10,] 3.608077e-05 7.216153e-05 0.999963919
[11,] 1.116219e-05 2.232438e-05 0.999988838
[12,] 4.556362e-06 9.112724e-06 0.999995444
[13,] 1.353488e-06 2.706975e-06 0.999998647
[14,] 3.777554e-07 7.555108e-07 0.999999622
[15,] 4.910452e-07 9.820904e-07 0.999999509
[16,] 1.425567e-06 2.851133e-06 0.999998574
[17,] 1.746937e-05 3.493873e-05 0.999982531
[18,] 1.957757e-04 3.915514e-04 0.999804224
[19,] 1.933339e-03 3.866677e-03 0.998066661
[20,] 6.357285e-03 1.271457e-02 0.993642715
[21,] 4.694441e-02 9.388883e-02 0.953055587
[22,] 1.104397e-01 2.208794e-01 0.889560318
[23,] 1.854900e-01 3.709799e-01 0.814510034
[24,] 2.822137e-01 5.644275e-01 0.717786259
[25,] 4.129664e-01 8.259328e-01 0.587033615
[26,] 5.628964e-01 8.742071e-01 0.437103558
[27,] 7.423694e-01 5.152612e-01 0.257630604
[28,] 8.544335e-01 2.911330e-01 0.145566482
[29,] 9.173361e-01 1.653278e-01 0.082663905
[30,] 9.431140e-01 1.137720e-01 0.056885998
[31,] 9.541331e-01 9.173375e-02 0.045866875
[32,] 9.541200e-01 9.176000e-02 0.045879999
[33,] 9.518112e-01 9.637762e-02 0.048188812
[34,] 9.531618e-01 9.367633e-02 0.046838165
[35,] 9.581477e-01 8.370456e-02 0.041852278
[36,] 9.525199e-01 9.496027e-02 0.047480133
[37,] 9.517104e-01 9.657924e-02 0.048289618
[38,] 9.623549e-01 7.529015e-02 0.037645073
[39,] 9.852476e-01 2.950478e-02 0.014752392
[40,] 9.917344e-01 1.653112e-02 0.008265560
[41,] 9.901513e-01 1.969733e-02 0.009848666
[42,] 9.853794e-01 2.924124e-02 0.014620620
[43,] 9.770478e-01 4.590430e-02 0.022952150
[44,] 9.694213e-01 6.115730e-02 0.030578651
[45,] 9.627235e-01 7.455302e-02 0.037276512
[46,] 9.552668e-01 8.946631e-02 0.044733155
[47,] 9.542501e-01 9.149979e-02 0.045749893
[48,] 9.429060e-01 1.141881e-01 0.057094027
[49,] 9.226742e-01 1.546517e-01 0.077325835
[50,] 8.956411e-01 2.087178e-01 0.104358880
[51,] 8.673397e-01 2.653206e-01 0.132660301
[52,] 8.769852e-01 2.460295e-01 0.123014769
[53,] 8.677228e-01 2.645544e-01 0.132277177
[54,] 8.471291e-01 3.057418e-01 0.152870896
[55,] 8.428500e-01 3.143001e-01 0.157150046
[56,] 8.364183e-01 3.271634e-01 0.163581683
[57,] 7.961771e-01 4.076458e-01 0.203822880
[58,] 7.640701e-01 4.718598e-01 0.235929879
[59,] 7.672668e-01 4.654664e-01 0.232733218
[60,] 7.306187e-01 5.387626e-01 0.269381284
[61,] 6.976825e-01 6.046351e-01 0.302317539
> postscript(file="/var/www/html/rcomp/tmp/1u0l91228940300.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/232kv1228940300.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3r44k1228940300.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4y14r1228940300.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5nin01228940300.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 = 94
Frequency = 1
1 2 3 4 5 6
1.10988636 1.08488636 0.79738636 0.75988636 0.44738636 0.18488636
7 8 9 10 11 12
0.17238636 -0.06511364 -0.62761364 -1.17761364 -1.35032468 -1.33603896
13 14 15 16 17 18
3.00436688 3.27936688 3.59186688 4.15436688 3.54186688 3.67936688
19 20 21 22 23 24
1.76686688 1.52936688 1.46686688 1.71686688 1.84415584 1.45844156
25 26 27 28 29 30
-1.04994048 -1.17494048 -1.26244048 -1.39994048 -1.71244048 -1.77494048
31 32 33 34 35 36
-1.48744048 -1.22494048 -0.68744048 -0.23744048 0.38984848 0.20413420
37 38 39 40 41 42
-0.10424784 -0.02924784 -0.01674784 0.04575216 0.03325216 -0.02924784
43 44 45 46 47 48
