R version 2.9.0 (2009-04-17)
Copyright (C) 2009 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(32.68
+ ,10967.87
+ ,31.54
+ ,10433.56
+ ,32.43
+ ,10665.78
+ ,26.54
+ ,10666.71
+ ,25.85
+ ,10682.74
+ ,27.6
+ ,10777.22
+ ,25.71
+ ,10052.6
+ ,25.38
+ ,10213.97
+ ,28.57
+ ,10546.82
+ ,27.64
+ ,10767.2
+ ,25.36
+ ,10444.5
+ ,25.9
+ ,10314.68
+ ,26.29
+ ,9042.56
+ ,21.74
+ ,9220.75
+ ,19.2
+ ,9721.84
+ ,19.32
+ ,9978.53
+ ,19.82
+ ,9923.81
+ ,20.36
+ ,9892.56
+ ,24.31
+ ,10500.98
+ ,25.97
+ ,10179.35
+ ,25.61
+ ,10080.48
+ ,24.67
+ ,9492.44
+ ,25.59
+ ,8616.49
+ ,26.09
+ ,8685.4
+ ,28.37
+ ,8160.67
+ ,27.34
+ ,8048.1
+ ,24.46
+ ,8641.21
+ ,27.46
+ ,8526.63
+ ,30.23
+ ,8474.21
+ ,32.33
+ ,7916.13
+ ,29.87
+ ,7977.64
+ ,24.87
+ ,8334.59
+ ,25.48
+ ,8623.36
+ ,27.28
+ ,9098.03
+ ,28.24
+ ,9154.34
+ ,29.58
+ ,9284.73
+ ,26.95
+ ,9492.49
+ ,29.08
+ ,9682.35
+ ,28.76
+ ,9762.12
+ ,29.59
+ ,10124.63
+ ,30.7
+ ,10540.05
+ ,30.52
+ ,10601.61
+ ,32.67
+ ,10323.73
+ ,33.19
+ ,10418.4
+ ,37.13
+ ,10092.96
+ ,35.54
+ ,10364.91
+ ,37.75
+ ,10152.09
+ ,41.84
+ ,10032.8
+ ,42.94
+ ,10204.59
+ ,49.14
+ ,10001.6
+ ,44.61
+ ,10411.75
+ ,40.22
+ ,10673.38
+ ,44.23
+ ,10539.51
+ ,45.85
+ ,10723.78
+ ,53.38
+ ,10682.06
+ ,53.26
+ ,10283.19
+ ,51.8
+ ,10377.18
+ ,55.3
+ ,10486.64
+ ,57.81
+ ,10545.38
+ ,63.96
+ ,10554.27
+ ,63.77
+ ,10532.54
+ ,59.15
+ ,10324.31
+ ,56.12
+ ,10695.25
+ ,57.42
+ ,10827.81
+ ,63.52
+ ,10872.48
+ ,61.71
+ ,10971.19
+ ,63.01
+ ,11145.65
+ ,68.18
+ ,11234.68
+ ,72.03
+ ,11333.88
+ ,69.75
+ ,10997.97
+ ,74.41
+ ,11036.89
+ ,74.33
+ ,11257.35
+ ,64.24
+ ,11533.59
+ ,60.03
+ ,11963.12
+ ,59.44
+ ,12185.15
+ ,62.5
+ ,12377.62
+ ,55.04
+ ,12512.89
+ ,58.34
+ ,12631.48
+ ,61.92
+ ,12268.53
+ ,67.65
+ ,12754.8
+ ,67.68
+ ,13407.75
+ ,70.3
+ ,13480.21
+ ,75.26
+ ,13673.28
+ ,71.44
+ ,13239.71
+ ,76.36
+ ,13557.69
+ ,81.71
+ ,13901.28
+ ,92.6
+ ,13200.58
+ ,90.6
+ ,13406.97
+ ,92.23
+ ,12538.12
+ ,94.09
+ ,12419.57
+ ,102.79
+ ,12193.88
+ ,109.65
+ ,12656.63
+ ,124.05
+ ,12812.48
+ ,132.69
+ ,12056.67
+ ,135.81
+ ,11322.38
+ ,116.07
+ ,11530.75
+ ,101.42
+ ,11114.08
+ ,75.73
+ ,9181.73
+ ,55.48
+ ,8614.55
+ ,43.8
+ ,8595.56
+ ,45.29
+ ,8396.2
+ ,44.01
+ ,7690.5
+ ,47.48
+ ,7235.47
+ ,51.07
+ ,7992.12
+ ,57.84
+ ,8398.37
+ ,69.04
+ ,8593
+ ,65.61
+ ,8679.75
+ ,72.87
+ ,9374.63
+ ,68.41
+ ,9634.97
+ ,73.25
+ ,9857.34
+ ,77.43
+ ,10238.83)
+ ,dim=c(2
+ ,111)
+ ,dimnames=list(c('olieprijs'
+ ,'dowjones')
+ ,1:111))
> y <- array(NA,dim=c(2,111),dimnames=list(c('olieprijs','dowjones'),1:111))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
olieprijs dowjones
1 32.68 10967.87
2 31.54 10433.56
3 32.43 10665.78
4 26.54 10666.71
5 25.85 10682.74
6 27.60 10777.22
7 25.71 10052.60
8 25.38 10213.97
9 28.57 10546.82
10 27.64 10767.20
11 25.36 10444.50
12 25.90 10314.68
