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(10723.78
+ ,3080.58
+ ,10539.51
+ ,10673.38
+ ,10411.75
+ ,10001.60
+ ,10682.06
+ ,3106.22
+ ,10723.78
+ ,10539.51
+ ,10673.38
+ ,10411.75
+ ,10283.19
+ ,3119.31
+ ,10682.06
+ ,10723.78
+ ,10539.51
+ ,10673.38
+ ,10377.18
+ ,3061.26
+ ,10283.19
+ ,10682.06
+ ,10723.78
+ ,10539.51
+ ,10486.64
+ ,3097.31
+ ,10377.18
+ ,10283.19
+ ,10682.06
+ ,10723.78
+ ,10545.38
+ ,3161.69
+ ,10486.64
+ ,10377.18
+ ,10283.19
+ ,10682.06
+ ,10554.27
+ ,3257.16
+ ,10545.38
+ ,10486.64
+ ,10377.18
+ ,10283.19
+ ,10532.54
+ ,3277.01
+ ,10554.27
+ ,10545.38
+ ,10486.64
+ ,10377.18
+ ,10324.31
+ ,3295.32
+ ,10532.54
+ ,10554.27
+ ,10545.38
+ ,10486.64
+ ,10695.25
+ ,3363.99
+ ,10324.31
+ ,10532.54
+ ,10554.27
+ ,10545.38
+ ,10827.81
+ ,3494.17
+ ,10695.25
+ ,10324.31
+ ,10532.54
+ ,10554.27
+ ,10872.48
+ ,3667.03
+ ,10827.81
+ ,10695.25
+ ,10324.31
+ ,10532.54
+ ,10971.19
+ ,3813.06
+ ,10872.48
+ ,10827.81
+ ,10695.25
+ ,10324.31
+ ,11145.65
+ ,3917.96
+ ,10971.19
+ ,10872.48
+ ,10827.81
+ ,10695.25
+ ,11234.68
+ ,3895.51
+ ,11145.65
+ ,10971.19
+ ,10872.48
+ ,10827.81
+ ,11333.88
+ ,3801.06
+ ,11234.68
+ ,11145.65
+ ,10971.19
+ ,10872.48
+ ,10997.97
+ ,3570.12
+ ,11333.88
+ ,11234.68
+ ,11145.65
+ ,10971.19
+ ,11036.89
+ ,3701.61
+ ,10997.97
+ ,11333.88
+ ,11234.68
+ ,11145.65
+ ,11257.35
+ ,3862.27
+ ,11036.89
+ ,10997.97
+ ,11333.88
+ ,11234.68
+ ,11533.59
+ ,3970.10
+ ,11257.35
+ ,11036.89
+ ,10997.97
+ ,11333.88
+ ,11963.12
+ ,4138.52
+ ,11533.59
+ ,11257.35
+ ,11036.89
+ ,10997.97
+ ,12185.15
+ ,4199.75
+ ,11963.12
+ ,11533.59
+ ,11257.35
+ ,11036.89
+ ,12377.62
+ ,4290.89
+ ,12185.15
+ ,11963.12
+ ,11533.59
+ ,11257.35
+ ,12512.89
+ ,4443.91
+ ,12377.62
+ ,12185.15
+ ,11963.12
+ ,11533.59
+ ,12631.48
+ ,4502.64
+ ,12512.89
+ ,12377.62
+ ,12185.15
+ ,11963.12
+ ,12268.53
+ ,4356.98
+ ,12631.48
+ ,12512.89
+ ,12377.62
+ ,12185.15
+ ,12754.80
+ ,4591.27
+ ,12268.53
+ ,12631.48
+ ,12512.89
+ ,12377.62
+ ,13407.75
+ ,4696.96
+ ,12754.80
+ ,12268.53
+ ,12631.48
+ ,12512.89
+ ,13480.21
+ ,4621.40
+ ,13407.75
+ ,12754.80
+ ,12268.53
+ ,12631.48
+ ,13673.28
+ ,4562.84
+ ,13480.21
+ ,13407.75
+ ,12754.80
+ ,12268.53
+ ,13239.71
+ ,4202.52
+ ,13673.28
+ ,13480.21
+ ,13407.75
+ ,12754.80
+ ,13557.69
+ ,4296.49
+ ,13239.71
+ ,13673.28
+ ,13480.21
+ ,13407.75
+ ,13901.28
+ ,4435.23
+ ,13557.69
+ ,13239.71
+ ,13673.28
+ ,13480.21
+ ,13200.58
+ ,4105.18
+ ,13901.28
+ ,13557.69
+ ,13239.71
+ ,13673.28
+ ,13406.97
+ ,4116.68
+ ,13200.58
+ ,13901.28
+ ,13557.69
+ ,13239.71
+ ,12538.12
+ ,3844.49
+ ,13406.97
+ ,13200.58
