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(103.7
+ ,114813
+ ,116476
+ ,106370
+ ,106.2
+ ,117925
+ ,123297
+ ,109375
+ ,107.7
+ ,126466
+ ,114813
+ ,116476
+ ,109.9
+ ,131235
+ ,117925
+ ,123297
+ ,111.7
+ ,120546
+ ,126466
+ ,114813
+ ,114.9
+ ,123791
+ ,131235
+ ,117925
+ ,116
+ ,129813
+ ,120546
+ ,126466
+ ,118.3
+ ,133463
+ ,123791
+ ,131235
+ ,120.4
+ ,122987
+ ,129813
+ ,120546
+ ,126
+ ,125418
+ ,133463
+ ,123791
+ ,128.1
+ ,130199
+ ,122987
+ ,129813
+ ,130.1
+ ,133016
+ ,125418
+ ,133463
+ ,130.8
+ ,121454
+ ,130199
+ ,122987
+ ,133.6
+ ,122044
+ ,133016
+ ,125418
+ ,134.2
+ ,128313
+ ,121454
+ ,130199
+ ,135.5
+ ,131556
+ ,122044
+ ,133016
+ ,136.2
+ ,120027
+ ,128313
+ ,121454
+ ,139.1
+ ,123001
+ ,131556
+ ,122044
+ ,139
+ ,130111
+ ,120027
+ ,128313
+ ,139.6
+ ,132524
+ ,123001
+ ,131556
+ ,138.7
+ ,123742
+ ,130111
+ ,120027
+ ,140.9
+ ,124931
+ ,132524
+ ,123001
+ ,141.3
+ ,133646
+ ,123742
+ ,130111
+ ,141.8
+ ,136557
+ ,124931
+ ,132524
+ ,142
+ ,127509
+ ,133646
+ ,123742
+ ,144.5
+ ,128945
+ ,136557
+ ,124931
+ ,144.6
+ ,137191
+ ,127509
+ ,133646
+ ,145.5
+ ,139716
+ ,128945
+ ,136557
+ ,146.8
+ ,129083
+ ,137191
+ ,127509
+ ,149.5
+ ,131604
+ ,139716
+ ,128945
+ ,149.9
+ ,139413
+ ,129083
+ ,137191
+ ,150.1
+ ,143125
+ ,131604
+ ,139716
+ ,150.9
+ ,133948
+ ,139413
+ ,129083
+ ,152.8
+ ,137116
+ ,143125
+ ,131604
+ ,153.1
+ ,144864
+ ,133948
+ ,139413
+ ,154
+ ,149277
+ ,137116
+ ,143125
+ ,154.9
+ ,138796
+ ,144864
+ ,133948
+ ,156.9
+ ,143258
+ ,149277
+ ,137116
+ ,158.4
+ ,150034
+ ,138796
+ ,144864
+ ,159.7
+ ,154708
+ ,143258
+ ,149277
+ ,160.2
+ ,144888
+ ,150034
+ ,138796
+ ,163.2
+ ,148762
+ ,154708
+ ,143258
+ ,163.7
+ ,156500
+ ,144888
+ ,150034
+ ,164.4
+ ,161088
+ ,148762
+ ,154708
+ ,163.7
+ ,152772
+ ,156500
+ ,144888
+ ,165.5
+ ,158011
+ ,161088
+ ,148762
+ ,165.6
+ ,163318
+ ,152772
+ ,156500
+ ,166.8
+ ,169969
+ ,158011
+ ,161088
+ ,167.5
+ ,162269
+ ,163318
+ ,152772
+ ,170.6
+ ,165765
+ ,169969
+ ,158011
+ ,170.9
+ ,170600
+ ,162269
+ ,163318
+ ,172
+ ,174681
+ ,165765
+ ,169969
+ ,171.8
+ ,166364
+ ,170600
+ ,162269
+ ,173.9
+ ,170240
+ ,174681
+ ,165765
+ ,174
+ ,176150
+ ,166364
+ ,170600
+ ,173.8
+ ,182056
+ ,170240
+ ,174681
+ ,173.9
+ ,172218
+ ,176150
+ ,166364
+ ,176
+ ,177856
+ ,182056
+ ,170240
+ ,176.6
+ ,182253
+ ,172218
+ ,176150
+ ,178.2
+ ,188090
+ ,177856
+ ,182056
+ ,179.2
+ ,176863
+ ,182253
+ ,172218
+ ,181.3
+ ,183273
+ ,188090
+ ,177856
+ ,181.8
+ ,187969
+ ,176863
+ ,182253
+ ,182.9
+ ,194650
+ ,183273
+ ,188090
+ ,183.8
+ ,183036
+ ,187969
+ ,176863
