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(15335.63636
+ ,13845.66667
+ ,12823.61538
+ ,12792
+ ,10284.5
+ ,11188.5
+ ,15335.63636
+ ,13845.66667
+ ,12823.61538
+ ,12792
+ ,13633.25
+ ,11188.5
+ ,15335.63636
+ ,13845.66667
+ ,12823.61538
+ ,12298.46667
+ ,13633.25
+ ,11188.5
+ ,15335.63636
+ ,13845.66667
+ ,15353.63636
+ ,12298.46667
+ ,13633.25
+ ,11188.5
+ ,15335.63636
+ ,12696.15385
+ ,15353.63636
+ ,12298.46667
+ ,13633.25
+ ,11188.5
+ ,12213.93333
+ ,12696.15385
+ ,15353.63636
+ ,12298.46667
+ ,13633.25
+ ,13683.72727
+ ,12213.93333
+ ,12696.15385
+ ,15353.63636
+ ,12298.46667
+ ,11214.14286
+ ,13683.72727
+ ,12213.93333
+ ,12696.15385
+ ,15353.63636
+ ,13950.23077
+ ,11214.14286
+ ,13683.72727
+ ,12213.93333
+ ,12696.15385
+ ,11179.13333
+ ,13950.23077
+ ,11214.14286
+ ,13683.72727
+ ,12213.93333
+ ,11801.875
+ ,11179.13333
+ ,13950.23077
+ ,11214.14286
+ ,13683.72727
+ ,11188.82353
+ ,11801.875
+ ,11179.13333
+ ,13950.23077
+ ,11214.14286
+ ,16456.27273
+ ,11188.82353
+ ,11801.875
+ ,11179.13333
+ ,13950.23077
+ ,11110.0625
+ ,16456.27273
+ ,11188.82353
+ ,11801.875
+ ,11179.13333
+ ,16530.69231
+ ,11110.0625
+ ,16456.27273
+ ,11188.82353
+ ,11801.875
+ ,10038.41176
+ ,16530.69231
+ ,11110.0625
+ ,16456.27273
+ ,11188.82353
+ ,11681.25
+ ,10038.41176
+ ,16530.69231
+ ,11110.0625
+ ,16456.27273
+ ,11148.88235
+ ,11681.25
+ ,10038.41176
+ ,16530.69231
+ ,11110.0625
+ ,8631
+ ,11148.88235
+ ,11681.25
+ ,10038.41176
+ ,16530.69231
+ ,9386.444444
+ ,8631
+ ,11148.88235
+ ,11681.25
+ ,10038.41176
+ ,9764.736842
+ ,9386.444444
+ ,8631
+ ,11148.88235
+ ,11681.25
+ ,12043.75
+ ,9764.736842
+ ,9386.444444
+ ,8631
+ ,11148.88235
+ ,12948.06667
+ ,12043.75
+ ,9764.736842
+ ,9386.444444
+ ,8631
+ ,10987.125
+ ,12948.06667
+ ,12043.75
+ ,9764.736842
+ ,9386.444444
+ ,11648.3125
+ ,10987.125
+ ,12948.06667
+ ,12043.75
+ ,9764.736842
+ ,10633.35294
+ ,11648.3125
+ ,10987.125
+ ,12948.06667
+ ,12043.75
+ ,10219.3
+ ,10633.35294
+ ,11648.3125
+ ,10987.125
+ ,12948.06667
+ ,9037.6
+ ,10219.3
+ ,10633.35294
+ ,11648.3125
+ ,10987.125
+ ,10296.31579
+ ,9037.6
+ ,10219.3
+ ,10633.35294
+ ,11648.3125
+ ,11705.41176
+ ,10296.31579
+ ,9037.6
+ ,10219.3
+ ,10633.35294
+ ,10681.94444
+ ,11705.41176
+ ,10296.31579
+ ,9037.6
+ ,10219.3
+ ,9362.947368
+ ,10681.94444
+ ,11705.41176
+ ,10296.31579
+ ,9037.6
+ ,11306.35294
+ ,9362.947368
+ ,10681.94444
+ ,11705.41176
+ ,10296.31579
+ ,10984.45
+ ,11306.35294
+ ,9362.947368
+ ,10681.94444
+ ,11705.41176
+ ,10062.61905
+ ,10984.45
+ ,11306.35294
+ ,9362.947368
+ ,10681.94444
+ ,8118.583333
+ ,10062.61905
+ ,10984.45
+ ,11306.35294
+ ,9362.947368
+ ,8867.48
+ ,8118.583333
+ ,10062.61905
+ ,10984.45
+ ,11306.35294
+ ,8346.72
+ ,8867.48
+ ,8118.583333
+ ,10062.61905
+ ,10984.45
+ ,8529.307692
+ ,8346.72
+ ,8867.48
+ ,8118.583333
+ ,10062.61905
+ ,10697.18182
+ ,8529.307692
+ ,8346.72
+ ,8867.48
+ ,8118.583333
+ ,8591.84
+ ,10697.18182
+ ,8529.307692
+ ,8346.72
+ ,8867.48
+ ,8695.607143
+ ,8591.84
+ ,10697.18182
+ ,8529.307692
+ ,8346.72
+ ,8125.571429