13 26.29 9042.56
14 21.74 9220.75
15 19.20 9721.84
16 19.32 9978.53
17 19.82 9923.81
18 20.36 9892.56
19 24.31 10500.98
20 25.97 10179.35
21 25.61 10080.48
22 24.67 9492.44
23 25.59 8616.49
24 26.09 8685.40
25 28.37 8160.67
26 27.34 8048.10
27 24.46 8641.21
28 27.46 8526.63
29 30.23 8474.21
30 32.33 7916.13
31 29.87 7977.64
32 24.87 8334.59
33 25.48 8623.36
34 27.28 9098.03
35 28.24 9154.34
36 29.58 9284.73
37 26.95 9492.49
38 29.08 9682.35
39 28.76 9762.12
40 29.59 10124.63
41 30.70 10540.05
42 30.52 10601.61
43 32.67 10323.73
44 33.19 10418.40
45 37.13 10092.96
46 35.54 10364.91
47 37.75 10152.09
48 41.84 10032.80
49 42.94 10204.59
50 49.14 10001.60
51 44.61 10411.75
52 40.22 10673.38
53 44.23 10539.51
54 45.85 10723.78
55 53.38 10682.06
56 53.26 10283.19
57 51.80 10377.18
58 55.30 10486.64
59 57.81 10545.38
60 63.96 10554.27
61 63.77 10532.54
62 59.15 10324.31
63 56.12 10695.25
64 57.42 10827.81
65 63.52 10872.48
66 61.71 10971.19
67 63.01 11145.65
68 68.18 11234.68
69 72.03 11333.88
70 69.75 10997.97
71 74.41 11036.89
72 74.33 11257.35
73 64.24 11533.59
74 60.03 11963.12
75 59.44 12185.15
76 62.50 12377.62
77 55.04 12512.89
78 58.34 12631.48
79 61.92 12268.53
80 67.65 12754.80
81 67.68 13407.75
82 70.30 13480.21
83 75.26 13673.28
84 71.44 13239.71
85 76.36 13557.69
86 81.71 13901.28
87 92.60 13200.58
88 90.60 13406.97
89 92.23 12538.12
90 94.09 12419.57
91 102.79 12193.88
92 109.65 12656.63
93 124.05 12812.48
94 132.69 12056.67
95 135.81 11322.38
96 116.07 11530.75
97 101.42 11114.08
98 75.73 9181.73
99 55.48 8614.55
100 43.80 8595.56
101 45.29 8396.20
102 44.01 7690.50
103 47.48 7235.47
104 51.07 7992.12
105 57.84 8398.37
106 69.04 8593.00
107 65.61 8679.75
108 72.87 9374.63
109 68.41 9634.97
110 73.25 9857.34
111 77.43 10238.83
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) dowjones
-55.92278 0.01027
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-27.925 -15.504 -6.383 11.520 75.466
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -55.922784 14.489554 -3.860 0.000193 ***
dowjones 0.010269 0.001373 7.478 2.03e-11 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 21.51 on 109 degrees of freedom
Multiple R-squared: 0.3391, Adjusted R-squared: 0.333
F-statistic: 55.93 on 1 and 109 DF, p-value: 2.028e-11
> 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,] 7.647363e-03 1.529473e-02 9.923526e-01
[2,] 1.396772e-03 2.793544e-03 9.986032e-01
[3,] 2.181033e-04 4.362066e-04 9.997819e-01
[4,] 3.328710e-05 6.657420e-05 9.999667e-01
[5,] 4.326572e-06 8.653144e-06 9.999957e-01
[6,] 6.924902e-07 1.384980e-06 9.999993e-01
[7,] 1.260882e-07 2.521764e-07 9.999999e-01
[8,] 1.645486e-08 3.290972e-08 1.000000e+00
[9,] 4.550569e-09 9.101139e-09 1.000000e+00
[10,] 9.374017e-10 1.874803e-09 1.000000e+00
[11,] 1.129026e-09 2.258052e-09 1.000000e+00