+ ,186.3
+ ,189516
+ ,194650
+ ,183273
+ ,187.4
+ ,193805
+ ,183036
+ ,187969
+ ,189.2
+ ,200499
+ ,189516
+ ,194650
+ ,189.7
+ ,188142
+ ,193805
+ ,183036
+ ,191.9
+ ,193732
+ ,200499
+ ,189516
+ ,192.6
+ ,197126
+ ,188142
+ ,193805
+ ,193.7
+ ,205140
+ ,193732
+ ,200499
+ ,194.2
+ ,191751
+ ,197126
+ ,188142
+ ,197.6
+ ,196700
+ ,205140
+ ,193732
+ ,199.3
+ ,199784
+ ,191751
+ ,197126
+ ,201.4
+ ,207360
+ ,196700
+ ,205140
+ ,203
+ ,196101
+ ,199784
+ ,191751
+ ,206.3
+ ,200824
+ ,207360
+ ,196700
+ ,207.1
+ ,205743
+ ,196101
+ ,199784
+ ,209.8
+ ,212489
+ ,200824
+ ,207360
+ ,211.1
+ ,200810
+ ,205743
+ ,196101
+ ,215.3
+ ,203683
+ ,212489
+ ,200824
+ ,217.4
+ ,207286
+ ,200810
+ ,205743
+ ,215.5
+ ,210910
+ ,203683
+ ,212489
+ ,210.9
+ ,194915
+ ,207286
+ ,200810
+ ,212.6
+ ,217920
+ ,210910
+ ,203683)
+ ,dim=c(4
+ ,86)
+ ,dimnames=list(c('RPI'
+ ,'HFCE'
+ ,'HFCE-2'
+ ,'HFCE-4')
+ ,1:86))
> y <- array(NA,dim=c(4,86),dimnames=list(c('RPI','HFCE','HFCE-2','HFCE-4'),1:86))
> 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 Quarterly Dummies'
> par1 = '2'
> #'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
HFCE RPI HFCE-2 HFCE-4 Q1 Q2 Q3 t
1 114813 103.7 116476 106370 1 0 0 1
2 117925 106.2 123297 109375 0 1 0 2
3 126466 107.7 114813 116476 0 0 1 3
4 131235 109.9 117925 123297 0 0 0 4
5 120546 111.7 126466 114813 1 0 0 5
6 123791 114.9 131235 117925 0 1 0 6
7 129813 116.0 120546 126466 0 0 1 7
8 133463 118.3 123791 131235 0 0 0 8
9 122987 120.4 129813 120546 1 0 0 9
10 125418 126.0 133463 123791 0 1 0 10
11 130199 128.1 122987 129813 0 0 1 11
12 133016 130.1 125418 133463 0 0 0 12
13 121454 130.8 130199 122987 1 0 0 13
14 122044 133.6 133016 125418 0 1 0 14
15 128313 134.2 121454 130199 0 0 1 15
16 131556 135.5 122044 133016 0 0 0 16
17 120027 136.2 128313 121454 1 0 0 17
18 123001 139.1 131556 122044 0 1 0 18
19 130111 139.0 120027 128313 0 0 1 19
20 132524 139.6 123001 131556 0 0 0 20
21 123742 138.7 130111 120027 1 0 0 21
22 124931 140.9 132524 123001 0 1 0 22
23 133646 141.3 123742 130111 0 0 1 23
24 136557 141.8 124931 132524 0 0 0 24
25 127509 142.0 133646 123742 1 0 0 25
26 128945 144.5 136557 124931 0 1 0 26
27 137191 144.6 127509 133646 0 0 1 27
28 139716 145.5 128945 136557 0 0 0 28
29 129083 146.8 137191 127509 1 0 0 29
30 131604 149.5 139716 128945 0 1 0 30
31 139413 149.9 129083 137191 0 0 1 31
32 143125 150.1 131604 139716 0 0 0 32
33 133948 150.9 139413 129083 1 0 0 33
34 137116 152.8 143125 131604 0 1 0 34
35 144864 153.1 133948 139413 0 0 1 35
36 149277 154.0 137116 143125 0 0 0 36