+ ,8695.607143
+ ,8591.84
+ ,10697.18182
+ ,8529.307692
+ ,7009.758621
+ ,8125.571429
+ ,8695.607143
+ ,8591.84
+ ,10697.18182
+ ,7883.466667
+ ,7009.758621
+ ,8125.571429
+ ,8695.607143
+ ,8591.84
+ ,7527.645161
+ ,7883.466667
+ ,7009.758621
+ ,8125.571429
+ ,8695.607143
+ ,6763.758621
+ ,7527.645161
+ ,7883.466667
+ ,7009.758621
+ ,8125.571429
+ ,6682.333333
+ ,6763.758621
+ ,7527.645161
+ ,7883.466667
+ ,7009.758621
+ ,7855.681818
+ ,6682.333333
+ ,6763.758621
+ ,7527.645161
+ ,7883.466667
+ ,6738.88
+ ,7855.681818
+ ,6682.333333
+ ,6763.758621
+ ,7527.645161
+ ,7895.434783
+ ,6738.88
+ ,7855.681818
+ ,6682.333333
+ ,6763.758621
+ ,6361.884615
+ ,7895.434783
+ ,6738.88
+ ,7855.681818
+ ,6682.333333
+ ,6935.956522
+ ,6361.884615
+ ,7895.434783
+ ,6738.88
+ ,7855.681818
+ ,8344.454545
+ ,6935.956522
+ ,6361.884615
+ ,7895.434783
+ ,6738.88
+ ,9107.944444
+ ,8344.454545
+ ,6935.956522
+ ,6361.884615
+ ,7895.434783)
+ ,dim=c(5
+ ,56)
+ ,dimnames=list(c('Yt'
+ ,'Yt-1'
+ ,'Yt-2'
+ ,'Yt-3'
+ ,'Yt-4')
+ ,1:56))
> y <- array(NA,dim=c(5,56),dimnames=list(c('Yt','Yt-1','Yt-2','Yt-3','Yt-4'),1:56))
> 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
Yt Yt-1 Yt-2 Yt-3 Yt-4 M1 M2 M3 M4 M5 M6 M7 M8 M9
1 15335.636 13845.667 12823.615 12792.000 10284.500 1 0 0 0 0 0 0 0 0
2 11188.500 15335.636 13845.667 12823.615 12792.000 0 1 0 0 0 0 0 0 0
3 13633.250 11188.500 15335.636 13845.667 12823.615 0 0 1 0 0 0 0 0 0
4 12298.467 13633.250 11188.500 15335.636 13845.667 0 0 0 1 0 0 0 0 0
5 15353.636 12298.467 13633.250 11188.500 15335.636 0 0 0 0 1 0 0 0 0
6 12696.154 15353.636 12298.467 13633.250 11188.500 0 0 0 0 0 1 0 0 0
7 12213.933 12696.154 15353.636 12298.467 13633.250 0 0 0 0 0 0 1 0 0
8 13683.727 12213.933 12696.154 15353.636 12298.467 0 0 0 0 0 0 0 1 0
9 11214.143 13683.727 12213.933 12696.154 15353.636 0 0 0 0 0 0 0 0 1
10 13950.231 11214.143 13683.727 12213.933 12696.154 0 0 0 0 0 0 0 0 0
11 11179.133 13950.231 11214.143 13683.727 12213.933 0 0 0 0 0 0 0 0 0
12 11801.875 11179.133 13950.231 11214.143 13683.727 0 0 0 0 0 0 0 0 0
13 11188.824 11801.875 11179.133 13950.231 11214.143 1 0 0 0 0 0 0 0 0
14 16456.273 11188.824 11801.875 11179.133 13950.231 0 1 0 0 0 0 0 0 0
15 11110.062 16456.273 11188.824 11801.875 11179.133 0 0 1 0 0 0 0 0 0
16 16530.692 11110.062 16456.273 11188.824 11801.875 0 0 0 1 0 0 0 0 0
17 10038.412 16530.692 11110.062 16456.273 11188.824 0 0 0 0 1 0 0 0 0
18 11681.250 10038.412 16530.692 11110.062 16456.273 0 0 0 0 0 1 0 0 0
19 11148.882 11681.250 10038.412 16530.692 11110.062 0 0 0 0 0 0 1 0 0
20 8631.000 11148.882 11681.250 10038.412 16530.692 0 0 0 0 0 0 0 1 0
21 9386.444 8631.000 11148.882 11681.250 10038.412 0 0 0 0 0 0 0 0 1
22 9764.737 9386.444 8631.000 11148.882 11681.250 0 0 0 0 0 0 0 0 0
23 12043.750 9764.737 9386.444 8631.000 11148.882 0 0 0 0 0 0 0 0 0
24 12948.067 12043.750 9764.737 9386.444 8631.000 0 0 0 0 0 0 0 0 0
25 10987.125 12948.067 12043.750 9764.737 9386.444 1 0 0 0 0 0 0 0 0
26 11648.312 10987.125 12948.067 12043.750 9764.737 0 1 0 0 0 0 0 0 0