+ ,13901.28
+ ,13557.69
+ ,12419.57
+ ,3720.98
+ ,12538.12
+ ,13406.97
+ ,13200.58
+ ,13901.28
+ ,12193.88
+ ,3674.40
+ ,12419.57
+ ,12538.12
+ ,13406.97
+ ,13200.58
+ ,12656.63
+ ,3857.62
+ ,12193.88
+ ,12419.57
+ ,12538.12
+ ,13406.97
+ ,12812.48
+ ,3801.06
+ ,12656.63
+ ,12193.88
+ ,12419.57
+ ,12538.12
+ ,12056.67
+ ,3504.37
+ ,12812.48
+ ,12656.63
+ ,12193.88
+ ,12419.57
+ ,11322.38
+ ,3032.60
+ ,12056.67
+ ,12812.48
+ ,12656.63
+ ,12193.88
+ ,11530.75
+ ,3047.03
+ ,11322.38
+ ,12056.67
+ ,12812.48
+ ,12656.63
+ ,11114.08
+ ,2962.34
+ ,11530.75
+ ,11322.38
+ ,12056.67
+ ,12812.48
+ ,9181.73
+ ,2197.82
+ ,11114.08
+ ,11530.75
+ ,11322.38
+ ,12056.67
+ ,8614.55
+ ,2014.45
+ ,9181.73
+ ,11114.08
+ ,11530.75
+ ,11322.38
+ ,8595.56
+ ,1862.83
+ ,8614.55
+ ,9181.73
+ ,11114.08
+ ,11530.75
+ ,8396.20
+ ,1905.41
+ ,8595.56
+ ,8614.55
+ ,9181.73
+ ,11114.08
+ ,7690.50
+ ,1810.99
+ ,8396.20
+ ,8595.56
+ ,8614.55
+ ,9181.73
+ ,7235.47
+ ,1670.07
+ ,7690.50
+ ,8396.20
+ ,8595.56
+ ,8614.55
+ ,7992.12
+ ,1864.44
+ ,7235.47
+ ,7690.50
+ ,8396.20
+ ,8595.56
+ ,8398.37
+ ,2052.02
+ ,7992.12
+ ,7235.47
+ ,7690.50
+ ,8396.20
+ ,8593.01
+ ,2029.60
+ ,8398.37
+ ,7992.12
+ ,7235.47
+ ,7690.50
+ ,8679.75
+ ,2070.83
+ ,8593.01
+ ,8398.37
+ ,7992.12
+ ,7235.47
+ ,9374.63
+ ,2293.41
+ ,8679.75
+ ,8593.01
+ ,8398.37
+ ,7992.12
+ ,9634.97
+ ,2443.27
+ ,9374.63
+ ,8679.75
+ ,8593.01
+ ,8398.37)
+ ,dim=c(6
+ ,56)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Yt-1'
+ ,'Yt-2'
+ ,'Yt-3'
+ ,'Yt-4
')
+ ,1:56))
> y <- array(NA,dim=c(6,56),dimnames=list(c('Y','X','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 = '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
X Y Yt-1 Yt-2 Yt-3 Yt-4\r\r M1 M2 M3 M4 M5 M6 M7 M8
1 3080.58 10723.78 10539.51 10673.38 10411.75 10001.60 1 0 0 0 0 0 0 0
2 3106.22 10682.06 10723.78 10539.51 10673.38 10411.75 0 1 0 0 0 0 0 0
3 3119.31 10283.19 10682.06 10723.78 10539.51 10673.38 0 0 1 0 0 0 0 0
4 3061.26 10377.18 10283.19 10682.06 10723.78 10539.51 0 0 0 1 0 0 0 0
5 3097.31 10486.64 10377.18 10283.19 10682.06 10723.78 0 0 0 0 1 0 0 0
6 3161.69 10545.38 10486.64 10377.18 10283.19 10682.06 0 0 0 0 0 1 0 0
7 3257.16 10554.27 10545.38 10486.64 10377.18 10283.19 0 0 0 0 0 0 1 0
8 3277.01 10532.54 10554.27 10545.38 10486.64 10377.18 0 0 0 0 0 0 0 1
9 3295.32 10324.31 10532.54 10554.27 10545.38 10486.64 0 0 0 0 0 0 0 0
10 3363.99 10695.25 10324.31 10532.54 10554.27 10545.38 0 0 0 0 0 0 0 0
11 3494.17 10827.81 10695.25 10324.31 10532.54 10554.27 0 0 0 0 0 0 0 0
12 3667.03 10872.48 10827.81 10695.25 10324.31 10532.54 0 0 0 0 0 0 0 0
