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(17972385.83
+ ,0
+ ,17637387.4
+ ,15213975.95
+ ,16471559.62
+ ,14731798.37
+ ,16896235.55
+ ,0
+ ,17972385.83
+ ,17637387.4
+ ,15213975.95
+ ,16471559.62
+ ,16697955.94
+ ,0
+ ,16896235.55
+ ,17972385.83
+ ,17637387.4
+ ,15213975.95
+ ,19691579.52
+ ,0
+ ,16697955.94
+ ,16896235.55
+ ,17972385.83
+ ,17637387.4
+ ,15930700.75
+ ,0
+ ,19691579.52
+ ,16697955.94
+ ,16896235.55
+ ,17972385.83
+ ,17444615.98
+ ,0
+ ,15930700.75
+ ,19691579.52
+ ,16697955.94
+ ,16896235.55
+ ,17699369.88
+ ,0
+ ,17444615.98
+ ,15930700.75
+ ,19691579.52
+ ,16697955.94
+ ,15189796.81
+ ,0
+ ,17699369.88
+ ,17444615.98
+ ,15930700.75
+ ,19691579.52
+ ,15672722.75
+ ,0
+ ,15189796.81
+ ,17699369.88
+ ,17444615.98
+ ,15930700.75
+ ,17180794.3
+ ,0
+ ,15672722.75
+ ,15189796.81
+ ,17699369.88
+ ,17444615.98
+ ,17664893.45
+ ,0
+ ,17180794.3
+ ,15672722.75
+ ,15189796.81
+ ,17699369.88
+ ,17862884.98
+ ,0
+ ,17664893.45
+ ,17180794.3
+ ,15672722.75
+ ,15189796.81
+ ,16162288.88
+ ,0
+ ,17862884.98
+ ,17664893.45
+ ,17180794.3
+ ,15672722.75
+ ,17463628.82
+ ,0
+ ,16162288.88
+ ,17862884.98
+ ,17664893.45
+ ,17180794.3
+ ,16772112.17
+ ,0
+ ,17463628.82
+ ,16162288.88
+ ,17862884.98
+ ,17664893.45
+ ,19106861.48
+ ,0
+ ,16772112.17
+ ,17463628.82
+ ,16162288.88
+ ,17862884.98
+ ,16721314.25
+ ,0
+ ,19106861.48
+ ,16772112.17
+ ,17463628.82
+ ,16162288.88
+ ,18161267.85
+ ,0
+ ,16721314.25
+ ,19106861.48
+ ,16772112.17
+ ,17463628.82
+ ,18509941.2
+ ,0
+ ,18161267.85
+ ,16721314.25
+ ,19106861.48
+ ,16772112.17
+ ,17802737.97
+ ,0
+ ,18509941.2
+ ,18161267.85
+ ,16721314.25
+ ,19106861.48
+ ,16409869.75
+ ,0
+ ,17802737.97
+ ,18509941.2
+ ,18161267.85
+ ,16721314.25
+ ,17967742.04
+ ,0
+ ,16409869.75
+ ,17802737.97
+ ,18509941.2
+ ,18161267.85
+ ,20286602.27
+ ,0
+ ,17967742.04
+ ,16409869.75
+ ,17802737.97
+ ,18509941.2
+ ,19537280.81
+ ,0
+ ,20286602.27
+ ,17967742.04
+ ,16409869.75
+ ,17802737.97
+ ,18021889.62
+ ,0
+ ,19537280.81
+ ,20286602.27
+ ,17967742.04
+ ,16409869.75
+ ,20194317.23
+ ,0
+ ,18021889.62
+ ,19537280.81
+ ,20286602.27
+ ,17967742.04
+ ,19049596.62
+ ,0
+ ,20194317.23
+ ,18021889.62
+ ,19537280.81
+ ,20286602.27
+ ,20244720.94
+ ,0
+ ,19049596.62
+ ,20194317.23
+ ,18021889.62
+ ,19537280.81
+ ,21473302.24
+ ,0
+ ,20244720.94
+ ,19049596.62
+ ,20194317.23
+ ,18021889.62
+ ,19673603.19
+ ,0
+ ,21473302.24
+ ,20244720.94
+ ,19049596.62
+ ,20194317.23
+ ,21053177.29
+ ,0
+ ,19673603.19
+ ,21473302.24
+ ,20244720.94
+ ,19049596.62
+ ,20159479.84
+ ,0
+ ,21053177.29
+ ,19673603.19
+ ,21473302.24
+ ,20244720.94
+ ,18203628.31
+ ,0
+ ,20159479.84
+ ,21053177.29
+ ,19673603.19
+ ,21473302.24
+ ,21289464.94
+ ,0
+ ,18203628.31
+ ,20159479.84
+ ,21053177.29
+ ,19673603.19
+ ,20432335.71
+ ,1
+ ,21289464.94
+ ,18203628.31
+ ,20159479.84
+ ,21053177.29
+ ,17180395.07
+ ,1
+ ,20432335.71
+ ,21289464.94
+ ,18203628.31
+ ,20159479.84
+ ,15816786.32
+ ,1
+ ,17180395.07
+ ,20432335.71
+ ,21289464.94
+ ,18203628.31
+ ,15071819.75
+ ,1