27 10633.353 11648.312 10987.125 12948.067 12043.750 0 0 1 0 0 0 0 0 0
28 10219.300 10633.353 11648.312 10987.125 12948.067 0 0 0 1 0 0 0 0 0
29 9037.600 10219.300 10633.353 11648.312 10987.125 0 0 0 0 1 0 0 0 0
30 10296.316 9037.600 10219.300 10633.353 11648.312 0 0 0 0 0 1 0 0 0
31 11705.412 10296.316 9037.600 10219.300 10633.353 0 0 0 0 0 0 1 0 0
32 10681.944 11705.412 10296.316 9037.600 10219.300 0 0 0 0 0 0 0 1 0
33 9362.947 10681.944 11705.412 10296.316 9037.600 0 0 0 0 0 0 0 0 1
34 11306.353 9362.947 10681.944 11705.412 10296.316 0 0 0 0 0 0 0 0 0
35 10984.450 11306.353 9362.947 10681.944 11705.412 0 0 0 0 0 0 0 0 0
36 10062.619 10984.450 11306.353 9362.947 10681.944 0 0 0 0 0 0 0 0 0
37 8118.583 10062.619 10984.450 11306.353 9362.947 1 0 0 0 0 0 0 0 0
38 8867.480 8118.583 10062.619 10984.450 11306.353 0 1 0 0 0 0 0 0 0
39 8346.720 8867.480 8118.583 10062.619 10984.450 0 0 1 0 0 0 0 0 0
40 8529.308 8346.720 8867.480 8118.583 10062.619 0 0 0 1 0 0 0 0 0
41 10697.182 8529.308 8346.720 8867.480 8118.583 0 0 0 0 1 0 0 0 0
42 8591.840 10697.182 8529.308 8346.720 8867.480 0 0 0 0 0 1 0 0 0
43 8695.607 8591.840 10697.182 8529.308 8346.720 0 0 0 0 0 0 1 0 0
44 8125.571 8695.607 8591.840 10697.182 8529.308 0 0 0 0 0 0 0 1 0
45 7009.759 8125.571 8695.607 8591.840 10697.182 0 0 0 0 0 0 0 0 1
46 7883.467 7009.759 8125.571 8695.607 8591.840 0 0 0 0 0 0 0 0 0
47 7527.645 7883.467 7009.759 8125.571 8695.607 0 0 0 0 0 0 0 0 0
48 6763.759 7527.645 7883.467 7009.759 8125.571 0 0 0 0 0 0 0 0 0
49 6682.333 6763.759 7527.645 7883.467 7009.759 1 0 0 0 0 0 0 0 0
50 7855.682 6682.333 6763.759 7527.645 7883.467 0 1 0 0 0 0 0 0 0
51 6738.880 7855.682 6682.333 6763.759 7527.645 0 0 1 0 0 0 0 0 0
52 7895.435 6738.880 7855.682 6682.333 6763.759 0 0 0 1 0 0 0 0 0
53 6361.885 7895.435 6738.880 7855.682 6682.333 0 0 0 0 1 0 0 0 0
54 6935.957 6361.885 7895.435 6738.880 7855.682 0 0 0 0 0 1 0 0 0
55 8344.455 6935.957 6361.885 7895.435 6738.880 0 0 0 0 0 0 1 0 0
56 9107.944 8344.455 6935.957 6361.885 7895.435 0 0 0 0 0 0 0 1 0
M10 M11 t
1 0 0 1
2 0 0 2
3 0 0 3
4 0 0 4
5 0 0 5
6 0 0 6
7 0 0 7
8 0 0 8
9 0 0 9
10 1 0 10
11 0 1 11
12 0 0 12
13 0 0 13
14 0 0 14
15 0 0 15
16 0 0 16
17 0 0 17
18 0 0 18
19 0 0 19
20 0 0 20
21 0 0 21
22 1 0 22
23 0 1 23
24 0 0 24
25 0 0 25
26 0 0 26
27 0 0 27
28 0 0 28
29 0 0 29
30 0 0 30
31 0 0 31
32 0 0 32
33 0 0 33
34 1 0 34
35 0 1 35
36 0 0 36
37 0 0 37
38 0 0 38
39 0 0 39
40 0 0 40
41 0 0 41
42 0 0 42
43 0 0 43
44 0 0 44
45 0 0 45
46 1 0 46
47 0 1 47
48 0 0 48
49 0 0 49
50 0 0 50
51 0 0 51
52 0 0 52
53 0 0 53
54 0 0 54
55 0 0 55
56 0 0 56
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `Yt-1` `Yt-2` `Yt-3` `Yt-4` M1
1.742e+04 -7.691e-02 2.898e-01 -2.297e-01 -2.482e-01 -4.827e+02
M2 M3 M4 M5 M6 M7
6.822e+02 -5.279e+01 7.047e+02 4.780e+02 -4.699e+01 6.554e+02
M8 M9 M10 M11 t
6.048e+02 -1.081e+03 5.817e+02 7.386e+02 -1.554e+02
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-3320.8 -706.3 -233.1 613.6 3995.1
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.742e+04 4.247e+03 4.103 0.000201 ***