13 3813.06 10971.19 10872.48 10827.81 10695.25 10324.31 1 0 0 0 0 0 0 0
14 3917.96 11145.65 10971.19 10872.48 10827.81 10695.25 0 1 0 0 0 0 0 0
15 3895.51 11234.68 11145.65 10971.19 10872.48 10827.81 0 0 1 0 0 0 0 0
16 3801.06 11333.88 11234.68 11145.65 10971.19 10872.48 0 0 0 1 0 0 0 0
17 3570.12 10997.97 11333.88 11234.68 11145.65 10971.19 0 0 0 0 1 0 0 0
18 3701.61 11036.89 10997.97 11333.88 11234.68 11145.65 0 0 0 0 0 1 0 0
19 3862.27 11257.35 11036.89 10997.97 11333.88 11234.68 0 0 0 0 0 0 1 0
20 3970.10 11533.59 11257.35 11036.89 10997.97 11333.88 0 0 0 0 0 0 0 1
21 4138.52 11963.12 11533.59 11257.35 11036.89 10997.97 0 0 0 0 0 0 0 0
22 4199.75 12185.15 11963.12 11533.59 11257.35 11036.89 0 0 0 0 0 0 0 0
23 4290.89 12377.62 12185.15 11963.12 11533.59 11257.35 0 0 0 0 0 0 0 0
24 4443.91 12512.89 12377.62 12185.15 11963.12 11533.59 0 0 0 0 0 0 0 0
25 4502.64 12631.48 12512.89 12377.62 12185.15 11963.12 1 0 0 0 0 0 0 0
26 4356.98 12268.53 12631.48 12512.89 12377.62 12185.15 0 1 0 0 0 0 0 0
27 4591.27 12754.80 12268.53 12631.48 12512.89 12377.62 0 0 1 0 0 0 0 0
28 4696.96 13407.75 12754.80 12268.53 12631.48 12512.89 0 0 0 1 0 0 0 0
29 4621.40 13480.21 13407.75 12754.80 12268.53 12631.48 0 0 0 0 1 0 0 0
30 4562.84 13673.28 13480.21 13407.75 12754.80 12268.53 0 0 0 0 0 1 0 0
31 4202.52 13239.71 13673.28 13480.21 13407.75 12754.80 0 0 0 0 0 0 1 0
32 4296.49 13557.69 13239.71 13673.28 13480.21 13407.75 0 0 0 0 0 0 0 1
33 4435.23 13901.28 13557.69 13239.71 13673.28 13480.21 0 0 0 0 0 0 0 0
34 4105.18 13200.58 13901.28 13557.69 13239.71 13673.28 0 0 0 0 0 0 0 0
35 4116.68 13406.97 13200.58 13901.28 13557.69 13239.71 0 0 0 0 0 0 0 0
36 3844.49 12538.12 13406.97 13200.58 13901.28 13557.69 0 0 0 0 0 0 0 0
37 3720.98 12419.57 12538.12 13406.97 13200.58 13901.28 1 0 0 0 0 0 0 0
38 3674.40 12193.88 12419.57 12538.12 13406.97 13200.58 0 1 0 0 0 0 0 0
39 3857.62 12656.63 12193.88 12419.57 12538.12 13406.97 0 0 1 0 0 0 0 0
40 3801.06 12812.48 12656.63 12193.88 12419.57 12538.12 0 0 0 1 0 0 0 0
41 3504.37 12056.67 12812.48 12656.63 12193.88 12419.57 0 0 0 0 1 0 0 0
42 3032.60 11322.38 12056.67 12812.48 12656.63 12193.88 0 0 0 0 0 1 0 0
43 3047.03 11530.75 11322.38 12056.67 12812.48 12656.63 0 0 0 0 0 0 1 0
44 2962.34 11114.08 11530.75 11322.38 12056.67 12812.48 0 0 0 0 0 0 0 1
45 2197.82 9181.73 11114.08 11530.75 11322.38 12056.67 0 0 0 0 0 0 0 0
46 2014.45 8614.55 9181.73 11114.08 11530.75 11322.38 0 0 0 0 0 0 0 0
47 1862.83 8595.56 8614.55 9181.73 11114.08 11530.75 0 0 0 0 0 0 0 0
48 1905.41 8396.20 8595.56 8614.55 9181.73 11114.08 0 0 0 0 0 0 0 0