+ ,15816786.32
+ ,17180395.07
+ ,20432335.71
+ ,21289464.94
+ ,14521120.61
+ ,1
+ ,15071819.75
+ ,15816786.32
+ ,17180395.07
+ ,20432335.71
+ ,15668789.39
+ ,1
+ ,14521120.61
+ ,15071819.75
+ ,15816786.32
+ ,17180395.07
+ ,14346884.11
+ ,1
+ ,15668789.39
+ ,14521120.61
+ ,15071819.75
+ ,15816786.32
+ ,13881008.13
+ ,1
+ ,14346884.11
+ ,15668789.39
+ ,14521120.61
+ ,15071819.75
+ ,15465943.69
+ ,1
+ ,13881008.13
+ ,14346884.11
+ ,15668789.39
+ ,14521120.61
+ ,14238232.92
+ ,1
+ ,15465943.69
+ ,13881008.13
+ ,14346884.11
+ ,15668789.39
+ ,13557713.21
+ ,1
+ ,14238232.92
+ ,15465943.69
+ ,13881008.13
+ ,14346884.11
+ ,16127590.29
+ ,1
+ ,13557713.21
+ ,14238232.92
+ ,15465943.69
+ ,13881008.13
+ ,16793894.2
+ ,1
+ ,16127590.29
+ ,13557713.21
+ ,14238232.92
+ ,15465943.69
+ ,16014007.43
+ ,1
+ ,16793894.2
+ ,16127590.29
+ ,13557713.21
+ ,14238232.92
+ ,16867867.15
+ ,1
+ ,16014007.43
+ ,16793894.2
+ ,16127590.29
+ ,13557713.21
+ ,16014583.21
+ ,1
+ ,16867867.15
+ ,16014007.43
+ ,16793894.2
+ ,16127590.29
+ ,15878594.85
+ ,1
+ ,16014583.21
+ ,16867867.15
+ ,16014007.43
+ ,16793894.2
+ ,18664899.14
+ ,1
+ ,15878594.85
+ ,16014583.21
+ ,16867867.15
+ ,16014007.43
+ ,17962530.06
+ ,1
+ ,18664899.14
+ ,15878594.85
+ ,16014583.21
+ ,16867867.15
+ ,17332692.2
+ ,1
+ ,17962530.06
+ ,18664899.14
+ ,15878594.85
+ ,16014583.21
+ ,19542066.35
+ ,1
+ ,17332692.2
+ ,17962530.06
+ ,18664899.14
+ ,15878594.85
+ ,17203555.19
+ ,1
+ ,19542066.35
+ ,17332692.2
+ ,17962530.06
+ ,18664899.14)
+ ,dim=c(6
+ ,56)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:56))
> y <- array(NA,dim=c(6,56),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:56))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par20 = ''
> par19 = ''
> par18 = ''
> par17 = ''
> par16 = ''
> par15 = ''
> par14 = ''
> par13 = ''
> par12 = ''
> par11 = ''
> par10 = ''
> par9 = ''
> par8 = ''
> par7 = ''
> par6 = ''
> par5 = ''
> par4 = ''
> par3 = 'Linear Trend'
> par2 = 'Include Monthly Dummies'
> par1 = '1'
> ylab = ''
> xlab = ''
> main = ''
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Y X Y1 Y2 Y3 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9
1 17972386 0 17637387 15213976 16471560 14731798 1 0 0 0 0 0 0 0 0
2 16896236 0 17972386 17637387 15213976 16471560 0 1 0 0 0 0 0 0 0
3 16697956 0 16896236 17972386 17637387 15213976 0 0 1 0 0 0 0 0 0
4 19691580 0 16697956 16896236 17972386 17637387 0 0 0 1 0 0 0 0 0
5 15930701 0 19691580 16697956 16896236 17972386 0 0 0 0 1 0 0 0 0
6 17444616 0 15930701 19691580 16697956 16896236 0 0 0 0 0 1 0 0 0
7 17699370 0 17444616 15930701 19691580 16697956 0 0 0 0 0 0 1 0 0
8 15189797 0 17699370 17444616 15930701 19691580 0 0 0 0 0 0 0 1 0
9 15672723 0 15189797 17699370 17444616 15930701 0 0 0 0 0 0 0 0 1
10 17180794 0 15672723 15189797 17699370 17444616 0 0 0 0 0 0 0 0 0
11 17664893 0 17180794 15672723 15189797 17699370 0 0 0 0 0 0 0 0 0
12 17862885 0 17664893 17180794 15672723 15189797 0 0 0 0 0 0 0 0 0
13 16162289 0 17862885 17664893 17180794 15672723 1 0 0 0 0 0 0 0 0