`Yt-1` -7.691e-02 1.591e-01 -0.483 0.631464
`Yt-2` 2.898e-01 1.575e-01 1.840 0.073448 .
`Yt-3` -2.297e-01 1.535e-01 -1.497 0.142529
`Yt-4` -2.482e-01 1.544e-01 -1.607 0.116110
M1 -4.827e+02 1.029e+03 -0.469 0.641731
M2 6.822e+02 1.013e+03 0.674 0.504411
M3 -5.279e+01 1.018e+03 -0.052 0.958890
M4 7.047e+02 1.009e+03 0.698 0.489124
M5 4.780e+02 1.029e+03 0.464 0.644911
M6 -4.699e+01 1.007e+03 -0.047 0.963006
M7 6.554e+02 1.037e+03 0.632 0.531116
M8 6.048e+02 1.025e+03 0.590 0.558539
M9 -1.081e+03 1.069e+03 -1.012 0.317895
M10 5.817e+02 1.106e+03 0.526 0.601875
M11 7.386e+02 1.086e+03 0.680 0.500485
t -1.554e+02 3.928e+01 -3.956 0.000312 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1472 on 39 degrees of freedom
Multiple R-squared: 0.7502, Adjusted R-squared: 0.6477
F-statistic: 7.32 on 16 and 39 DF, p-value: 2.065e-07
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.9761288 0.0477424314 0.0238712157
[2,] 0.9996209 0.0007581933 0.0003790966
[3,] 0.9997378 0.0005244207 0.0002622103
[4,] 0.9991598 0.0016803414 0.0008401707
[5,] 0.9984729 0.0030541181 0.0015270590
[6,] 0.9960450 0.0079100303 0.0039550151
[7,] 0.9913368 0.0173264353 0.0086632177
[8,] 0.9833906 0.0332188574 0.0166094287
[9,] 0.9705725 0.0588549158 0.0294274579
[10,] 0.9739595 0.0520809758 0.0260404879
[11,] 0.9488958 0.1022084844 0.0511042422
[12,] 0.9150547 0.1698905947 0.0849452973
[13,] 0.8729478 0.2541043924 0.1270521962
[14,] 0.7881299 0.4237402273 0.2118701137
[15,] 0.7642062 0.4715876035 0.2357938017
[16,] 0.6853562 0.6292875118 0.3146437559
[17,] 0.6034964 0.7930072604 0.3965036302
> postscript(file="/var/www/html/rcomp/tmp/1pq141258728656.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2ptuz1258728656.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/34uwm1258728656.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4fl4n1258728656.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/528d21258728656.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 = 56
Frequency = 1
1 2 3 4 5 6
1387.847648 -3320.767110 -493.740358 -444.965572 1598.609067 -224.526671
7 8 9 10 11 12
-2043.219283 735.921923 508.589086 350.888856 -1277.674971 -969.319199
13 14 15 16 17 18
-77.924396 3995.085600 -422.655351 2471.975738 -614.405013 -281.779535
19 20 21 22 23 24
564.642940 -2409.932092 -1086.431838 -1142.489024 234.882417 1647.419638
25 26 27 28 29 30
8.053491 -135.857437 1132.071568 -379.674914 -1251.791705 647.445250
31 32 33 34 35 36
1601.842220 153.792544 185.016170 1451.993132 1775.046151 602.335836
37 38 39 40 41 42
-562.278138 -296.845916 402.201867 -949.671983 1454.797819 209.960178
43 44 45 46 47 48
-1110.699067 -313.494041 392.826582 -660.392965 -732.253597 -1280.436275
49 50 51 52 53 54
-755.698606 -241.615137 -617.877727 -697.663270 -1187.210167 -351.099223
55 56
987.433191 1833.711665
> postscript(file="/var/www/html/rcomp/tmp/6nmse1258728656.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 = 56
Frequency = 1
lag(myerror, k = 1) myerror
0 1387.847648 NA
1 -3320.767110 1387.847648