[12,] 1.158079e-09 2.316157e-09 1.000000e+00
[13,] 5.765412e-10 1.153082e-09 1.000000e+00
[14,] 1.958539e-10 3.917077e-10 1.000000e+00
[15,] 5.172298e-11 1.034460e-10 1.000000e+00
[16,] 9.982178e-12 1.996436e-11 1.000000e+00
[17,] 1.921187e-12 3.842375e-12 1.000000e+00
[18,] 4.554090e-13 9.108180e-13 1.000000e+00
[19,] 3.613284e-13 7.226568e-13 1.000000e+00
[20,] 1.430097e-13 2.860195e-13 1.000000e+00
[21,] 1.146790e-13 2.293580e-13 1.000000e+00
[22,] 3.444809e-14 6.889619e-14 1.000000e+00
[23,] 6.367349e-15 1.273470e-14 1.000000e+00
[24,] 1.535347e-15 3.070694e-15 1.000000e+00
[25,] 7.464725e-16 1.492945e-15 1.000000e+00
[26,] 6.254665e-16 1.250933e-15 1.000000e+00
[27,] 1.627854e-16 3.255709e-16 1.000000e+00
[28,] 3.405229e-17 6.810459e-17 1.000000e+00
[29,] 6.789053e-18 1.357811e-17 1.000000e+00
[30,] 1.414473e-18 2.828946e-18 1.000000e+00
[31,] 3.263867e-19 6.527734e-19 1.000000e+00
[32,] 9.859429e-20 1.971886e-19 1.000000e+00
[33,] 2.287362e-20 4.574724e-20 1.000000e+00
[34,] 7.113225e-21 1.422645e-20 1.000000e+00
[35,] 2.191291e-21 4.382582e-21 1.000000e+00
[36,] 9.104301e-22 1.820860e-21 1.000000e+00
[37,] 5.903163e-22 1.180633e-21 1.000000e+00
[38,] 3.728050e-22 7.456100e-22 1.000000e+00
[39,] 4.441163e-22 8.882326e-22 1.000000e+00
[40,] 6.199267e-22 1.239853e-21 1.000000e+00
[41,] 5.070958e-21 1.014192e-20 1.000000e+00
[42,] 1.285486e-20 2.570971e-20 1.000000e+00
[43,] 7.096192e-20 1.419238e-19 1.000000e+00
[44,] 2.061760e-18 4.123521e-18 1.000000e+00
[45,] 4.144016e-17 8.288031e-17 1.000000e+00
[46,] 6.783947e-15 1.356789e-14 1.000000e+00
[47,] 4.486679e-14 8.973358e-14 1.000000e+00
[48,] 8.383796e-14 1.676759e-13 1.000000e+00
[49,] 3.077618e-13 6.155235e-13 1.000000e+00
[50,] 1.218555e-12 2.437111e-12 1.000000e+00
[51,] 2.126146e-11 4.252293e-11 1.000000e+00
[52,] 2.205522e-10 4.411045e-10 1.000000e+00
[53,] 9.907492e-10 1.981498e-09 1.000000e+00
[54,] 5.575082e-09 1.115016e-08 1.000000e+00
[55,] 3.066705e-08 6.133410e-08 1.000000e+00
[56,] 2.906375e-07 5.812751e-07 9.999997e-01
[57,] 1.473395e-06 2.946790e-06 9.999985e-01
[58,] 3.453836e-06 6.907673e-06 9.999965e-01
[59,] 4.833698e-06 9.667396e-06 9.999952e-01
[60,] 6.497600e-06 1.299520e-05 9.999935e-01
[61,] 1.147858e-05 2.295716e-05 9.999885e-01
[62,] 1.521701e-05 3.043403e-05 9.999848e-01
[63,] 1.848031e-05 3.696061e-05 9.999815e-01
[64,] 2.589289e-05 5.178578e-05 9.999741e-01
[65,] 3.824304e-05 7.648608e-05 9.999618e-01
[66,] 5.194617e-05 1.038923e-04 9.999481e-01
[67,] 8.281609e-05 1.656322e-04 9.999172e-01
[68,] 1.002919e-04 2.005838e-04 9.998997e-01
[69,] 7.708070e-05 1.541614e-04 9.999229e-01
[70,] 6.338658e-05 1.267732e-04 9.999366e-01
[71,] 5.788108e-05 1.157622e-04 9.999421e-01
[72,] 5.083089e-05 1.016618e-04 9.999492e-01
[73,] 8.076816e-05 1.615363e-04 9.999192e-01