14 17463629 0 16162289 17862885 17664893 17180794 0 1 0 0 0 0 0 0 0
15 16772112 0 17463629 16162289 17862885 17664893 0 0 1 0 0 0 0 0 0
16 19106861 0 16772112 17463629 16162289 17862885 0 0 0 1 0 0 0 0 0
17 16721314 0 19106861 16772112 17463629 16162289 0 0 0 0 1 0 0 0 0
18 18161268 0 16721314 19106861 16772112 17463629 0 0 0 0 0 1 0 0 0
19 18509941 0 18161268 16721314 19106861 16772112 0 0 0 0 0 0 1 0 0
20 17802738 0 18509941 18161268 16721314 19106861 0 0 0 0 0 0 0 1 0
21 16409870 0 17802738 18509941 18161268 16721314 0 0 0 0 0 0 0 0 1
22 17967742 0 16409870 17802738 18509941 18161268 0 0 0 0 0 0 0 0 0
23 20286602 0 17967742 16409870 17802738 18509941 0 0 0 0 0 0 0 0 0
24 19537281 0 20286602 17967742 16409870 17802738 0 0 0 0 0 0 0 0 0
25 18021890 0 19537281 20286602 17967742 16409870 1 0 0 0 0 0 0 0 0
26 20194317 0 18021890 19537281 20286602 17967742 0 1 0 0 0 0 0 0 0
27 19049597 0 20194317 18021890 19537281 20286602 0 0 1 0 0 0 0 0 0
28 20244721 0 19049597 20194317 18021890 19537281 0 0 0 1 0 0 0 0 0
29 21473302 0 20244721 19049597 20194317 18021890 0 0 0 0 1 0 0 0 0
30 19673603 0 21473302 20244721 19049597 20194317 0 0 0 0 0 1 0 0 0
31 21053177 0 19673603 21473302 20244721 19049597 0 0 0 0 0 0 1 0 0
32 20159480 0 21053177 19673603 21473302 20244721 0 0 0 0 0 0 0 1 0
33 18203628 0 20159480 21053177 19673603 21473302 0 0 0 0 0 0 0 0 1
34 21289465 0 18203628 20159480 21053177 19673603 0 0 0 0 0 0 0 0 0
35 20432336 1 21289465 18203628 20159480 21053177 0 0 0 0 0 0 0 0 0
36 17180395 1 20432336 21289465 18203628 20159480 0 0 0 0 0 0 0 0 0
37 15816786 1 17180395 20432336 21289465 18203628 1 0 0 0 0 0 0 0 0
38 15071820 1 15816786 17180395 20432336 21289465 0 1 0 0 0 0 0 0 0
39 14521121 1 15071820 15816786 17180395 20432336 0 0 1 0 0 0 0 0 0
40 15668789 1 14521121 15071820 15816786 17180395 0 0 0 1 0 0 0 0 0
41 14346884 1 15668789 14521121 15071820 15816786 0 0 0 0 1 0 0 0 0
42 13881008 1 14346884 15668789 14521121 15071820 0 0 0 0 0 1 0 0 0
43 15465944 1 13881008 14346884 15668789 14521121 0 0 0 0 0 0 1 0 0
44 14238233 1 15465944 13881008 14346884 15668789 0 0 0 0 0 0 0 1 0
45 13557713 1 14238233 15465944 13881008 14346884 0 0 0 0 0 0 0 0 1
46 16127590 1 13557713 14238233 15465944 13881008 0 0 0 0 0 0 0 0 0
47 16793894 1 16127590 13557713 14238233 15465944 0 0 0 0 0 0 0 0 0
48 16014007 1 16793894 16127590 13557713 14238233 0 0 0 0 0 0 0 0 0
49 16867867 1 16014007 16793894 16127590 13557713 1 0 0 0 0 0 0 0 0
50 16014583 1 16867867 16014007 16793894 16127590 0 1 0 0 0 0 0 0 0
51 15878595 1 16014583 16867867 16014007 16793894 0 0 1 0 0 0 0 0 0
52 18664899 1 15878595 16014583 16867867 16014007 0 0 0 1 0 0 0 0 0
53 17962530 1 18664899 15878595 16014583 16867867 0 0 0 0 1 0 0 0 0
54 17332692 1 17962530 18664899 15878595 16014583 0 0 0 0 0 1 0 0 0
55 19542066 1 17332692 17962530 18664899 15878595 0 0 0 0 0 0 1 0 0
56 17203555 1 19542066 17332692 17962530 18664899 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) X Y1 Y2 Y3 Y4
7.058e+06 -2.794e+06 3.603e-01 1.520e-01 3.746e-01 -3.206e-01