0.05825216 -0.27924784 -0.64174784 -1.19174784 -1.06445887 -1.35017316
49 50 51 52 53 54
-2.15855519 -2.18355519 -2.17105519 -2.80855519 -2.32105519 -2.08355519
55 56 57 58 59 60
-1.49605519 -1.83355519 -2.39605519 -2.64605519 -2.31876623 -2.30448052
61 62 63 64 65 66
-3.01286255 -3.03786255 -3.12536255 -2.76286255 -1.87536255 -1.83786255
67 68 69 70 71 72
-1.55036255 -0.78786255 -0.75036255 -0.70036255 -0.37307359 0.14121212
73 74 75 76 77 78
-0.16716991 -0.49216991 -0.57966991 -0.41716991 -0.42966991 -0.19216991
79 80 81 82 83 84
0.39533009 0.55783009 1.39533009 2.54533009 2.87261905 3.18690476
85 86 87 88 89 90
2.37852273 2.55352273 2.76602273 2.42852273 2.31602273 2.05352273
91 92 93 94
2.14102273 2.10352273 2.24102273 1.69102273
> postscript(file="/var/www/html/rcomp/tmp/6aa461228940300.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 = 94
Frequency = 1
lag(myerror, k = 1) myerror
0 1.10988636 NA
1 1.08488636 1.10988636
2 0.79738636 1.08488636
3 0.75988636 0.79738636
4 0.44738636 0.75988636
5 0.18488636 0.44738636
6 0.17238636 0.18488636
7 -0.06511364 0.17238636
8 -0.62761364 -0.06511364
9 -1.17761364 -0.62761364
10 -1.35032468 -1.17761364
11 -1.33603896 -1.35032468
12 3.00436688 -1.33603896
13 3.27936688 3.00436688
14 3.59186688 3.27936688
15 4.15436688 3.59186688
16 3.54186688 4.15436688
17 3.67936688 3.54186688
18 1.76686688 3.67936688
19 1.52936688 1.76686688
20 1.46686688 1.52936688
21 1.71686688 1.46686688
22 1.84415584 1.71686688
23 1.45844156 1.84415584
24 -1.04994048 1.45844156
25 -1.17494048 -1.04994048
26 -1.26244048 -1.17494048
27 -1.39994048 -1.26244048
28 -1.71244048 -1.39994048
29 -1.77494048 -1.71244048
30 -1.48744048 -1.77494048
31 -1.22494048 -1.48744048
32 -0.68744048 -1.22494048
33 -0.23744048 -0.68744048
34 0.38984848 -0.23744048
35 0.20413420 0.38984848
36 -0.10424784 0.20413420
37 -0.02924784 -0.10424784
38 -0.01674784 -0.02924784
39 0.04575216 -0.01674784
40 0.03325216 0.04575216
41 -0.02924784 0.03325216
42 0.05825216 -0.02924784
43 -0.27924784 0.05825216
44 -0.64174784 -0.27924784
45 -1.19174784 -0.64174784
46 -1.06445887 -1.19174784
47 -1.35017316 -1.06445887
48 -2.15855519 -1.35017316
49 -2.18355519 -2.15855519
50 -2.17105519 -2.18355519
51 -2.80855519 -2.17105519
52 -2.32105519 -2.80855519
53 -2.08355519 -2.32105519
54 -1.49605519 -2.08355519
55 -1.83355519 -1.49605519
56 -2.39605519 -1.83355519
57 -2.64605519 -2.39605519
58 -2.31876623 -2.64605519
59 -2.30448052 -2.31876623
60 -3.01286255 -2.30448052
61 -3.03786255 -3.01286255
62 -3.12536255 -3.03786255
63 -2.76286255 -3.12536255
64 -1.87536255 -2.76286255
65 -1.83786255 -1.87536255
66 -1.55036255 -1.83786255
67 -0.78786255 -1.55036255
68 -0.75036255 -0.78786255
69 -0.70036255 -0.75036255
70 -0.37307359 -0.70036255
71 0.14121212 -0.37307359
72 -0.16716991 0.14121212
73 -0.49216991 -0.16716991
74 -0.57966991 -0.49216991
75 -0.41716991 -0.57966991
76 -0.42966991 -0.41716991
77 -0.19216991 -0.42966991
78 0.39533009 -0.19216991
79 0.55783009 0.39533009
80 1.39533009 0.55783009
81 2.54533009 1.39533009
82 2.87261905 2.54533009
83 3.18690476 2.87261905
84 2.37852273 3.18690476
85 2.55352273 2.37852273
86 2.76602273 2.55352273
87 2.42852273 2.76602273
88 2.31602273 2.42852273
89 2.05352273 2.31602273
90 2.14102273 2.05352273
91 2.10352273 2.14102273
92 2.24102273 2.10352273
93 1.69102273 2.24102273
94 NA 1.69102273