49 1810.99 7690.50 8396.20 8595.56 8614.55 9181.73 1 0 0 0 0 0 0 0
50 1670.07 7235.47 7690.50 8396.20 8595.56 8614.55 0 1 0 0 0 0 0 0
51 1864.44 7992.12 7235.47 7690.50 8396.20 8595.56 0 0 1 0 0 0 0 0
52 2052.02 8398.37 7992.12 7235.47 7690.50 8396.20 0 0 0 1 0 0 0 0
53 2029.60 8593.01 8398.37 7992.12 7235.47 7690.50 0 0 0 0 1 0 0 0
54 2070.83 8679.75 8593.01 8398.37 7992.12 7235.47 0 0 0 0 0 1 0 0
55 2293.41 9374.63 8679.75 8593.01 8398.37 7992.12 0 0 0 0 0 0 1 0
56 2443.27 9634.97 9374.63 8679.75 8593.01 8398.37 0 0 0 0 0 0 0 1
M9 M10 M11 t
1 0 0 0 1
2 0 0 0 2
3 0 0 0 3
4 0 0 0 4
5 0 0 0 5
6 0 0 0 6
7 0 0 0 7
8 0 0 0 8
9 1 0 0 9
10 0 1 0 10
11 0 0 1 11
12 0 0 0 12
13 0 0 0 13
14 0 0 0 14
15 0 0 0 15
16 0 0 0 16
17 0 0 0 17
18 0 0 0 18
19 0 0 0 19
20 0 0 0 20
21 1 0 0 21
22 0 1 0 22
23 0 0 1 23
24 0 0 0 24
25 0 0 0 25
26 0 0 0 26
27 0 0 0 27
28 0 0 0 28
29 0 0 0 29
30 0 0 0 30
31 0 0 0 31
32 0 0 0 32
33 1 0 0 33
34 0 1 0 34
35 0 0 1 35
36 0 0 0 36
37 0 0 0 37
38 0 0 0 38
39 0 0 0 39
40 0 0 0 40
41 0 0 0 41
42 0 0 0 42
43 0 0 0 43
44 0 0 0 44
45 1 0 0 45
46 0 1 0 46
47 0 0 1 47
48 0 0 0 48
49 0 0 0 49
50 0 0 0 50
51 0 0 0 51
52 0 0 0 52
53 0 0 0 53
54 0 0 0 54
55 0 0 0 55
56 0 0 0 56
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Y `Yt-1` `Yt-2` `Yt-3` `Yt-4\r\r`
-1.000e+03 5.645e-01 -1.231e-02 2.908e-02 -8.278e-02 -6.526e-02
M1 M2 M3 M4 M5 M6
-8.704e+01 -1.315e+00 -3.587e+01 -1.805e+02 -2.338e+02 -2.417e+02
M7 M8 M9 M10 M11 t
-2.401e+02 -2.103e+02 -1.036e+02 -1.076e+02 -1.393e+02 -9.139e+00
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-543.26 -122.13 -20.55 153.48 408.28
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.000e+03 2.875e+02 -3.478 0.001281 **
Y 5.645e-01 8.507e-02 6.636 7.68e-08 ***
`Yt-1` -1.231e-02 1.345e-01 -0.092 0.927566
`Yt-2` 2.908e-02 1.364e-01 0.213 0.832322
`Yt-3` -8.278e-02 1.357e-01 -0.610 0.545420
`Yt-4\r\r` -6.526e-02 8.822e-02 -0.740 0.464029
M1 -8.704e+01 1.661e+02 -0.524 0.603247
M2 -1.315e+00 1.653e+02 -0.008 0.993695
M3 -3.587e+01 1.678e+02 -0.214 0.831878
M4 -1.805e+02 1.639e+02 -1.101 0.277700
M5 -2.338e+02 1.629e+02 -1.435 0.159446
M6 -2.417e+02 1.722e+02 -1.403 0.168632
M7 -2.401e+02 1.696e+02 -1.416 0.164991
M8 -2.103e+02 1.611e+02 -1.306 0.199548
M9 -1.036e+02 1.688e+02 -0.614 0.543043
M10 -1.076e+02 1.750e+02 -0.615 0.542329
M11 -1.393e+02 1.746e+02 -0.798 0.429902
t -9.139e+00 2.149e+00 -4.253 0.000132 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 236 on 38 degrees of freedom
Multiple R-squared: 0.949, Adjusted R-squared: 0.9262