[74,] 1.186230e-04 2.372459e-04 9.998814e-01
[75,] 1.332512e-04 2.665024e-04 9.998667e-01
[76,] 1.432268e-04 2.864536e-04 9.998568e-01
[77,] 2.368501e-04 4.737001e-04 9.997631e-01
[78,] 4.210114e-04 8.420227e-04 9.995790e-01
[79,] 7.653328e-04 1.530666e-03 9.992347e-01
[80,] 1.928665e-03 3.857329e-03 9.980713e-01
[81,] 6.242623e-03 1.248525e-02 9.937574e-01
[82,] 3.081534e-02 6.163068e-02 9.691847e-01
[83,] 6.217538e-02 1.243508e-01 9.378246e-01
[84,] 2.037668e-01 4.075336e-01 7.962332e-01
[85,] 3.745620e-01 7.491240e-01 6.254380e-01
[86,] 6.054309e-01 7.891381e-01 3.945691e-01
[87,] 7.327073e-01 5.345854e-01 2.672927e-01
[88,] 8.737926e-01 2.524147e-01 1.262074e-01
[89,] 9.331145e-01 1.337711e-01 6.688553e-02
[90,] 9.624925e-01 7.501499e-02 3.750749e-02
[91,] 9.992447e-01 1.510549e-03 7.552745e-04
[92,] 9.996192e-01 7.615627e-04 3.807814e-04
[93,] 9.995935e-01 8.130003e-04 4.065002e-04
[94,] 9.996375e-01 7.250644e-04 3.625322e-04
[95,] 9.991312e-01 1.737682e-03 8.688412e-04
[96,] 9.997115e-01 5.769189e-04 2.884594e-04
[97,] 9.999160e-01 1.679150e-04 8.395749e-05
[98,] 9.999126e-01 1.747547e-04 8.737733e-05
[99,] 9.995983e-01 8.033063e-04 4.016532e-04
[100,] 9.994286e-01 1.142898e-03 5.714492e-04
[101,] 9.993753e-01 1.249488e-03 6.247440e-04
[102,] 9.971194e-01 5.761261e-03 2.880631e-03
> postscript(file="/var/www/html/rcomp/tmp/19wz71262197807.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2c0zm1262197807.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/36ibh1262197807.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4fe4q1262197807.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5xvck1262197807.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 = 111
Frequency = 1
1 2 3 4 5 6
-24.0233048 -19.6766200 -21.1712243 -27.0707742 -27.9253820 -27.1455715
7 8 9 10 11 12
-21.5946449 -23.5817097 -23.8096563 -27.0026789 -25.9689599 -24.0958734
13 14 15 16 17 18
-10.6428175 -17.0226023 -24.7081599 -27.2240401 -26.1621352 -25.3012374
19 20 21 22 23 24
-27.5989377 -22.6362063 -21.9809370 -16.8825134 -6.9676199 -7.1752381
25 26 27 28 29 30
0.4930723 0.6190231 -8.3514629 -4.1748719 -0.8665851 6.9641874
31 32 33 34 35 36
3.8725578 -4.7928651 -7.1481661 -10.2224239 -9.8406560 -9.8395956
37 38 39 40 41 42
-14.6030269 -14.4226478 -15.5617844 -18.4543014 -21.6101370 -22.4222800
43 44 45 46 47 48
-17.4188054 -17.8709461 -10.5890908 -14.9716717 -10.5762807 -5.2613240
49 50 51 52 53 54
-5.9253890 2.3590603 -6.3826590 -13.4592667 -8.0745919 -8.3468106
55 56 57 58 59 60
-0.3883992 3.5874888 1.1623310 3.5383159 5.4451307 11.5038417
61 62 63 64 65 66
11.5369812 9.0552387 2.2161562 2.1549335 7.7962293 4.9726030
67 68 69 70 71 72
4.4811205 8.7368955 11.5682376 12.7376065 16.9979475 14.6541034
73 74 75 76 77 78
1.7274696 -6.8932577 -9.7632237 -8.6796460 -17.5286970 -15.4464656