37 138796 154.9 144864 133948 1 0 0 37
38 143258 156.9 149277 137116 0 1 0 38
39 150034 158.4 138796 144864 0 0 1 39
40 154708 159.7 143258 149277 0 0 0 40
41 144888 160.2 150034 138796 1 0 0 41
42 148762 163.2 154708 143258 0 1 0 42
43 156500 163.7 144888 150034 0 0 1 43
44 161088 164.4 148762 154708 0 0 0 44
45 152772 163.7 156500 144888 1 0 0 45
46 158011 165.5 161088 148762 0 1 0 46
47 163318 165.6 152772 156500 0 0 1 47
48 169969 166.8 158011 161088 0 0 0 48
49 162269 167.5 163318 152772 1 0 0 49
50 165765 170.6 169969 158011 0 1 0 50
51 170600 170.9 162269 163318 0 0 1 51
52 174681 172.0 165765 169969 0 0 0 52
53 166364 171.8 170600 162269 1 0 0 53
54 170240 173.9 174681 165765 0 1 0 54
55 176150 174.0 166364 170600 0 0 1 55
56 182056 173.8 170240 174681 0 0 0 56
57 172218 173.9 176150 166364 1 0 0 57
58 177856 176.0 182056 170240 0 1 0 58
59 182253 176.6 172218 176150 0 0 1 59
60 188090 178.2 177856 182056 0 0 0 60
61 176863 179.2 182253 172218 1 0 0 61
62 183273 181.3 188090 177856 0 1 0 62
63 187969 181.8 176863 182253 0 0 1 63
64 194650 182.9 183273 188090 0 0 0 64
65 183036 183.8 187969 176863 1 0 0 65
66 189516 186.3 194650 183273 0 1 0 66
67 193805 187.4 183036 187969 0 0 1 67
68 200499 189.2 189516 194650 0 0 0 68
69 188142 189.7 193805 183036 1 0 0 69
70 193732 191.9 200499 189516 0 1 0 70
71 197126 192.6 188142 193805 0 0 1 71
72 205140 193.7 193732 200499 0 0 0 72
73 191751 194.2 197126 188142 1 0 0 73
74 196700 197.6 205140 193732 0 1 0 74
75 199784 199.3 191751 197126 0 0 1 75
76 207360 201.4 196700 205140 0 0 0 76
77 196101 203.0 199784 191751 1 0 0 77
78 200824 206.3 207360 196700 0 1 0 78
79 205743 207.1 196101 199784 0 0 1 79
80 212489 209.8 200824 207360 0 0 0 80
81 200810 211.1 205743 196101 1 0 0 81
82 203683 215.3 212489 200824 0 1 0 82
83 207286 217.4 200810 205743 0 0 1 83
84 210910 215.5 203683 212489 0 0 0 84
85 194915 210.9 207286 200810 1 0 0 85
86 217920 212.6 210910 203683 0 1 0 86
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) RPI `HFCE-2` `HFCE-4` Q1 Q2
7.469e+04 -4.430e+02 6.304e-01 2.113e-01 -1.264e+04 -1.144e+04
Q3 t
-1.206e+03 7.203e+02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-8037.50 -687.43 -74.97 493.19 10906.41
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 7.469e+04 1.068e+04 6.992 8.18e-10 ***
RPI -4.430e+02 7.924e+01 -5.590 3.21e-07 ***
`HFCE-2` 6.304e-01 1.591e-01 3.963 0.000163 ***
`HFCE-4` 2.113e-01 1.497e-01 1.412 0.161906
Q1 -1.264e+04 2.487e+03 -5.082 2.50e-06 ***
Q2 -1.144e+04 2.762e+03 -4.141 8.69e-05 ***
Q3 -1.206e+03 6.451e+02 -1.870 0.065233 .