F-statistic: 41.59 on 17 and 38 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,] 0.1183703 0.2367407 0.8816297
[2,] 0.4620088 0.9240176 0.5379912
[3,] 0.5563268 0.8873464 0.4436732
[4,] 0.5261045 0.9477910 0.4738955
[5,] 0.4147464 0.8294927 0.5852536
[6,] 0.3185889 0.6371777 0.6814111
[7,] 0.2937545 0.5875091 0.7062455
[8,] 0.3025049 0.6050099 0.6974951
[9,] 0.4428058 0.8856116 0.5571942
[10,] 0.6531269 0.6937461 0.3468731
[11,] 0.8275161 0.3449678 0.1724839
[12,] 0.8295171 0.3409658 0.1704829
[13,] 0.8768439 0.2463122 0.1231561
[14,] 0.8439809 0.3120382 0.1560191
[15,] 0.8093312 0.3813376 0.1906688
> postscript(file="/var/www/html/rcomp/tmp/1bauz1259621705.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/20e231259621705.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/346mt1259621705.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/44u8u1259621705.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5hhrk1259621705.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
-543.257514 -516.071809 -233.993762 -188.522572 -130.522065 -119.338518
7 8 9 10 11 12
-42.047701 -17.047650 32.742973 -92.234865 13.376572 3.051223
13 14 15 16 17 18
203.350293 168.268573 150.879738 161.296189 201.916956 340.260496
19 20 21 22 23 24
408.281680 319.703300 126.382787 93.432778 144.275087 140.268043
25 26 27 28 29 30
270.707804 281.300329 300.615467 226.640901 144.180800 -7.811041
31 32 33 34 35 36
-29.770955 -98.366330 -213.909160 -163.585332 -248.322619 -88.071833
37 38 39 40 41 42
-100.753511 -101.346049 -193.448145 -238.481659 -84.038130 -114.448628
43 44 45 46 47 48
-154.061234 -52.718057 54.783400 162.387418 90.670960 -55.247433
49 50 51 52 53 54
169.952928 167.848956 -24.053299 39.067141 -131.537560 -98.662310
55 56
-182.401788 -151.571262
> postscript(file="/var/www/html/rcomp/tmp/65b4w1259621705.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 -543.257514 NA
1 -516.071809 -543.257514
2 -233.993762 -516.071809
3 -188.522572 -233.993762
4 -130.522065 -188.522572
5 -119.338518 -130.522065
6 -42.047701 -119.338518
7 -17.047650 -42.047701
8 32.742973 -17.047650
9 -92.234865 32.742973
10 13.376572 -92.234865
11 3.051223 13.376572
12 203.350293 3.051223
13 168.268573 203.350293
14 150.879738 168.268573
15 161.296189 150.879738
16 201.916956 161.296189
17 340.260496 201.916956
18 408.281680 340.260496
19 319.703300 408.281680
20 126.382787 319.703300
21 93.432778 126.382787
22 144.275087 93.432778
23 140.268043 144.275087
24 270.707804 140.268043
25 281.300329 270.707804
26 300.615467 281.300329
27 226.640901 300.615467
28 144.180800 226.640901
29 -7.811041 144.180800
