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.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(124,0,113,0,109,0,109,0,106,0,101,0,98,0,93,0,91,0,122,1,139,1,140,1,132,1,117,0,114,0,113,0,110,0,107,0,103,0,98,0,98,0,137,1,148,1,147,1,139,1,130,0,128,0,127,0,123,0,118,0,114,0,108,0,111,0,151,1,159,1,158,1,148,1,138,0,137,0,136,0,133,0,126,0,120,0,114,0,116,0,153,1,162,1,161,1,149,1,139,0,135,0,130,0,127,0,122,0,117,0,112,0,113,0,149,1,157,1,157,1,147,1,137,0,132,0,125,0,123,0,117,0,114,0,111,0,112,0,144,1,150,1,149,1,134,1,123,0,116,0,117,0,111,0,105,0,102,0,95,0,93,0,124,1,130,1,124,1,115,1,106,0,105,0,105,0,101,0,95,0,93,0,84,0,87,0,116,1,120,1,117,1,109,1),dim=c(2,97),dimnames=list(c('Y','X'),1:97))
> y <- array(NA,dim=c(2,97),dimnames=list(c('Y','X'),1:97))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = '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
1 124 0 1 0 0 0 0 0 0 0 0 0 0 1
2 113 0 0 1 0 0 0 0 0 0 0 0 0 2
3 109 0 0 0 1 0 0 0 0 0 0 0 0 3
4 109 0 0 0 0 1 0 0 0 0 0 0 0 4
5 106 0 0 0 0 0 1 0 0 0 0 0 0 5
6 101 0 0 0 0 0 0 1 0 0 0 0 0 6
7 98 0 0 0 0 0 0 0 1 0 0 0 0 7
8 93 0 0 0 0 0 0 0 0 1 0 0 0 8
9 91 0 0 0 0 0 0 0 0 0 1 0 0 9
10 122 1 0 0 0 0 0 0 0 0 0 1 0 10
11 139 1 0 0 0 0 0 0 0 0 0 0 1 11
12 140 1 0 0 0 0 0 0 0 0 0 0 0 12
13 132 1 1 0 0 0 0 0 0 0 0 0 0 13
14 117 0 0 1 0 0 0 0 0 0 0 0 0 14
15 114 0 0 0 1 0 0 0 0 0 0 0 0 15
16 113 0 0 0 0 1 0 0 0 0 0 0 0 16
17 110 0 0 0 0 0 1 0 0 0 0 0 0 17
18 107 0 0 0 0 0 0 1 0 0 0 0 0 18
19 103 0 0 0 0 0 0 0 1 0 0 0 0 19
20 98 0 0 0 0 0 0 0 0 1 0 0 0 20
21 98 0 0 0 0 0 0 0 0 0 1 0 0 21
22 137 1 0 0 0 0 0 0 0 0 0 1 0 22
23 148 1 0 0 0 0 0 0 0 0 0 0 1 23
24 147 1 0 0 0 0 0 0 0 0 0 0 0 24
25 139 1 1 0 0 0 0 0 0 0 0 0 0 25
26 130 0 0 1 0 0 0 0 0 0 0 0 0 26
27 128 0 0 0 1 0 0 0 0 0 0 0 0 27
28 127 0 0 0 0 1 0 0 0 0 0 0 0 28
29 123 0 0 0 0 0 1 0 0 0 0 0 0 29
30 118 0 0 0 0 0 0 1 0 0 0 0 0 30
31 114 0 0 0 0 0 0 0 1 0 0 0 0 31
32 108 0 0 0 0 0 0 0 0 1 0 0 0 32
33 111 0 0 0 0 0 0 0 0 0 1 0 0 33
34 151 1 0 0 0 0 0 0 0 0 0 1 0 34
35 159 1 0 0 0 0 0 0 0 0 0 0 1 35
36 158 1 0 0 0 0 0 0 0 0 0 0 0 36
37 148 1 1 0 0 0 0 0 0 0 0 0 0 37
38 138 0 0 1 0 0 0 0 0 0 0 0 0 38
39 137 0 0 0 1 0 0 0 0 0 0 0 0 39
40 136 0 0 0 0 1 0 0 0 0 0 0 0 40
41 133 0 0 0 0 0 1 0 0 0 0 0 0 41
42 126 0 0 0 0 0 0 1 0 0 0 0 0 42
43 120 0 0 0 0 0 0 0 1 0 0 0 0 43
44 114 0 0 0 0 0 0 0 0 1 0 0 0 44
45 116 0 0 0 0 0 0 0 0 0 1 0 0 45
46 153 1 0 0 0 0 0 0 0 0 0 1 0 46
47 162 1 0 0 0 0 0 0 0 0 0 0 1 47
48 161 1 0 0 0 0 0 0 0 0 0 0 0 48
49 149 1 1 0 0 0 0 0 0 0 0 0 0 49
50 139 0 0 1 0 0 0 0 0 0 0 0 0 50