t 7.203e+02 1.195e+02 6.030 5.15e-08 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1980 on 78 degrees of freedom
Multiple R-squared: 0.9961, Adjusted R-squared: 0.9957
F-statistic: 2839 on 7 and 78 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,] 1.130732e-01 2.261464e-01 0.8869268
[2,] 5.795077e-02 1.159015e-01 0.9420492
[3,] 2.234121e-02 4.468243e-02 0.9776588
[4,] 8.110494e-03 1.622099e-02 0.9918895
[5,] 4.776054e-03 9.552108e-03 0.9952239
[6,] 4.605243e-03 9.210487e-03 0.9953948
[7,] 1.767116e-03 3.534232e-03 0.9982329
[8,] 1.536827e-03 3.073654e-03 0.9984632
[9,] 2.401440e-03 4.802880e-03 0.9975986
[10,] 1.163058e-03 2.326115e-03 0.9988369
[11,] 5.169123e-04 1.033825e-03 0.9994831
[12,] 1.966164e-04 3.932329e-04 0.9998034
[13,] 9.333852e-05 1.866770e-04 0.9999067
[14,] 3.859547e-05 7.719095e-05 0.9999614
[15,] 1.514036e-05 3.028073e-05 0.9999849
[16,] 5.600477e-06 1.120095e-05 0.9999944
[17,] 2.048700e-06 4.097400e-06 0.9999980
[18,] 7.457126e-07 1.491425e-06 0.9999993
[19,] 8.018485e-07 1.603697e-06 0.9999992
[20,] 3.187968e-07 6.375936e-07 0.9999997
[21,] 1.720741e-07 3.441483e-07 0.9999998
[22,] 6.608894e-08 1.321779e-07 0.9999999
[23,] 4.571071e-08 9.142142e-08 1.0000000
[24,] 6.276423e-08 1.255285e-07 0.9999999
[25,] 3.185021e-08 6.370041e-08 1.0000000
[26,] 1.986177e-08 3.972353e-08 1.0000000
[27,] 7.099739e-09 1.419948e-08 1.0000000
[28,] 9.932074e-09 1.986415e-08 1.0000000
[29,] 7.405151e-09 1.481030e-08 1.0000000
[30,] 3.568153e-09 7.136307e-09 1.0000000
[31,] 2.452216e-09 4.904433e-09 1.0000000
[32,] 4.968532e-09 9.937064e-09 1.0000000
[33,] 5.151191e-09 1.030238e-08 1.0000000
[34,] 3.045044e-09 6.090087e-09 1.0000000
[35,] 2.593645e-09 5.187291e-09 1.0000000
[36,] 1.341144e-08 2.682289e-08 1.0000000
[37,] 1.130395e-08 2.260789e-08 1.0000000
[38,] 4.608775e-09 9.217550e-09 1.0000000
[39,] 5.686759e-08 1.137352e-07 0.9999999
[40,] 2.498363e-08 4.996726e-08 1.0000000
[41,] 4.597455e-08 9.194910e-08 1.0000000
[42,] 2.549432e-07 5.098863e-07 0.9999997
[43,] 2.334478e-07 4.668957e-07 0.9999998
[44,] 1.013211e-07 2.026423e-07 0.9999999
[45,] 8.868849e-08 1.773770e-07 0.9999999
[46,] 5.844070e-08 1.168814e-07 0.9999999
[47,] 3.067953e-08 6.135905e-08 1.0000000
[48,] 1.620515e-08 3.241030e-08 1.0000000
[49,] 1.787343e-08 3.574686e-08 1.0000000
[50,] 4.335180e-08 8.670361e-08 1.0000000
[51,] 2.483335e-08 4.966670e-08 1.0000000
[52,] 1.536082e-08 3.072164e-08 1.0000000
[53,] 7.924092e-09 1.584818e-08 1.0000000
[54,] 1.480507e-08 2.961014e-08 1.0000000
[55,] 1.713909e-08 3.427819e-08 1.0000000
[56,] 8.342032e-08 1.668406e-07 0.9999999
[57,] 1.328835e-07 2.657669e-07 0.9999999
[58,] 2.966587e-07 5.933175e-07 0.9999997
[59,] 3.372986e-07 6.745972e-07 0.9999997
[60,] 1.649247e-07 3.298494e-07 0.9999998
[61,] 7.740949e-08 1.548190e-07 0.9999999
[62,] 5.635565e-08 1.127113e-07 0.9999999
[63,] 1.772011e-08 3.544022e-08 1.0000000
[64,] 2.759845e-08 5.519691e-08 1.0000000
[65,] 9.433913e-09 1.886783e-08 1.0000000
> postscript(file="/var/www/html/rcomp/tmp/1nywu1259169675.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/292eq1259169675.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3klty1259169675.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4hy5f1259169675.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5j0x01259169675.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 = 86