M1 M2 M3 M4 M5 M6
-1.278e+06 -3.012e+05 -6.140e+05 1.702e+06 -6.971e+05 -3.108e+05
M7 M8 M9 M10 M11 t
3.103e+04 -7.945e+05 -1.914e+06 4.473e+05 1.871e+06 6.269e+04
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1498952 -536456 48795 442203 2015070
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 7.058e+06 1.705e+06 4.138 0.000187 ***
X -2.794e+06 6.268e+05 -4.457 7.12e-05 ***
Y1 3.603e-01 1.264e-01 2.851 0.007004 **
Y2 1.520e-01 1.226e-01 1.241 0.222379
Y3 3.746e-01 1.201e-01 3.120 0.003448 **
Y4 -3.206e-01 1.109e-01 -2.892 0.006300 **
M1 -1.278e+06 6.475e+05 -1.973 0.055753 .
M2 -3.012e+05 6.755e+05 -0.446 0.658213
M3 -6.140e+05 6.748e+05 -0.910 0.368640
M4 1.702e+06 6.684e+05 2.546 0.015057 *
M5 -6.971e+05 6.217e+05 -1.121 0.269190
M6 -3.108e+05 6.120e+05 -0.508 0.614573
M7 3.103e+04 7.215e+05 0.043 0.965917
M8 -7.945e+05 6.378e+05 -1.246 0.220521
M9 -1.914e+06 6.937e+05 -2.759 0.008872 **
M10 4.473e+05 8.204e+05 0.545 0.588791
M11 1.871e+06 6.836e+05 2.737 0.009371 **
t 6.269e+04 1.639e+04 3.825 0.000473 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 822600 on 38 degrees of freedom
Multiple R-squared: 0.877, Adjusted R-squared: 0.822
F-statistic: 15.94 on 17 and 38 DF, p-value: 2.464e-12
> 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,] 0.8299735 0.3400530 0.1700265
[2,] 0.8331479 0.3337041 0.1668521
[3,] 0.7876216 0.4247569 0.2123784
[4,] 0.7574487 0.4851026 0.2425513
[5,] 0.6634802 0.6730395 0.3365198
[6,] 0.6663547 0.6672905 0.3336453
[7,] 0.6328071 0.7343858 0.3671929
[8,] 0.5119441 0.9761119 0.4880559
[9,] 0.8798021 0.2403958 0.1201979
[10,] 0.8980771 0.2038457 0.1019229
[11,] 0.8915004 0.2169992 0.1084996
[12,] 0.8189367 0.3621267 0.1810633
[13,] 0.8121994 0.3756012 0.1878006
[14,] 0.6858475 0.6283050 0.3141525
[15,] 0.6108650 0.7782699 0.3891350
> postscript(file="/var/www/html/rcomp/tmp/1cc6c1292938115.ps",horizontal=F,onefile=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2cc6c1292938115.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3436x1292938115.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4436x1292938115.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5436x1292938115.ps",horizontal=F,onefile=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
2015069.79 439344.12 -482964.99 1018445.14 -943853.59 750123.62
7 8 9 10 11 12
-558086.76 -258344.61 373862.99 55647.31 -541839.28 75343.30
13 14 15 16 17 18
-965144.60 181767.71 -388913.85 318783.74 -1498952.23 672723.68
19 20 21 22 23 24
-635388.71 717741.02 -720860.24 -646366.80 213194.35 494894.83
25 26 27 28 29 30
-918109.29 505939.87 83122.47 -691058.16 1317955.55 -429873.64
31 32 33 34 35 36
192188.87 -239111.97 41942.68 450777.68 863306.42 -294552.98
37 38 39 40 41 42
-923994.28 -412021.50 706340.05 -744971.42 -218266.40 -863981.51
43 44 45 46 47 48
78892.25 -23126.80 305054.57 139941.82 -534661.50 -275685.15
49 50 51 52 53 54
792178.37 -715030.19 82416.32 98800.69 1343116.67 -128992.16
55 56
922394.35 -197157.65