30 -29.770955 -7.811041
31 -98.366330 -29.770955
32 -213.909160 -98.366330
33 -163.585332 -213.909160
34 -248.322619 -163.585332
35 -88.071833 -248.322619
36 -100.753511 -88.071833
37 -101.346049 -100.753511
38 -193.448145 -101.346049
39 -238.481659 -193.448145
40 -84.038130 -238.481659
41 -114.448628 -84.038130
42 -154.061234 -114.448628
43 -52.718057 -154.061234
44 54.783400 -52.718057
45 162.387418 54.783400
46 90.670960 162.387418
47 -55.247433 90.670960
48 169.952928 -55.247433
49 167.848956 169.952928
50 -24.053299 167.848956
51 39.067141 -24.053299
52 -131.537560 39.067141
53 -98.662310 -131.537560
54 -182.401788 -98.662310
55 -151.571262 -182.401788
56 NA -151.571262
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -516.071809 -543.257514
[2,] -233.993762 -516.071809
[3,] -188.522572 -233.993762
[4,] -130.522065 -188.522572
[5,] -119.338518 -130.522065
[6,] -42.047701 -119.338518
[7,] -17.047650 -42.047701
[8,] 32.742973 -17.047650
[9,] -92.234865 32.742973
[10,] 13.376572 -92.234865
[11,] 3.051223 13.376572
[12,] 203.350293 3.051223
[13,] 168.268573 203.350293
[14,] 150.879738 168.268573
[15,] 161.296189 150.879738
[16,] 201.916956 161.296189
[17,] 340.260496 201.916956
[18,] 408.281680 340.260496
[19,] 319.703300 408.281680
[20,] 126.382787 319.703300
[21,] 93.432778 126.382787
[22,] 144.275087 93.432778
[23,] 140.268043 144.275087
[24,] 270.707804 140.268043
[25,] 281.300329 270.707804
[26,] 300.615467 281.300329
[27,] 226.640901 300.615467
[28,] 144.180800 226.640901
[29,] -7.811041 144.180800
[30,] -29.770955 -7.811041
[31,] -98.366330 -29.770955
[32,] -213.909160 -98.366330
[33,] -163.585332 -213.909160
[34,] -248.322619 -163.585332
[35,] -88.071833 -248.322619
[36,] -100.753511 -88.071833
[37,] -101.346049 -100.753511
[38,] -193.448145 -101.346049
[39,] -238.481659 -193.448145
[40,] -84.038130 -238.481659
[41,] -114.448628 -84.038130
[42,] -154.061234 -114.448628
[43,] -52.718057 -154.061234
[44,] 54.783400 -52.718057
[45,] 162.387418 54.783400
[46,] 90.670960 162.387418
[47,] -55.247433 90.670960
[48,] 169.952928 -55.247433
[49,] 167.848956 169.952928
[50,] -24.053299 167.848956
[51,] 39.067141 -24.053299
[52,] -131.537560 39.067141
[53,] -98.662310 -131.537560
[54,] -182.401788 -98.662310
[55,] -151.571262 -182.401788
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -516.071809 -543.257514
2 -233.993762 -516.071809
3 -188.522572 -233.993762
4 -130.522065 -188.522572
5 -119.338518 -130.522065
6 -42.047701 -119.338518
7 -17.047650 -42.047701
8 32.742973 -17.047650
9 -92.234865 32.742973
10 13.376572 -92.234865