79 80 81 82 83 84
-8.1394303 -7.4028053 -14.0777722 -12.2018443 -9.2244279 -8.5922149
85 86 87 88 89 90
-6.9374654 -5.1156982 12.9696005 8.8502374 19.4022229 22.4795808
91 92 93 94 95 96
33.4971303 35.6052758 48.4048944 64.8061027 75.4663280 53.5866328
97 98 99 100 101 102
43.2153043 37.3680835 22.9423014 11.4573046 14.9944784 20.9611208
103 104 105 106 107 108
29.1037007 24.9238666 27.5221953 36.7235925 32.4027802 32.5272456
109 110 111
25.3938846 27.9504272 28.2130097
> postscript(file="/var/www/html/rcomp/tmp/6ot421262197807.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 = 111
Frequency = 1
lag(myerror, k = 1) myerror
0 -24.0233048 NA
1 -19.6766200 -24.0233048
2 -21.1712243 -19.6766200
3 -27.0707742 -21.1712243
4 -27.9253820 -27.0707742
5 -27.1455715 -27.9253820
6 -21.5946449 -27.1455715
7 -23.5817097 -21.5946449
8 -23.8096563 -23.5817097
9 -27.0026789 -23.8096563
10 -25.9689599 -27.0026789
11 -24.0958734 -25.9689599
12 -10.6428175 -24.0958734
13 -17.0226023 -10.6428175
14 -24.7081599 -17.0226023
15 -27.2240401 -24.7081599
16 -26.1621352 -27.2240401
17 -25.3012374 -26.1621352
18 -27.5989377 -25.3012374
19 -22.6362063 -27.5989377
20 -21.9809370 -22.6362063
21 -16.8825134 -21.9809370
22 -6.9676199 -16.8825134
23 -7.1752381 -6.9676199
24 0.4930723 -7.1752381
25 0.6190231 0.4930723
26 -8.3514629 0.6190231
27 -4.1748719 -8.3514629
28 -0.8665851 -4.1748719
29 6.9641874 -0.8665851
30 3.8725578 6.9641874
31 -4.7928651 3.8725578
32 -7.1481661 -4.7928651
33 -10.2224239 -7.1481661
34 -9.8406560 -10.2224239
35 -9.8395956 -9.8406560
36 -14.6030269 -9.8395956
37 -14.4226478 -14.6030269
38 -15.5617844 -14.4226478
39 -18.4543014 -15.5617844
40 -21.6101370 -18.4543014
41 -22.4222800 -21.6101370
42 -17.4188054 -22.4222800
43 -17.8709461 -17.4188054
44 -10.5890908 -17.8709461
45 -14.9716717 -10.5890908
46 -10.5762807 -14.9716717
47 -5.2613240 -10.5762807
48 -5.9253890 -5.2613240
49 2.3590603 -5.9253890
50 -6.3826590 2.3590603
51 -13.4592667 -6.3826590
52 -8.0745919 -13.4592667
53 -8.3468106 -8.0745919
54 -0.3883992 -8.3468106
55 3.5874888 -0.3883992
56 1.1623310 3.5874888
57 3.5383159 1.1623310
58 5.4451307 3.5383159
59 11.5038417 5.4451307
60 11.5369812 11.5038417
61 9.0552387 11.5369812
62 2.2161562 9.0552387
63 2.1549335 2.2161562
64 7.7962293 2.1549335
65 4.9726030 7.7962293
66 4.4811205 4.9726030
67 8.7368955 4.4811205
68 11.5682376 8.7368955
69 12.7376065 11.5682376
70 16.9979475 12.7376065
71 14.6541034 16.9979475
72 1.7274696 14.6541034
73 -6.8932577 1.7274696
74 -9.7632237 -6.8932577
75 -8.6796460 -9.7632237
76 -17.5286970 -8.6796460
77 -15.4464656 -17.5286970
78 -8.1394303 -15.4464656
79 -7.4028053 -8.1394303
80 -14.0777722 -7.4028053
81 -12.2018443 -14.0777722
82 -9.2244279 -12.2018443
83 -8.5922149 -9.2244279
84 -6.9374654 -8.5922149