> postscript(file="/var/www/html/rcomp/tmp/6fcn01292938115.ps",horizontal=F,onefile=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 2015069.79 NA
1 439344.12 2015069.79
2 -482964.99 439344.12
3 1018445.14 -482964.99
4 -943853.59 1018445.14
5 750123.62 -943853.59
6 -558086.76 750123.62
7 -258344.61 -558086.76
8 373862.99 -258344.61
9 55647.31 373862.99
10 -541839.28 55647.31
11 75343.30 -541839.28
12 -965144.60 75343.30
13 181767.71 -965144.60
14 -388913.85 181767.71
15 318783.74 -388913.85
16 -1498952.23 318783.74
17 672723.68 -1498952.23
18 -635388.71 672723.68
19 717741.02 -635388.71
20 -720860.24 717741.02
21 -646366.80 -720860.24
22 213194.35 -646366.80
23 494894.83 213194.35
24 -918109.29 494894.83
25 505939.87 -918109.29
26 83122.47 505939.87
27 -691058.16 83122.47
28 1317955.55 -691058.16
29 -429873.64 1317955.55
30 192188.87 -429873.64
31 -239111.97 192188.87
32 41942.68 -239111.97
33 450777.68 41942.68
34 863306.42 450777.68
35 -294552.98 863306.42
36 -923994.28 -294552.98
37 -412021.50 -923994.28
38 706340.05 -412021.50
39 -744971.42 706340.05
40 -218266.40 -744971.42
41 -863981.51 -218266.40
42 78892.25 -863981.51
43 -23126.80 78892.25
44 305054.57 -23126.80
45 139941.82 305054.57
46 -534661.50 139941.82
47 -275685.15 -534661.50
48 792178.37 -275685.15
49 -715030.19 792178.37
50 82416.32 -715030.19
51 98800.69 82416.32
52 1343116.67 98800.69
53 -128992.16 1343116.67
54 922394.35 -128992.16
55 -197157.65 922394.35
56 NA -197157.65
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 439344.12 2015069.79
[2,] -482964.99 439344.12
[3,] 1018445.14 -482964.99
[4,] -943853.59 1018445.14
[5,] 750123.62 -943853.59
[6,] -558086.76 750123.62
[7,] -258344.61 -558086.76
[8,] 373862.99 -258344.61
[9,] 55647.31 373862.99
[10,] -541839.28 55647.31
[11,] 75343.30 -541839.28
[12,] -965144.60 75343.30
[13,] 181767.71 -965144.60
[14,] -388913.85 181767.71
[15,] 318783.74 -388913.85
[16,] -1498952.23 318783.74
[17,] 672723.68 -1498952.23
[18,] -635388.71 672723.68
[19,] 717741.02 -635388.71
[20,] -720860.24 717741.02
[21,] -646366.80 -720860.24
[22,] 213194.35 -646366.80
[23,] 494894.83 213194.35
[24,] -918109.29 494894.83
[25,] 505939.87 -918109.29
[26,] 83122.47 505939.87
[27,] -691058.16 83122.47
[28,] 1317955.55 -691058.16
[29,] -429873.64 1317955.55
[30,] 192188.87 -429873.64
[31,] -239111.97 192188.87
[32,] 41942.68 -239111.97
[33,] 450777.68 41942.68
[34,] 863306.42 450777.68
[35,] -294552.98 863306.42
[36,] -923994.28 -294552.98
[37,] -412021.50 -923994.28
[38,] 706340.05 -412021.50
[39,] -744971.42 706340.05
[40,] -218266.40 -744971.42
[41,] -863981.51 -218266.40
[42,] 78892.25 -863981.51
[43,] -23126.80 78892.25
[44,] 305054.57 -23126.80
[45,] 139941.82 305054.57
[46,] -534661.50 139941.82
[47,] -275685.15 -534661.50
[48,] 792178.37 -275685.15
[49,] -715030.19 792178.37
[50,] 82416.32 -715030.19
[51,] 98800.69 82416.32
[52,] 1343116.67 98800.69
[53,] -128992.16 1343116.67
[54,] 922394.35 -128992.16
[55,] -197157.65 922394.35
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 439344.12 2015069.79