11 3.051223 13.376572
12 203.350293 3.051223
13 168.268573 203.350293
14 150.879738 168.268573
15 161.296189 150.879738
16 201.916956 161.296189
17 340.260496 201.916956
18 408.281680 340.260496
19 319.703300 408.281680
20 126.382787 319.703300
21 93.432778 126.382787
22 144.275087 93.432778
23 140.268043 144.275087
24 270.707804 140.268043
25 281.300329 270.707804
26 300.615467 281.300329
27 226.640901 300.615467
28 144.180800 226.640901
29 -7.811041 144.180800
30 -29.770955 -7.811041
31 -98.366330 -29.770955
32 -213.909160 -98.366330
33 -163.585332 -213.909160
34 -248.322619 -163.585332
35 -88.071833 -248.322619
36 -100.753511 -88.071833
37 -101.346049 -100.753511
38 -193.448145 -101.346049
39 -238.481659 -193.448145
40 -84.038130 -238.481659
41 -114.448628 -84.038130
42 -154.061234 -114.448628
43 -52.718057 -154.061234
44 54.783400 -52.718057
45 162.387418 54.783400
46 90.670960 162.387418
47 -55.247433 90.670960
48 169.952928 -55.247433
49 167.848956 169.952928
50 -24.053299 167.848956
51 39.067141 -24.053299
52 -131.537560 39.067141
53 -98.662310 -131.537560
54 -182.401788 -98.662310
55 -151.571262 -182.401788
> 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/7wifz1259621705.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/85vq51259621705.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9eftc1259621705.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10e4ok1259621705.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11adnn1259621705.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/12f8qk1259621705.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/13smwx1259621705.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/14nso01259621705.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/15dtsf1259621705.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/16pjqn1259621705.tab")
+ }
>
> system("convert tmp/1bauz1259621705.ps tmp/1bauz1259621705.png")
> system("convert tmp/20e231259621705.ps tmp/20e231259621705.png")
> system("convert tmp/346mt1259621705.ps tmp/346mt1259621705.png")
> system("convert tmp/44u8u1259621705.ps tmp/44u8u1259621705.png")
> system("convert tmp/5hhrk1259621705.ps tmp/5hhrk1259621705.png")
> system("convert tmp/65b4w1259621705.ps tmp/65b4w1259621705.png")
> system("convert tmp/7wifz1259621705.ps tmp/7wifz1259621705.png")
> system("convert tmp/85vq51259621705.ps tmp/85vq51259621705.png")
> system("convert tmp/9eftc1259621705.ps tmp/9eftc1259621705.png")
> system("convert tmp/10e4ok1259621705.ps tmp/10e4ok1259621705.png")
>
>
> proc.time()
user system elapsed
2.368 1.636 5.553