51 135 0 0 0 1 0 0 0 0 0 0 0 0 51
52 130 0 0 0 0 1 0 0 0 0 0 0 0 52
53 127 0 0 0 0 0 1 0 0 0 0 0 0 53
54 122 0 0 0 0 0 0 1 0 0 0 0 0 54
55 117 0 0 0 0 0 0 0 1 0 0 0 0 55
56 112 0 0 0 0 0 0 0 0 1 0 0 0 56
57 113 0 0 0 0 0 0 0 0 0 1 0 0 57
58 149 1 0 0 0 0 0 0 0 0 0 1 0 58
59 157 1 0 0 0 0 0 0 0 0 0 0 1 59
60 157 1 0 0 0 0 0 0 0 0 0 0 0 60
61 147 1 1 0 0 0 0 0 0 0 0 0 0 61
62 137 0 0 1 0 0 0 0 0 0 0 0 0 62
63 132 0 0 0 1 0 0 0 0 0 0 0 0 63
64 125 0 0 0 0 1 0 0 0 0 0 0 0 64
65 123 0 0 0 0 0 1 0 0 0 0 0 0 65
66 117 0 0 0 0 0 0 1 0 0 0 0 0 66
67 114 0 0 0 0 0 0 0 1 0 0 0 0 67
68 111 0 0 0 0 0 0 0 0 1 0 0 0 68
69 112 0 0 0 0 0 0 0 0 0 1 0 0 69
70 144 1 0 0 0 0 0 0 0 0 0 1 0 70
71 150 1 0 0 0 0 0 0 0 0 0 0 1 71
72 149 1 0 0 0 0 0 0 0 0 0 0 0 72
73 134 1 1 0 0 0 0 0 0 0 0 0 0 73
74 123 0 0 1 0 0 0 0 0 0 0 0 0 74
75 116 0 0 0 1 0 0 0 0 0 0 0 0 75
76 117 0 0 0 0 1 0 0 0 0 0 0 0 76
77 111 0 0 0 0 0 1 0 0 0 0 0 0 77
78 105 0 0 0 0 0 0 1 0 0 0 0 0 78
79 102 0 0 0 0 0 0 0 1 0 0 0 0 79
80 95 0 0 0 0 0 0 0 0 1 0 0 0 80
81 93 0 0 0 0 0 0 0 0 0 1 0 0 81
82 124 1 0 0 0 0 0 0 0 0 0 1 0 82
83 130 1 0 0 0 0 0 0 0 0 0 0 1 83
84 124 1 0 0 0 0 0 0 0 0 0 0 0 84
85 115 1 1 0 0 0 0 0 0 0 0 0 0 85
86 106 0 0 1 0 0 0 0 0 0 0 0 0 86
87 105 0 0 0 1 0 0 0 0 0 0 0 0 87
88 105 0 0 0 0 1 0 0 0 0 0 0 0 88
89 101 0 0 0 0 0 1 0 0 0 0 0 0 89
90 95 0 0 0 0 0 0 1 0 0 0 0 0 90
91 93 0 0 0 0 0 0 0 1 0 0 0 0 91
92 84 0 0 0 0 0 0 0 0 1 0 0 0 92
93 87 0 0 0 0 0 0 0 0 0 1 0 0 93
94 116 1 0 0 0 0 0 0 0 0 0 1 0 94
95 120 1 0 0 0 0 0 0 0 0 0 0 1 95
96 117 1 0 0 0 0 0 0 0 0 0 0 0 96
97 109 1 1 0 0 0 0 0 0 0 0 0 0 97
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
134.0000 15.9554 -9.8920 -3.8743 -7.1414 -8.7834
M5 M6 M7 M8 M9 M10
-12.1754 -17.4425 -21.0845 -26.7265 -25.8686 -7.3409
M11 t
1.3920 -0.1080
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-22.590 -11.090 1.636 11.318 16.227
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 134.00000 13.89664 9.643 3.39e-15 ***
X 15.95536 13.41687 1.189 0.2378
M1 -9.89203 6.21494 -1.592 0.1153
M2 -3.87434 14.71562 -0.263 0.7930
M3 -7.14137 14.72206 -0.485 0.6289
M4 -8.78340 14.72864 -0.596 0.5526
M5 -12.17543 14.73536 -0.826 0.4110
M6 -17.44246 14.74222 -1.183 0.2401
M7 -21.08449 14.74922 -1.430 0.1566
M8 -26.72652 14.75636 -1.811 0.0737 .
M9 -25.86855 14.76364 -1.752 0.0834 .
M10 -7.34094 6.21545 -1.181 0.2409
M11 1.39203 6.21494 0.224 0.8233
t -0.10797 0.04614 -2.340 0.0217 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 12.43 on 83 degrees of freedom
Multiple R-squared: 0.6245, Adjusted R-squared: 0.5657