85 -5.1156982 -6.9374654
86 12.9696005 -5.1156982
87 8.8502374 12.9696005
88 19.4022229 8.8502374
89 22.4795808 19.4022229
90 33.4971303 22.4795808
91 35.6052758 33.4971303
92 48.4048944 35.6052758
93 64.8061027 48.4048944
94 75.4663280 64.8061027
95 53.5866328 75.4663280
96 43.2153043 53.5866328
97 37.3680835 43.2153043
98 22.9423014 37.3680835
99 11.4573046 22.9423014
100 14.9944784 11.4573046
101 20.9611208 14.9944784
102 29.1037007 20.9611208
103 24.9238666 29.1037007
104 27.5221953 24.9238666
105 36.7235925 27.5221953
106 32.4027802 36.7235925
107 32.5272456 32.4027802
108 25.3938846 32.5272456
109 27.9504272 25.3938846
110 28.2130097 27.9504272
111 NA 28.2130097
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -19.6766200 -24.0233048
[2,] -21.1712243 -19.6766200
[3,] -27.0707742 -21.1712243
[4,] -27.9253820 -27.0707742
[5,] -27.1455715 -27.9253820
[6,] -21.5946449 -27.1455715
[7,] -23.5817097 -21.5946449
[8,] -23.8096563 -23.5817097
[9,] -27.0026789 -23.8096563
[10,] -25.9689599 -27.0026789
[11,] -24.0958734 -25.9689599
[12,] -10.6428175 -24.0958734
[13,] -17.0226023 -10.6428175
[14,] -24.7081599 -17.0226023
[15,] -27.2240401 -24.7081599
[16,] -26.1621352 -27.2240401
[17,] -25.3012374 -26.1621352
[18,] -27.5989377 -25.3012374
[19,] -22.6362063 -27.5989377
[20,] -21.9809370 -22.6362063
[21,] -16.8825134 -21.9809370
[22,] -6.9676199 -16.8825134
[23,] -7.1752381 -6.9676199
[24,] 0.4930723 -7.1752381
[25,] 0.6190231 0.4930723
[26,] -8.3514629 0.6190231
[27,] -4.1748719 -8.3514629
[28,] -0.8665851 -4.1748719
[29,] 6.9641874 -0.8665851
[30,] 3.8725578 6.9641874
[31,] -4.7928651 3.8725578
[32,] -7.1481661 -4.7928651
[33,] -10.2224239 -7.1481661
[34,] -9.8406560 -10.2224239
[35,] -9.8395956 -9.8406560
[36,] -14.6030269 -9.8395956
[37,] -14.4226478 -14.6030269
[38,] -15.5617844 -14.4226478
[39,] -18.4543014 -15.5617844
[40,] -21.6101370 -18.4543014
[41,] -22.4222800 -21.6101370
[42,] -17.4188054 -22.4222800
[43,] -17.8709461 -17.4188054
[44,] -10.5890908 -17.8709461
[45,] -14.9716717 -10.5890908
[46,] -10.5762807 -14.9716717
[47,] -5.2613240 -10.5762807
[48,] -5.9253890 -5.2613240
[49,] 2.3590603 -5.9253890
[50,] -6.3826590 2.3590603
[51,] -13.4592667 -6.3826590
[52,] -8.0745919 -13.4592667
[53,] -8.3468106 -8.0745919
[54,] -0.3883992 -8.3468106
[55,] 3.5874888 -0.3883992
[56,] 1.1623310 3.5874888
[57,] 3.5383159 1.1623310
[58,] 5.4451307 3.5383159
[59,] 11.5038417 5.4451307
[60,] 11.5369812 11.5038417
[61,] 9.0552387 11.5369812
[62,] 2.2161562 9.0552387
[63,] 2.1549335 2.2161562
[64,] 7.7962293 2.1549335
[65,] 4.9726030 7.7962293
[66,] 4.4811205 4.9726030
[67,] 8.7368955 4.4811205
[68,] 11.5682376 8.7368955
[69,] 12.7376065 11.5682376
[70,] 16.9979475 12.7376065
[71,] 14.6541034 16.9979475
[72,] 1.7274696 14.6541034
[73,] -6.8932577 1.7274696