Frequency = 1
1 2 3 4 5 6
2077.76595 -560.14490 1542.19678 1955.83749 391.82690 -532.07319
7 8 9 10 11 12
-40.26005 -351.50900 484.28225 486.82866 578.69919 51.16224
13 14 15 16 17 18
-81.93906 -2463.61917 -601.37213 323.56624 -485.03075 -317.89205
19 20 21 22 23 24
1740.00262 -67.99475 624.51274 -1284.03817 690.97180 637.30491
25 26 27 28 29 30
-41.18872 -1506.54579 -304.93757 -828.35722 -2252.70743 -2353.34090
31 32 33 34 35 36
-357.57481 -606.46874 -185.87556 -971.44878 93.54120 197.03130
37 38 39 40 41 42
-911.32272 -937.22361 522.25041 100.08225 363.83781 -245.07066
43 44 45 46 47 48
1522.15419 1063.70017 1553.76191 1956.74819 -35.60905 948.13812
49 50 51 52 53 54
3888.98232 1535.91145 -714.41475 -1682.19487 410.32185 -17.31205
55 56 57 58 59 60
-792.54368 -207.62436 -50.47674 53.14454 -1281.97238 -1465.08715
61 62 63 64 65 66
-1023.05783 -476.30654 -361.38305 -394.05926 -278.27179 -179.51343
67 68 69 70 71 72
-25.03167 42.89063 -423.16652 -1370.29142 -1733.62085 -97.49861
73 74 75 76 77 78
-874.34866 -2574.90620 -1965.56059 -199.34009 2054.60316 495.31603
79 80 81 82 83 84
1263.78496 2700.82425 2794.99369 355.36622 260.67944 -2120.40353
85 86
-8037.50278 10906.41177
> postscript(file="/var/www/html/rcomp/tmp/6ankb1259169675.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 = 86
Frequency = 1
lag(myerror, k = 1) myerror
0 2077.76595 NA
1 -560.14490 2077.76595
2 1542.19678 -560.14490
3 1955.83749 1542.19678
4 391.82690 1955.83749
5 -532.07319 391.82690
6 -40.26005 -532.07319
7 -351.50900 -40.26005
8 484.28225 -351.50900
9 486.82866 484.28225
10 578.69919 486.82866
11 51.16224 578.69919
12 -81.93906 51.16224
13 -2463.61917 -81.93906
14 -601.37213 -2463.61917
15 323.56624 -601.37213
16 -485.03075 323.56624
17 -317.89205 -485.03075
18 1740.00262 -317.89205
19 -67.99475 1740.00262
20 624.51274 -67.99475
21 -1284.03817 624.51274
22 690.97180 -1284.03817
23 637.30491 690.97180
24 -41.18872 637.30491
25 -1506.54579 -41.18872
26 -304.93757 -1506.54579
27 -828.35722 -304.93757
28 -2252.70743 -828.35722
29 -2353.34090 -2252.70743
30 -357.57481 -2353.34090
31 -606.46874 -357.57481
32 -185.87556 -606.46874
33 -971.44878 -185.87556
34 93.54120 -971.44878
35 197.03130 93.54120
36 -911.32272 197.03130
37 -937.22361 -911.32272
38 522.25041 -937.22361
39 100.08225 522.25041
40 363.83781 100.08225
41 -245.07066 363.83781
42 1522.15419 -245.07066
43 1063.70017 1522.15419
44 1553.76191 1063.70017
45 1956.74819 1553.76191
46 -35.60905 1956.74819
47 948.13812 -35.60905
48 3888.98232 948.13812
49 1535.91145 3888.98232
50 -714.41475 1535.91145
51 -1682.19487 -714.41475
52 410.32185 -1682.19487
53 -17.31205 410.32185
54 -792.54368 -17.31205
55 -207.62436 -792.54368
56 -50.47674 -207.62436
57 53.14454 -50.47674
58 -1281.97238 53.14454
59 -1465.08715 -1281.97238
60 -1023.05783 -1465.08715
61 -476.30654 -1023.05783
62 -361.38305 -476.30654
63 -394.05926 -361.38305
64 -278.27179 -394.05926
65 -179.51343 -278.27179
66 -25.03167 -179.51343
67 42.89063 -25.03167
68 -423.16652 42.89063