F-statistic: 10.62 on 13 and 83 DF, p-value: 7.495e-13
> 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,] 6.264170e-05 1.252834e-04 9.999374e-01
[2,] 3.703433e-05 7.406866e-05 9.999630e-01
[3,] 2.727052e-06 5.454103e-06 9.999973e-01
[4,] 2.020945e-07 4.041890e-07 9.999998e-01
[5,] 2.956695e-07 5.913390e-07 9.999997e-01
[6,] 5.299576e-04 1.059915e-03 9.994700e-01
[7,] 2.536804e-04 5.073608e-04 9.997463e-01
[8,] 9.585137e-05 1.917027e-04 9.999041e-01
[9,] 3.494995e-05 6.989989e-05 9.999651e-01
[10,] 5.340259e-05 1.068052e-04 9.999466e-01
[11,] 9.424383e-05 1.884877e-04 9.999058e-01
[12,] 9.494601e-05 1.898920e-04 9.999051e-01
[13,] 7.482660e-05 1.496532e-04 9.999252e-01
[14,] 5.290045e-05 1.058009e-04 9.999471e-01
[15,] 4.376942e-05 8.753884e-05 9.999562e-01
[16,] 4.703217e-05 9.406433e-05 9.999530e-01
[17,] 9.841620e-05 1.968324e-04 9.999016e-01
[18,] 7.917337e-04 1.583467e-03 9.992083e-01
[19,] 6.376229e-04 1.275246e-03 9.993624e-01
[20,] 4.688529e-04 9.377057e-04 9.995311e-01
[21,] 3.708591e-04 7.417182e-04 9.996291e-01
[22,] 3.359322e-04 6.718643e-04 9.996641e-01
[23,] 2.551753e-04 5.103507e-04 9.997448e-01
[24,] 1.658736e-04 3.317471e-04 9.998341e-01
[25,] 1.068730e-04 2.137460e-04 9.998931e-01
[26,] 8.335356e-05 1.667071e-04 9.999166e-01
[27,] 1.752268e-04 3.504536e-04 9.998248e-01
[28,] 5.112382e-04 1.022476e-03 9.994888e-01
[29,] 9.738938e-04 1.947788e-03 9.990261e-01
[30,] 8.800850e-04 1.760170e-03 9.991199e-01
[31,] 1.105501e-03 2.211003e-03 9.988945e-01
[32,] 1.386081e-03 2.772163e-03 9.986139e-01
[33,] 4.901548e-03 9.803096e-03 9.950985e-01
[34,] 9.437010e-03 1.887402e-02 9.905630e-01
[35,] 2.002063e-02 4.004126e-02 9.799794e-01
[36,] 1.025540e-01 2.051080e-01 8.974460e-01
[37,] 2.347023e-01 4.694046e-01 7.652977e-01
[38,] 3.752591e-01 7.505183e-01 6.247409e-01
[39,] 6.206140e-01 7.587721e-01 3.793860e-01
[40,] 7.969291e-01 4.061419e-01 2.030709e-01
[41,] 9.219515e-01 1.560971e-01 7.804853e-02
[42,] 9.425187e-01 1.149627e-01 5.748134e-02
[43,] 9.570657e-01 8.586859e-02 4.293430e-02
[44,] 9.595476e-01 8.090478e-02 4.045239e-02
[45,] 9.614364e-01 7.712715e-02 3.856358e-02
[46,] 9.604296e-01 7.914071e-02 3.957035e-02
[47,] 9.600738e-01 7.985241e-02 3.992620e-02
[48,] 9.785891e-01 4.282177e-02 2.141089e-02
[49,] 9.799203e-01 4.015946e-02 2.007973e-02
[50,] 9.806831e-01 3.863388e-02 1.931694e-02
[51,] 9.795267e-01 4.094651e-02 2.047326e-02
[52,] 9.706867e-01 5.862666e-02 2.931333e-02
[53,] 9.588542e-01 8.229150e-02 4.114575e-02
[54,] 9.594173e-01 8.116545e-02 4.058272e-02
[55,] 9.739826e-01 5.203486e-02 2.601743e-02
[56,] 9.984611e-01 3.077892e-03 1.538946e-03