2 -493.740358 -3320.767110
3 -444.965572 -493.740358
4 1598.609067 -444.965572
5 -224.526671 1598.609067
6 -2043.219283 -224.526671
7 735.921923 -2043.219283
8 508.589086 735.921923
9 350.888856 508.589086
10 -1277.674971 350.888856
11 -969.319199 -1277.674971
12 -77.924396 -969.319199
13 3995.085600 -77.924396
14 -422.655351 3995.085600
15 2471.975738 -422.655351
16 -614.405013 2471.975738
17 -281.779535 -614.405013
18 564.642940 -281.779535
19 -2409.932092 564.642940
20 -1086.431838 -2409.932092
21 -1142.489024 -1086.431838
22 234.882417 -1142.489024
23 1647.419638 234.882417
24 8.053491 1647.419638
25 -135.857437 8.053491
26 1132.071568 -135.857437
27 -379.674914 1132.071568
28 -1251.791705 -379.674914
29 647.445250 -1251.791705
30 1601.842220 647.445250
31 153.792544 1601.842220
32 185.016170 153.792544
33 1451.993132 185.016170
34 1775.046151 1451.993132
35 602.335836 1775.046151
36 -562.278138 602.335836
37 -296.845916 -562.278138
38 402.201867 -296.845916
39 -949.671983 402.201867
40 1454.797819 -949.671983
41 209.960178 1454.797819
42 -1110.699067 209.960178
43 -313.494041 -1110.699067
44 392.826582 -313.494041
45 -660.392965 392.826582
46 -732.253597 -660.392965
47 -1280.436275 -732.253597
48 -755.698606 -1280.436275
49 -241.615137 -755.698606
50 -617.877727 -241.615137
51 -697.663270 -617.877727
52 -1187.210167 -697.663270
53 -351.099223 -1187.210167
54 987.433191 -351.099223
55 1833.711665 987.433191
56 NA 1833.711665
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -3320.767110 1387.847648
[2,] -493.740358 -3320.767110
[3,] -444.965572 -493.740358
[4,] 1598.609067 -444.965572
[5,] -224.526671 1598.609067
[6,] -2043.219283 -224.526671
[7,] 735.921923 -2043.219283
[8,] 508.589086 735.921923
[9,] 350.888856 508.589086
[10,] -1277.674971 350.888856
[11,] -969.319199 -1277.674971
[12,] -77.924396 -969.319199
[13,] 3995.085600 -77.924396
[14,] -422.655351 3995.085600
[15,] 2471.975738 -422.655351
[16,] -614.405013 2471.975738
[17,] -281.779535 -614.405013
[18,] 564.642940 -281.779535
[19,] -2409.932092 564.642940
[20,] -1086.431838 -2409.932092
[21,] -1142.489024 -1086.431838
[22,] 234.882417 -1142.489024
[23,] 1647.419638 234.882417
[24,] 8.053491 1647.419638
[25,] -135.857437 8.053491
[26,] 1132.071568 -135.857437
[27,] -379.674914 1132.071568
[28,] -1251.791705 -379.674914
[29,] 647.445250 -1251.791705
[30,] 1601.842220 647.445250
[31,] 153.792544 1601.842220
[32,] 185.016170 153.792544
[33,] 1451.993132 185.016170
[34,] 1775.046151 1451.993132
[35,] 602.335836 1775.046151
[36,] -562.278138 602.335836
[37,] -296.845916 -562.278138
[38,] 402.201867 -296.845916
[39,] -949.671983 402.201867
[40,] 1454.797819 -949.671983
[41,] 209.960178 1454.797819
[42,] -1110.699067 209.960178
[43,] -313.494041 -1110.699067
[44,] 392.826582 -313.494041
[45,] -660.392965 392.826582
[46,] -732.253597 -660.392965
[47,] -1280.436275 -732.253597
[48,] -755.698606 -1280.436275
[49,] -241.615137 -755.698606
[50,] -617.877727 -241.615137
[51,] -697.663270 -617.877727
[52,] -1187.210167 -697.663270