[74,] -9.7632237 -6.8932577
[75,] -8.6796460 -9.7632237
[76,] -17.5286970 -8.6796460
[77,] -15.4464656 -17.5286970
[78,] -8.1394303 -15.4464656
[79,] -7.4028053 -8.1394303
[80,] -14.0777722 -7.4028053
[81,] -12.2018443 -14.0777722
[82,] -9.2244279 -12.2018443
[83,] -8.5922149 -9.2244279
[84,] -6.9374654 -8.5922149
[85,] -5.1156982 -6.9374654
[86,] 12.9696005 -5.1156982
[87,] 8.8502374 12.9696005
[88,] 19.4022229 8.8502374
[89,] 22.4795808 19.4022229
[90,] 33.4971303 22.4795808
[91,] 35.6052758 33.4971303
[92,] 48.4048944 35.6052758
[93,] 64.8061027 48.4048944
[94,] 75.4663280 64.8061027
[95,] 53.5866328 75.4663280
[96,] 43.2153043 53.5866328
[97,] 37.3680835 43.2153043
[98,] 22.9423014 37.3680835
[99,] 11.4573046 22.9423014
[100,] 14.9944784 11.4573046
[101,] 20.9611208 14.9944784
[102,] 29.1037007 20.9611208
[103,] 24.9238666 29.1037007
[104,] 27.5221953 24.9238666
[105,] 36.7235925 27.5221953
[106,] 32.4027802 36.7235925
[107,] 32.5272456 32.4027802
[108,] 25.3938846 32.5272456
[109,] 27.9504272 25.3938846
[110,] 28.2130097 27.9504272
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -19.6766200 -24.0233048
2 -21.1712243 -19.6766200
3 -27.0707742 -21.1712243
4 -27.9253820 -27.0707742
5 -27.1455715 -27.9253820
6 -21.5946449 -27.1455715
7 -23.5817097 -21.5946449
8 -23.8096563 -23.5817097
9 -27.0026789 -23.8096563
10 -25.9689599 -27.0026789
11 -24.0958734 -25.9689599
12 -10.6428175 -24.0958734
13 -17.0226023 -10.6428175
14 -24.7081599 -17.0226023
15 -27.2240401 -24.7081599
16 -26.1621352 -27.2240401
17 -25.3012374 -26.1621352
18 -27.5989377 -25.3012374
19 -22.6362063 -27.5989377
20 -21.9809370 -22.6362063
21 -16.8825134 -21.9809370
22 -6.9676199 -16.8825134
23 -7.1752381 -6.9676199
24 0.4930723 -7.1752381
25 0.6190231 0.4930723
26 -8.3514629 0.6190231
27 -4.1748719 -8.3514629
28 -0.8665851 -4.1748719
29 6.9641874 -0.8665851
30 3.8725578 6.9641874
31 -4.7928651 3.8725578
32 -7.1481661 -4.7928651
33 -10.2224239 -7.1481661
34 -9.8406560 -10.2224239
35 -9.8395956 -9.8406560
36 -14.6030269 -9.8395956
37 -14.4226478 -14.6030269
38 -15.5617844 -14.4226478
39 -18.4543014 -15.5617844
40 -21.6101370 -18.4543014
41 -22.4222800 -21.6101370
42 -17.4188054 -22.4222800
43 -17.8709461 -17.4188054
44 -10.5890908 -17.8709461
45 -14.9716717 -10.5890908
46 -10.5762807 -14.9716717
47 -5.2613240 -10.5762807
48 -5.9253890 -5.2613240
49 2.3590603 -5.9253890
50 -6.3826590 2.3590603
51 -13.4592667 -6.3826590
52 -8.0745919 -13.4592667
53 -8.3468106 -8.0745919
54 -0.3883992 -8.3468106
55 3.5874888 -0.3883992
56 1.1623310 3.5874888
57 3.5383159 1.1623310
58 5.4451307 3.5383159
59 11.5038417 5.4451307
60 11.5369812 11.5038417
61 9.0552387 11.5369812
62 2.2161562 9.0552387
63 2.1549335 2.2161562
64 7.7962293 2.1549335
65 4.9726030 7.7962293
66 4.4811205 4.9726030
67 8.7368955 4.4811205