69 -1370.29142 -423.16652
70 -1733.62085 -1370.29142
71 -97.49861 -1733.62085
72 -874.34866 -97.49861
73 -2574.90620 -874.34866
74 -1965.56059 -2574.90620
75 -199.34009 -1965.56059
76 2054.60316 -199.34009
77 495.31603 2054.60316
78 1263.78496 495.31603
79 2700.82425 1263.78496
80 2794.99369 2700.82425
81 355.36622 2794.99369
82 260.67944 355.36622
83 -2120.40353 260.67944
84 -8037.50278 -2120.40353
85 10906.41177 -8037.50278
86 NA 10906.41177
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -560.14490 2077.76595
[2,] 1542.19678 -560.14490
[3,] 1955.83749 1542.19678
[4,] 391.82690 1955.83749
[5,] -532.07319 391.82690
[6,] -40.26005 -532.07319
[7,] -351.50900 -40.26005
[8,] 484.28225 -351.50900
[9,] 486.82866 484.28225
[10,] 578.69919 486.82866
[11,] 51.16224 578.69919
[12,] -81.93906 51.16224
[13,] -2463.61917 -81.93906
[14,] -601.37213 -2463.61917
[15,] 323.56624 -601.37213
[16,] -485.03075 323.56624
[17,] -317.89205 -485.03075
[18,] 1740.00262 -317.89205
[19,] -67.99475 1740.00262
[20,] 624.51274 -67.99475
[21,] -1284.03817 624.51274
[22,] 690.97180 -1284.03817
[23,] 637.30491 690.97180
[24,] -41.18872 637.30491
[25,] -1506.54579 -41.18872
[26,] -304.93757 -1506.54579
[27,] -828.35722 -304.93757
[28,] -2252.70743 -828.35722
[29,] -2353.34090 -2252.70743
[30,] -357.57481 -2353.34090
[31,] -606.46874 -357.57481
[32,] -185.87556 -606.46874
[33,] -971.44878 -185.87556
[34,] 93.54120 -971.44878
[35,] 197.03130 93.54120
[36,] -911.32272 197.03130
[37,] -937.22361 -911.32272
[38,] 522.25041 -937.22361
[39,] 100.08225 522.25041
[40,] 363.83781 100.08225
[41,] -245.07066 363.83781
[42,] 1522.15419 -245.07066
[43,] 1063.70017 1522.15419
[44,] 1553.76191 1063.70017
[45,] 1956.74819 1553.76191
[46,] -35.60905 1956.74819
[47,] 948.13812 -35.60905
[48,] 3888.98232 948.13812
[49,] 1535.91145 3888.98232
[50,] -714.41475 1535.91145
[51,] -1682.19487 -714.41475
[52,] 410.32185 -1682.19487
[53,] -17.31205 410.32185
[54,] -792.54368 -17.31205
[55,] -207.62436 -792.54368
[56,] -50.47674 -207.62436
[57,] 53.14454 -50.47674
[58,] -1281.97238 53.14454
[59,] -1465.08715 -1281.97238
[60,] -1023.05783 -1465.08715
[61,] -476.30654 -1023.05783
[62,] -361.38305 -476.30654
[63,] -394.05926 -361.38305
[64,] -278.27179 -394.05926
[65,] -179.51343 -278.27179
[66,] -25.03167 -179.51343
[67,] 42.89063 -25.03167
[68,] -423.16652 42.89063
[69,] -1370.29142 -423.16652
[70,] -1733.62085 -1370.29142
[71,] -97.49861 -1733.62085
[72,] -874.34866 -97.49861
[73,] -2574.90620 -874.34866
[74,] -1965.56059 -2574.90620
[75,] -199.34009 -1965.56059
[76,] 2054.60316 -199.34009
[77,] 495.31603 2054.60316
[78,] 1263.78496 495.31603
[79,] 2700.82425 1263.78496
[80,] 2794.99369 2700.82425
[81,] 355.36622 2794.99369
[82,] 260.67944 355.36622
[83,] -2120.40353 260.67944
[84,] -8037.50278 -2120.40353
[85,] 10906.41177 -8037.50278
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -560.14490 2077.76595
2 1542.19678 -560.14490
3 1955.83749 1542.19678
4 391.82690 1955.83749
5 -532.07319 391.82690
6 -40.26005 -532.07319
7 -351.50900 -40.26005
8 484.28225 -351.50900
9 486.82866 484.28225
10 578.69919 486.82866
11 51.16224 578.69919
12 -81.93906 51.16224
13 -2463.61917 -81.93906
14 -601.37213 -2463.61917