[57,] 9.997012e-01 5.975248e-04 2.987624e-04
[58,] 9.999821e-01 3.589179e-05 1.794589e-05
[59,] 9.999628e-01 7.441287e-05 3.720643e-05
[60,] 9.999500e-01 9.998244e-05 4.999122e-05
[61,] 9.998262e-01 3.475741e-04 1.737870e-04
[62,] 9.993887e-01 1.222597e-03 6.112985e-04
[63,] 9.970698e-01 5.860481e-03 2.930241e-03
[64,] 9.945817e-01 1.083662e-02 5.418310e-03
> postscript(file="/var/www/html/rcomp/tmp/169f41227613924.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/216b91227613924.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3wzyl1227613924.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/41rol1227613924.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5m95r1227613924.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 97
Frequency = 1
1 2 3 4 5
-8.437695e-15 -1.690972e+01 -1.753472e+01 -1.578472e+01 -1.528472e+01
6 7 8 9 10
-1.490972e+01 -1.415972e+01 -1.340972e+01 -1.615972e+01 -1.953472e+01
11 12 13 14 15
-1.115972e+01 -8.659722e+00 -6.659722e+00 -1.161409e+01 -1.123909e+01
16 17 18 19 20
-1.048909e+01 -9.989087e+00 -7.614087e+00 -7.864087e+00 -7.114087e+00
21 22 23 24 25
-7.864087e+00 -3.239087e+00 -8.640873e-01 -3.640873e-01 1.635913e+00
26 27 28 29 30
2.681548e+00 4.056548e+00 4.806548e+00 4.306548e+00 4.681548e+00
31 32 33 34 35
4.431548e+00 4.181548e+00 6.431548e+00 1.205655e+01 1.143155e+01
36 37 38 39 40
1.193155e+01 1.193155e+01 1.197718e+01 1.435218e+01 1.510218e+01
41 42 43 44 45
1.560218e+01 1.397718e+01 1.172718e+01 1.147718e+01 1.272718e+01
46 47 48 49 50
1.535218e+01 1.572718e+01 1.622718e+01 1.422718e+01 1.427282e+01
51 52 53 54 55
1.364782e+01 1.039782e+01 1.089782e+01 1.127282e+01 1.002282e+01
56 57 58 59 60
1.077282e+01 1.102282e+01 1.264782e+01 1.202282e+01 1.352282e+01
61 62 63 64 65
1.352282e+01 1.356845e+01 1.194345e+01 6.693452e+00 8.193452e+00
66 67 68 69 70
7.568452e+00 8.318452e+00 1.106845e+01 1.131845e+01 8.943452e+00
71 72 73 74 75
6.318452e+00 6.818452e+00 1.818452e+00 8.640873e-01 -2.760913e+00
76 77 78 79 80
-1.091270e-02 -2.510913e+00 -3.135913e+00 -2.385913e+00 -3.635913e+00
81 82 83 84 85
-6.385913e+00 -9.760913e+00 -1.238591e+01 -1.688591e+01 -1.588591e+01
86 87 88 89 90
-1.484028e+01 -1.246528e+01 -1.071528e+01 -1.121528e+01 -1.184028e+01
91 92 93 94 95
-1.009028e+01 -1.334028e+01 -1.109028e+01 -1.646528e+01 -2.109028e+01
96 97
-2.259028e+01 -2.059028e+01
> postscript(file="/var/www/html/rcomp/tmp/60gdq1227613924.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 97
Frequency = 1
lag(myerror, k = 1) myerror
0 -8.437695e-15 NA
1 -1.690972e+01 -8.437695e-15