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 1.08488636 1.10988636
[2,] 0.79738636 1.08488636
[3,] 0.75988636 0.79738636
[4,] 0.44738636 0.75988636
[5,] 0.18488636 0.44738636
[6,] 0.17238636 0.18488636
[7,] -0.06511364 0.17238636
[8,] -0.62761364 -0.06511364
[9,] -1.17761364 -0.62761364
[10,] -1.35032468 -1.17761364
[11,] -1.33603896 -1.35032468
[12,] 3.00436688 -1.33603896
[13,] 3.27936688 3.00436688
[14,] 3.59186688 3.27936688
[15,] 4.15436688 3.59186688
[16,] 3.54186688 4.15436688
[17,] 3.67936688 3.54186688
[18,] 1.76686688 3.67936688
[19,] 1.52936688 1.76686688
[20,] 1.46686688 1.52936688
[21,] 1.71686688 1.46686688
[22,] 1.84415584 1.71686688
[23,] 1.45844156 1.84415584
[24,] -1.04994048 1.45844156
[25,] -1.17494048 -1.04994048
[26,] -1.26244048 -1.17494048
[27,] -1.39994048 -1.26244048
[28,] -1.71244048 -1.39994048
[29,] -1.77494048 -1.71244048
[30,] -1.48744048 -1.77494048
[31,] -1.22494048 -1.48744048
[32,] -0.68744048 -1.22494048
[33,] -0.23744048 -0.68744048
[34,] 0.38984848 -0.23744048
[35,] 0.20413420 0.38984848
[36,] -0.10424784 0.20413420
[37,] -0.02924784 -0.10424784
[38,] -0.01674784 -0.02924784
[39,] 0.04575216 -0.01674784
[40,] 0.03325216 0.04575216
[41,] -0.02924784 0.03325216
[42,] 0.05825216 -0.02924784
[43,] -0.27924784 0.05825216
[44,] -0.64174784 -0.27924784
[45,] -1.19174784 -0.64174784
[46,] -1.06445887 -1.19174784
[47,] -1.35017316 -1.06445887
[48,] -2.15855519 -1.35017316
[49,] -2.18355519 -2.15855519
[50,] -2.17105519 -2.18355519
[51,] -2.80855519 -2.17105519
[52,] -2.32105519 -2.80855519
[53,] -2.08355519 -2.32105519
[54,] -1.49605519 -2.08355519
[55,] -1.83355519 -1.49605519
[56,] -2.39605519 -1.83355519
[57,] -2.64605519 -2.39605519
[58,] -2.31876623 -2.64605519
[59,] -2.30448052 -2.31876623
[60,] -3.01286255 -2.30448052
[61,] -3.03786255 -3.01286255
[62,] -3.12536255 -3.03786255
[63,] -2.76286255 -3.12536255
[64,] -1.87536255 -2.76286255
[65,] -1.83786255 -1.87536255
[66,] -1.55036255 -1.83786255
[67,] -0.78786255 -1.55036255
[68,] -0.75036255 -0.78786255
[69,] -0.70036255 -0.75036255
[70,] -0.37307359 -0.70036255
[71,] 0.14121212 -0.37307359
[72,] -0.16716991 0.14121212
[73,] -0.49216991 -0.16716991
[74,] -0.57966991 -0.49216991
[75,] -0.41716991 -0.57966991
[76,] -0.42966991 -0.41716991
[77,] -0.19216991 -0.42966991
[78,] 0.39533009 -0.19216991
[79,] 0.55783009 0.39533009
[80,] 1.39533009 0.55783009
[81,] 2.54533009 1.39533009
[82,] 2.87261905 2.54533009
[83,] 3.18690476 2.87261905
[84,] 2.37852273 3.18690476
[85,] 2.55352273 2.37852273
[86,] 2.76602273 2.55352273
[87,] 2.42852273 2.76602273
[88,] 2.31602273 2.42852273
[89,] 2.05352273 2.31602273
[90,] 2.14102273 2.05352273
[91,] 2.10352273 2.14102273
[92,] 2.24102273 2.10352273
[93,] 1.69102273 2.24102273
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 1.08488636 1.10988636
2 0.79738636 1.08488636
3 0.75988636 0.79738636
4 0.44738636 0.75988636
5 0.18488636 0.44738636
6 0.17238636 0.18488636
7 -0.06511364 0.17238636
8 -0.62761364 -0.06511364
9 -1.17761364 -0.62761364
10 -1.35032468 -1.17761364
11 -1.33603896 -1.35032468
12 3.00436688 -1.33603896
13 3.27936688 3.00436688
14 3.59186688 3.27936688
15 4.15436688 3.59186688
16 3.54186688 4.15436688
17 3.67936688 3.54186688
18 1.76686688 3.67936688
19 1.52936688 1.76686688
20 1.46686688 1.52936688
21 1.71686688 1.46686688