2 -482964.99 439344.12
3 1018445.14 -482964.99
4 -943853.59 1018445.14
5 750123.62 -943853.59
6 -558086.76 750123.62
7 -258344.61 -558086.76
8 373862.99 -258344.61
9 55647.31 373862.99
10 -541839.28 55647.31
11 75343.30 -541839.28
12 -965144.60 75343.30
13 181767.71 -965144.60
14 -388913.85 181767.71
15 318783.74 -388913.85
16 -1498952.23 318783.74
17 672723.68 -1498952.23
18 -635388.71 672723.68
19 717741.02 -635388.71
20 -720860.24 717741.02
21 -646366.80 -720860.24
22 213194.35 -646366.80
23 494894.83 213194.35
24 -918109.29 494894.83
25 505939.87 -918109.29
26 83122.47 505939.87
27 -691058.16 83122.47
28 1317955.55 -691058.16
29 -429873.64 1317955.55
30 192188.87 -429873.64
31 -239111.97 192188.87
32 41942.68 -239111.97
33 450777.68 41942.68
34 863306.42 450777.68
35 -294552.98 863306.42
36 -923994.28 -294552.98
37 -412021.50 -923994.28
38 706340.05 -412021.50
39 -744971.42 706340.05
40 -218266.40 -744971.42
41 -863981.51 -218266.40
42 78892.25 -863981.51
43 -23126.80 78892.25
44 305054.57 -23126.80
45 139941.82 305054.57
46 -534661.50 139941.82
47 -275685.15 -534661.50
48 792178.37 -275685.15
49 -715030.19 792178.37
50 82416.32 -715030.19
51 98800.69 82416.32
52 1343116.67 98800.69
53 -128992.16 1343116.67
54 922394.35 -128992.16
55 -197157.65 922394.35
> 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/784431292938115.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/884431292938115.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/984431292938115.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10jvlo1292938115.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11mv2c1292938115.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/12pei01292938115.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/13wfxb1292938115.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/147ofw1292938115.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/15apdk1292938115.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/16d7uq1292938115.tab")
+ }
>
> try(system("convert tmp/1cc6c1292938115.ps tmp/1cc6c1292938115.png",intern=TRUE))
character(0)
> try(system("convert tmp/2cc6c1292938115.ps tmp/2cc6c1292938115.png",intern=TRUE))
character(0)
> try(system("convert tmp/3436x1292938115.ps tmp/3436x1292938115.png",intern=TRUE))
character(0)
> try(system("convert tmp/4436x1292938115.ps tmp/4436x1292938115.png",intern=TRUE))
character(0)
> try(system("convert tmp/5436x1292938115.ps tmp/5436x1292938115.png",intern=TRUE))
character(0)
> try(system("convert tmp/6fcn01292938115.ps tmp/6fcn01292938115.png",intern=TRUE))
character(0)
> try(system("convert tmp/784431292938115.ps tmp/784431292938115.png",intern=TRUE))
character(0)
> try(system("convert tmp/884431292938115.ps tmp/884431292938115.png",intern=TRUE))
character(0)
> try(system("convert tmp/984431292938115.ps tmp/984431292938115.png",intern=TRUE))
character(0)
> try(system("convert tmp/10jvlo1292938115.ps tmp/10jvlo1292938115.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.416 1.651 9.755