2 -1.753472e+01 -1.690972e+01
3 -1.578472e+01 -1.753472e+01
4 -1.528472e+01 -1.578472e+01
5 -1.490972e+01 -1.528472e+01
6 -1.415972e+01 -1.490972e+01
7 -1.340972e+01 -1.415972e+01
8 -1.615972e+01 -1.340972e+01
9 -1.953472e+01 -1.615972e+01
10 -1.115972e+01 -1.953472e+01
11 -8.659722e+00 -1.115972e+01
12 -6.659722e+00 -8.659722e+00
13 -1.161409e+01 -6.659722e+00
14 -1.123909e+01 -1.161409e+01
15 -1.048909e+01 -1.123909e+01
16 -9.989087e+00 -1.048909e+01
17 -7.614087e+00 -9.989087e+00
18 -7.864087e+00 -7.614087e+00
19 -7.114087e+00 -7.864087e+00
20 -7.864087e+00 -7.114087e+00
21 -3.239087e+00 -7.864087e+00
22 -8.640873e-01 -3.239087e+00
23 -3.640873e-01 -8.640873e-01
24 1.635913e+00 -3.640873e-01
25 2.681548e+00 1.635913e+00
26 4.056548e+00 2.681548e+00
27 4.806548e+00 4.056548e+00
28 4.306548e+00 4.806548e+00
29 4.681548e+00 4.306548e+00
30 4.431548e+00 4.681548e+00
31 4.181548e+00 4.431548e+00
32 6.431548e+00 4.181548e+00
33 1.205655e+01 6.431548e+00
34 1.143155e+01 1.205655e+01
35 1.193155e+01 1.143155e+01
36 1.193155e+01 1.193155e+01
37 1.197718e+01 1.193155e+01
38 1.435218e+01 1.197718e+01
39 1.510218e+01 1.435218e+01
40 1.560218e+01 1.510218e+01
41 1.397718e+01 1.560218e+01
42 1.172718e+01 1.397718e+01
43 1.147718e+01 1.172718e+01
44 1.272718e+01 1.147718e+01
45 1.535218e+01 1.272718e+01
46 1.572718e+01 1.535218e+01
47 1.622718e+01 1.572718e+01
48 1.422718e+01 1.622718e+01
49 1.427282e+01 1.422718e+01
50 1.364782e+01 1.427282e+01
51 1.039782e+01 1.364782e+01
52 1.089782e+01 1.039782e+01
53 1.127282e+01 1.089782e+01
54 1.002282e+01 1.127282e+01
55 1.077282e+01 1.002282e+01
56 1.102282e+01 1.077282e+01
57 1.264782e+01 1.102282e+01
58 1.202282e+01 1.264782e+01
59 1.352282e+01 1.202282e+01
60 1.352282e+01 1.352282e+01
61 1.356845e+01 1.352282e+01
62 1.194345e+01 1.356845e+01
63 6.693452e+00 1.194345e+01
64 8.193452e+00 6.693452e+00
65 7.568452e+00 8.193452e+00
66 8.318452e+00 7.568452e+00
67 1.106845e+01 8.318452e+00
68 1.131845e+01 1.106845e+01
69 8.943452e+00 1.131845e+01
70 6.318452e+00 8.943452e+00
71 6.818452e+00 6.318452e+00
72 1.818452e+00 6.818452e+00
73 8.640873e-01 1.818452e+00
74 -2.760913e+00 8.640873e-01
75 -1.091270e-02 -2.760913e+00
76 -2.510913e+00 -1.091270e-02
77 -3.135913e+00 -2.510913e+00
78 -2.385913e+00 -3.135913e+00
79 -3.635913e+00 -2.385913e+00
80 -6.385913e+00 -3.635913e+00
81 -9.760913e+00 -6.385913e+00
82 -1.238591e+01 -9.760913e+00
83 -1.688591e+01 -1.238591e+01
84 -1.588591e+01 -1.688591e+01
85 -1.484028e+01 -1.588591e+01
86 -1.246528e+01 -1.484028e+01
87 -1.071528e+01 -1.246528e+01
88 -1.121528e+01 -1.071528e+01