68 11.5682376 8.7368955
69 12.7376065 11.5682376
70 16.9979475 12.7376065
71 14.6541034 16.9979475
72 1.7274696 14.6541034
73 -6.8932577 1.7274696
74 -9.7632237 -6.8932577
75 -8.6796460 -9.7632237
76 -17.5286970 -8.6796460
77 -15.4464656 -17.5286970
78 -8.1394303 -15.4464656
79 -7.4028053 -8.1394303
80 -14.0777722 -7.4028053
81 -12.2018443 -14.0777722
82 -9.2244279 -12.2018443
83 -8.5922149 -9.2244279
84 -6.9374654 -8.5922149
85 -5.1156982 -6.9374654
86 12.9696005 -5.1156982
87 8.8502374 12.9696005
88 19.4022229 8.8502374
89 22.4795808 19.4022229
90 33.4971303 22.4795808
91 35.6052758 33.4971303
92 48.4048944 35.6052758
93 64.8061027 48.4048944
94 75.4663280 64.8061027
95 53.5866328 75.4663280
96 43.2153043 53.5866328
97 37.3680835 43.2153043
98 22.9423014 37.3680835
99 11.4573046 22.9423014
100 14.9944784 11.4573046
101 20.9611208 14.9944784
102 29.1037007 20.9611208
103 24.9238666 29.1037007
104 27.5221953 24.9238666
105 36.7235925 27.5221953
106 32.4027802 36.7235925
107 32.5272456 32.4027802
108 25.3938846 32.5272456
109 27.9504272 25.3938846
110 28.2130097 27.9504272
> 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/7ts091262197807.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8fncw1262197807.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9m1031262197807.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10iunh1262197807.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11fex31262197807.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/12tbj71262197807.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/13phn41262197807.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/14erpb1262197807.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/15tqt31262197807.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/163dfb1262197807.tab")
+ }
>
> try(system("convert tmp/19wz71262197807.ps tmp/19wz71262197807.png",intern=TRUE))
character(0)
> try(system("convert tmp/2c0zm1262197807.ps tmp/2c0zm1262197807.png",intern=TRUE))
character(0)
> try(system("convert tmp/36ibh1262197807.ps tmp/36ibh1262197807.png",intern=TRUE))
character(0)
> try(system("convert tmp/4fe4q1262197807.ps tmp/4fe4q1262197807.png",intern=TRUE))
character(0)
> try(system("convert tmp/5xvck1262197807.ps tmp/5xvck1262197807.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ot421262197807.ps tmp/6ot421262197807.png",intern=TRUE))
character(0)
> try(system("convert tmp/7ts091262197807.ps tmp/7ts091262197807.png",intern=TRUE))
character(0)
> try(system("convert tmp/8fncw1262197807.ps tmp/8fncw1262197807.png",intern=TRUE))
character(0)
> try(system("convert tmp/9m1031262197807.ps tmp/9m1031262197807.png",intern=TRUE))
character(0)
> try(system("convert tmp/10iunh1262197807.ps tmp/10iunh1262197807.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.172 1.694 5.836