[53,] -351.099223 -1187.210167
[54,] 987.433191 -351.099223
[55,] 1833.711665 987.433191
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -3320.767110 1387.847648
2 -493.740358 -3320.767110
3 -444.965572 -493.740358
4 1598.609067 -444.965572
5 -224.526671 1598.609067
6 -2043.219283 -224.526671
7 735.921923 -2043.219283
8 508.589086 735.921923
9 350.888856 508.589086
10 -1277.674971 350.888856
11 -969.319199 -1277.674971
12 -77.924396 -969.319199
13 3995.085600 -77.924396
14 -422.655351 3995.085600
15 2471.975738 -422.655351
16 -614.405013 2471.975738
17 -281.779535 -614.405013
18 564.642940 -281.779535
19 -2409.932092 564.642940
20 -1086.431838 -2409.932092
21 -1142.489024 -1086.431838
22 234.882417 -1142.489024
23 1647.419638 234.882417
24 8.053491 1647.419638
25 -135.857437 8.053491
26 1132.071568 -135.857437
27 -379.674914 1132.071568
28 -1251.791705 -379.674914
29 647.445250 -1251.791705
30 1601.842220 647.445250
31 153.792544 1601.842220
32 185.016170 153.792544
33 1451.993132 185.016170
34 1775.046151 1451.993132
35 602.335836 1775.046151
36 -562.278138 602.335836
37 -296.845916 -562.278138
38 402.201867 -296.845916
39 -949.671983 402.201867
40 1454.797819 -949.671983
41 209.960178 1454.797819
42 -1110.699067 209.960178
43 -313.494041 -1110.699067
44 392.826582 -313.494041
45 -660.392965 392.826582
46 -732.253597 -660.392965
47 -1280.436275 -732.253597
48 -755.698606 -1280.436275
49 -241.615137 -755.698606
50 -617.877727 -241.615137
51 -697.663270 -617.877727
52 -1187.210167 -697.663270
53 -351.099223 -1187.210167
54 987.433191 -351.099223
55 1833.711665 987.433191
> 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/7r0ln1258728656.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8x1971258728656.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/97vjp1258728656.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ik6m1258728656.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11r2vl1258728656.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/12s3bz1258728656.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/13wd4n1258728656.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/14rs841258728656.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/15oqvs1258728656.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/16zjvd1258728656.tab")
+ }
>
> system("convert tmp/1pq141258728656.ps tmp/1pq141258728656.png")
> system("convert tmp/2ptuz1258728656.ps tmp/2ptuz1258728656.png")
> system("convert tmp/34uwm1258728656.ps tmp/34uwm1258728656.png")
> system("convert tmp/4fl4n1258728656.ps tmp/4fl4n1258728656.png")
> system("convert tmp/528d21258728656.ps tmp/528d21258728656.png")
> system("convert tmp/6nmse1258728656.ps tmp/6nmse1258728656.png")
> system("convert tmp/7r0ln1258728656.ps tmp/7r0ln1258728656.png")
> system("convert tmp/8x1971258728656.ps tmp/8x1971258728656.png")
> system("convert tmp/97vjp1258728656.ps tmp/97vjp1258728656.png")
> system("convert tmp/10ik6m1258728656.ps tmp/10ik6m1258728656.png")
>
>
> proc.time()
user system elapsed
2.366 1.556 2.775