89 -1.184028e+01 -1.121528e+01
90 -1.009028e+01 -1.184028e+01
91 -1.334028e+01 -1.009028e+01
92 -1.109028e+01 -1.334028e+01
93 -1.646528e+01 -1.109028e+01
94 -2.109028e+01 -1.646528e+01
95 -2.259028e+01 -2.109028e+01
96 -2.059028e+01 -2.259028e+01
97 NA -2.059028e+01
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -16.90972222 -8.437695e-15
[2,] -17.53472222 -1.690972e+01
[3,] -15.78472222 -1.753472e+01
[4,] -15.28472222 -1.578472e+01
[5,] -14.90972222 -1.528472e+01
[6,] -14.15972222 -1.490972e+01
[7,] -13.40972222 -1.415972e+01
[8,] -16.15972222 -1.340972e+01
[9,] -19.53472222 -1.615972e+01
[10,] -11.15972222 -1.953472e+01
[11,] -8.65972222 -1.115972e+01
[12,] -6.65972222 -8.659722e+00
[13,] -11.61408730 -6.659722e+00
[14,] -11.23908730 -1.161409e+01
[15,] -10.48908730 -1.123909e+01
[16,] -9.98908730 -1.048909e+01
[17,] -7.61408730 -9.989087e+00
[18,] -7.86408730 -7.614087e+00
[19,] -7.11408730 -7.864087e+00
[20,] -7.86408730 -7.114087e+00
[21,] -3.23908730 -7.864087e+00
[22,] -0.86408730 -3.239087e+00
[23,] -0.36408730 -8.640873e-01
[24,] 1.63591270 -3.640873e-01
[25,] 2.68154762 1.635913e+00
[26,] 4.05654762 2.681548e+00
[27,] 4.80654762 4.056548e+00
[28,] 4.30654762 4.806548e+00
[29,] 4.68154762 4.306548e+00
[30,] 4.43154762 4.681548e+00
[31,] 4.18154762 4.431548e+00
[32,] 6.43154762 4.181548e+00
[33,] 12.05654762 6.431548e+00
[34,] 11.43154762 1.205655e+01
[35,] 11.93154762 1.143155e+01
[36,] 11.93154762 1.193155e+01
[37,] 11.97718254 1.193155e+01
[38,] 14.35218254 1.197718e+01
[39,] 15.10218254 1.435218e+01
[40,] 15.60218254 1.510218e+01
[41,] 13.97718254 1.560218e+01
[42,] 11.72718254 1.397718e+01
[43,] 11.47718254 1.172718e+01
[44,] 12.72718254 1.147718e+01
[45,] 15.35218254 1.272718e+01
[46,] 15.72718254 1.535218e+01
[47,] 16.22718254 1.572718e+01
[48,] 14.22718254 1.622718e+01
[49,] 14.27281746 1.422718e+01
[50,] 13.64781746 1.427282e+01
[51,] 10.39781746 1.364782e+01
[52,] 10.89781746 1.039782e+01
[53,] 11.27281746 1.089782e+01
[54,] 10.02281746 1.127282e+01
[55,] 10.77281746 1.002282e+01
[56,] 11.02281746 1.077282e+01
[57,] 12.64781746 1.102282e+01
[58,] 12.02281746 1.264782e+01
[59,] 13.52281746 1.202282e+01
[60,] 13.52281746 1.352282e+01
[61,] 13.56845238 1.352282e+01
[62,] 11.94345238 1.356845e+01
[63,] 6.69345238 1.194345e+01
[64,] 8.19345238 6.693452e+00
[65,] 7.56845238 8.193452e+00
[66,] 8.31845238 7.568452e+00
[67,] 11.06845238 8.318452e+00
[68,] 11.31845238 1.106845e+01
[69,] 8.94345238 1.131845e+01
[70,] 6.31845238 8.943452e+00
[71,] 6.81845238 6.318452e+00
[72,] 1.81845238 6.818452e+00