15 323.56624 -601.37213
16 -485.03075 323.56624
17 -317.89205 -485.03075
18 1740.00262 -317.89205
19 -67.99475 1740.00262
20 624.51274 -67.99475
21 -1284.03817 624.51274
22 690.97180 -1284.03817
23 637.30491 690.97180
24 -41.18872 637.30491
25 -1506.54579 -41.18872
26 -304.93757 -1506.54579
27 -828.35722 -304.93757
28 -2252.70743 -828.35722
29 -2353.34090 -2252.70743
30 -357.57481 -2353.34090
31 -606.46874 -357.57481
32 -185.87556 -606.46874
33 -971.44878 -185.87556
34 93.54120 -971.44878
35 197.03130 93.54120
36 -911.32272 197.03130
37 -937.22361 -911.32272
38 522.25041 -937.22361
39 100.08225 522.25041
40 363.83781 100.08225
41 -245.07066 363.83781
42 1522.15419 -245.07066
43 1063.70017 1522.15419
44 1553.76191 1063.70017
45 1956.74819 1553.76191
46 -35.60905 1956.74819
47 948.13812 -35.60905
48 3888.98232 948.13812
49 1535.91145 3888.98232
50 -714.41475 1535.91145
51 -1682.19487 -714.41475
52 410.32185 -1682.19487
53 -17.31205 410.32185
54 -792.54368 -17.31205
55 -207.62436 -792.54368
56 -50.47674 -207.62436
57 53.14454 -50.47674
58 -1281.97238 53.14454
59 -1465.08715 -1281.97238
60 -1023.05783 -1465.08715
61 -476.30654 -1023.05783
62 -361.38305 -476.30654
63 -394.05926 -361.38305
64 -278.27179 -394.05926
65 -179.51343 -278.27179
66 -25.03167 -179.51343
67 42.89063 -25.03167
68 -423.16652 42.89063
69 -1370.29142 -423.16652
70 -1733.62085 -1370.29142
71 -97.49861 -1733.62085
72 -874.34866 -97.49861
73 -2574.90620 -874.34866
74 -1965.56059 -2574.90620
75 -199.34009 -1965.56059
76 2054.60316 -199.34009
77 495.31603 2054.60316
78 1263.78496 495.31603
79 2700.82425 1263.78496
80 2794.99369 2700.82425
81 355.36622 2794.99369
82 260.67944 355.36622
83 -2120.40353 260.67944
84 -8037.50278 -2120.40353
85 10906.41177 -8037.50278
> 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/7uv8b1259169675.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8unuh1259169675.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9cvhp1259169675.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10dnv81259169675.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/119ct71259169675.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/12whhq1259169675.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/13db641259169675.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/1429og1259169675.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/153q4a1259169675.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/16njkp1259169676.tab")
+ }
>
> system("convert tmp/1nywu1259169675.ps tmp/1nywu1259169675.png")
> system("convert tmp/292eq1259169675.ps tmp/292eq1259169675.png")
> system("convert tmp/3klty1259169675.ps tmp/3klty1259169675.png")
> system("convert tmp/4hy5f1259169675.ps tmp/4hy5f1259169675.png")
> system("convert tmp/5j0x01259169675.ps tmp/5j0x01259169675.png")
> system("convert tmp/6ankb1259169675.ps tmp/6ankb1259169675.png")
> system("convert tmp/7uv8b1259169675.ps tmp/7uv8b1259169675.png")
> system("convert tmp/8unuh1259169675.ps tmp/8unuh1259169675.png")
> system("convert tmp/9cvhp1259169675.ps tmp/9cvhp1259169675.png")
> system("convert tmp/10dnv81259169675.ps tmp/10dnv81259169675.png")
>
>
> proc.time()
user system elapsed
2.802 1.600 4.292