22 1.84415584 1.71686688
23 1.45844156 1.84415584
24 -1.04994048 1.45844156
25 -1.17494048 -1.04994048
26 -1.26244048 -1.17494048
27 -1.39994048 -1.26244048
28 -1.71244048 -1.39994048
29 -1.77494048 -1.71244048
30 -1.48744048 -1.77494048
31 -1.22494048 -1.48744048
32 -0.68744048 -1.22494048
33 -0.23744048 -0.68744048
34 0.38984848 -0.23744048
35 0.20413420 0.38984848
36 -0.10424784 0.20413420
37 -0.02924784 -0.10424784
38 -0.01674784 -0.02924784
39 0.04575216 -0.01674784
40 0.03325216 0.04575216
41 -0.02924784 0.03325216
42 0.05825216 -0.02924784
43 -0.27924784 0.05825216
44 -0.64174784 -0.27924784
45 -1.19174784 -0.64174784
46 -1.06445887 -1.19174784
47 -1.35017316 -1.06445887
48 -2.15855519 -1.35017316
49 -2.18355519 -2.15855519
50 -2.17105519 -2.18355519
51 -2.80855519 -2.17105519
52 -2.32105519 -2.80855519
53 -2.08355519 -2.32105519
54 -1.49605519 -2.08355519
55 -1.83355519 -1.49605519
56 -2.39605519 -1.83355519
57 -2.64605519 -2.39605519
58 -2.31876623 -2.64605519
59 -2.30448052 -2.31876623
60 -3.01286255 -2.30448052
61 -3.03786255 -3.01286255
62 -3.12536255 -3.03786255
63 -2.76286255 -3.12536255
64 -1.87536255 -2.76286255
65 -1.83786255 -1.87536255
66 -1.55036255 -1.83786255
67 -0.78786255 -1.55036255
68 -0.75036255 -0.78786255
69 -0.70036255 -0.75036255
70 -0.37307359 -0.70036255
71 0.14121212 -0.37307359
72 -0.16716991 0.14121212
73 -0.49216991 -0.16716991
74 -0.57966991 -0.49216991
75 -0.41716991 -0.57966991
76 -0.42966991 -0.41716991
77 -0.19216991 -0.42966991
78 0.39533009 -0.19216991
79 0.55783009 0.39533009
80 1.39533009 0.55783009
81 2.54533009 1.39533009
82 2.87261905 2.54533009
83 3.18690476 2.87261905
84 2.37852273 3.18690476
85 2.55352273 2.37852273
86 2.76602273 2.55352273
87 2.42852273 2.76602273
88 2.31602273 2.42852273
89 2.05352273 2.31602273
90 2.14102273 2.05352273
91 2.10352273 2.14102273
92 2.24102273 2.10352273
93 1.69102273 2.24102273
> 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/77q351228940300.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8ffe41228940300.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9s2ed1228940300.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10sm381228940300.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ybdy1228940300.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/125xmu1228940300.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/13lfvc1228940300.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/14vjya1228940300.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/15l0ki1228940300.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/169ch91228940300.tab")
+ }
>
> system("convert tmp/1u0l91228940300.ps tmp/1u0l91228940300.png")
> system("convert tmp/232kv1228940300.ps tmp/232kv1228940300.png")
> system("convert tmp/3r44k1228940300.ps tmp/3r44k1228940300.png")
> system("convert tmp/4y14r1228940300.ps tmp/4y14r1228940300.png")
> system("convert tmp/5nin01228940300.ps tmp/5nin01228940300.png")
> system("convert tmp/6aa461228940300.ps tmp/6aa461228940300.png")
> system("convert tmp/77q351228940300.ps tmp/77q351228940300.png")
> system("convert tmp/8ffe41228940300.ps tmp/8ffe41228940300.png")
> system("convert tmp/9s2ed1228940300.ps tmp/9s2ed1228940300.png")
> system("convert tmp/10sm381228940300.ps tmp/10sm381228940300.png")
>
>
> proc.time()
user system elapsed
2.896 1.649 5.017