[73,] 0.86408730 1.818452e+00
[74,] -2.76091270 8.640873e-01
[75,] -0.01091270 -2.760913e+00
[76,] -2.51091270 -1.091270e-02
[77,] -3.13591270 -2.510913e+00
[78,] -2.38591270 -3.135913e+00
[79,] -3.63591270 -2.385913e+00
[80,] -6.38591270 -3.635913e+00
[81,] -9.76091270 -6.385913e+00
[82,] -12.38591270 -9.760913e+00
[83,] -16.88591270 -1.238591e+01
[84,] -15.88591270 -1.688591e+01
[85,] -14.84027778 -1.588591e+01
[86,] -12.46527778 -1.484028e+01
[87,] -10.71527778 -1.246528e+01
[88,] -11.21527778 -1.071528e+01
[89,] -11.84027778 -1.121528e+01
[90,] -10.09027778 -1.184028e+01
[91,] -13.34027778 -1.009028e+01
[92,] -11.09027778 -1.334028e+01
[93,] -16.46527778 -1.109028e+01
[94,] -21.09027778 -1.646528e+01
[95,] -22.59027778 -2.109028e+01
[96,] -20.59027778 -2.259028e+01
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -16.90972222 -8.437695e-15
2 -17.53472222 -1.690972e+01
3 -15.78472222 -1.753472e+01
4 -15.28472222 -1.578472e+01
5 -14.90972222 -1.528472e+01
6 -14.15972222 -1.490972e+01
7 -13.40972222 -1.415972e+01
8 -16.15972222 -1.340972e+01
9 -19.53472222 -1.615972e+01
10 -11.15972222 -1.953472e+01
11 -8.65972222 -1.115972e+01
12 -6.65972222 -8.659722e+00
13 -11.61408730 -6.659722e+00
14 -11.23908730 -1.161409e+01
15 -10.48908730 -1.123909e+01
16 -9.98908730 -1.048909e+01
17 -7.61408730 -9.989087e+00
18 -7.86408730 -7.614087e+00
19 -7.11408730 -7.864087e+00
20 -7.86408730 -7.114087e+00
21 -3.23908730 -7.864087e+00
22 -0.86408730 -3.239087e+00
23 -0.36408730 -8.640873e-01
24 1.63591270 -3.640873e-01
25 2.68154762 1.635913e+00
26 4.05654762 2.681548e+00
27 4.80654762 4.056548e+00
28 4.30654762 4.806548e+00
29 4.68154762 4.306548e+00
30 4.43154762 4.681548e+00
31 4.18154762 4.431548e+00
32 6.43154762 4.181548e+00
33 12.05654762 6.431548e+00
34 11.43154762 1.205655e+01
35 11.93154762 1.143155e+01
36 11.93154762 1.193155e+01
37 11.97718254 1.193155e+01
38 14.35218254 1.197718e+01
39 15.10218254 1.435218e+01
40 15.60218254 1.510218e+01
41 13.97718254 1.560218e+01
42 11.72718254 1.397718e+01
43 11.47718254 1.172718e+01
44 12.72718254 1.147718e+01
45 15.35218254 1.272718e+01
46 15.72718254 1.535218e+01
47 16.22718254 1.572718e+01
48 14.22718254 1.622718e+01
49 14.27281746 1.422718e+01
50 13.64781746 1.427282e+01
51 10.39781746 1.364782e+01
52 10.89781746 1.039782e+01
53 11.27281746 1.089782e+01
54 10.02281746 1.127282e+01
55 10.77281746 1.002282e+01
56 11.02281746 1.077282e+01
57 12.64781746 1.102282e+01
58 12.02281746 1.264782e+01
59 13.52281746 1.202282e+01
60 13.52281746 1.352282e+01
61 13.56845238 1.352282e+01
62 11.94345238 1.356845e+01
63 6.69345238 1.194345e+01
64 8.19345238 6.693452e+00
65 7.56845238 8.193452e+00
66 8.31845238 7.568452e+00
67 11.06845238 8.318452e+00
68 11.31845238 1.106845e+01
69 8.94345238 1.131845e+01
70 6.31845238 8.943452e+00
71 6.81845238 6.318452e+00
72 1.81845238 6.818452e+00
73 0.86408730 1.818452e+00
74 -2.76091270 8.640873e-01
75 -0.01091270 -2.760913e+00
76 -2.51091270 -1.091270e-02
77 -3.13591270 -2.510913e+00
78 -2.38591270 -3.135913e+00
79 -3.63591270 -2.385913e+00
80 -6.38591270 -3.635913e+00
81 -9.76091270 -6.385913e+00
82 -12.38591270 -9.760913e+00
83 -16.88591270 -1.238591e+01
84 -15.88591270 -1.688591e+01
85 -14.84027778 -1.588591e+01
86 -12.46527778 -1.484028e+01
87 -10.71527778 -1.246528e+01
88 -11.21527778 -1.071528e+01
89 -11.84027778 -1.121528e+01
90 -10.09027778 -1.184028e+01
91 -13.34027778 -1.009028e+01
92 -11.09027778 -1.334028e+01
93 -16.46527778 -1.109028e+01
94 -21.09027778 -1.646528e+01
95 -22.59027778 -2.109028e+01
96 -20.59027778 -2.259028e+01
> 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/7j6wz1227613924.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8hjap1227613924.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9fqkx1227613924.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
Warning message:
In dropInf(r.w/(s * sqrt(1 - hii))) :
Not plotting observations with leverage one:
1
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10tqxl1227613924.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11cmv41227613924.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/124njn1227613924.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/13wy7j1227613924.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/14ii5c1227613924.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/15ifpp1227613924.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/167ckh1227613924.tab")
+ }
>
> system("convert tmp/169f41227613924.ps tmp/169f41227613924.png")
> system("convert tmp/216b91227613924.ps tmp/216b91227613924.png")
> system("convert tmp/3wzyl1227613924.ps tmp/3wzyl1227613924.png")
> system("convert tmp/41rol1227613924.ps tmp/41rol1227613924.png")
> system("convert tmp/5m95r1227613924.ps tmp/5m95r1227613924.png")
> system("convert tmp/60gdq1227613924.ps tmp/60gdq1227613924.png")
> system("convert tmp/7j6wz1227613924.ps tmp/7j6wz1227613924.png")
> system("convert tmp/8hjap1227613924.ps tmp/8hjap1227613924.png")
> system("convert tmp/9fqkx1227613924.ps tmp/9fqkx1227613924.png")
> system("convert tmp/10tqxl1227613924.ps tmp/10tqxl1227613924.png")
>
>
> proc.time()
user system elapsed
2.910 1.564 3.753