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(6802.96
+ ,0
+ ,6349.71
+ ,6303.79
+ ,6158.17
+ ,6091.43
+ ,7132.68
+ ,0
+ ,6802.96
+ ,6349.71
+ ,6303.79
+ ,6158.17
+ ,7073.29
+ ,0
+ ,7132.68
+ ,6802.96
+ ,6349.71
+ ,6303.79
+ ,7264.5
+ ,0
+ ,7073.29
+ ,7132.68
+ ,6802.96
+ ,6349.71
+ ,7105.33
+ ,0
+ ,7264.5
+ ,7073.29
+ ,7132.68
+ ,6802.96
+ ,7218.71
+ ,0
+ ,7105.33
+ ,7264.5
+ ,7073.29
+ ,7132.68
+ ,7225.72
+ ,0
+ ,7218.71
+ ,7105.33
+ ,7264.5
+ ,7073.29
+ ,7354.25
+ ,0
+ ,7225.72
+ ,7218.71
+ ,7105.33
+ ,7264.5
+ ,7745.46
+ ,0
+ ,7354.25
+ ,7225.72
+ ,7218.71
+ ,7105.33
+ ,8070.26
+ ,0
+ ,7745.46
+ ,7354.25
+ ,7225.72
+ ,7218.71
+ ,8366.33
+ ,0
+ ,8070.26
+ ,7745.46
+ ,7354.25
+ ,7225.72
+ ,8667.51
+ ,0
+ ,8366.33
+ ,8070.26
+ ,7745.46
+ ,7354.25
+ ,8854.34
+ ,0
+ ,8667.51
+ ,8366.33
+ ,8070.26
+ ,7745.46
+ ,9218.1
+ ,0
+ ,8854.34
+ ,8667.51
+ ,8366.33
+ ,8070.26
+ ,9332.9
+ ,0
+ ,9218.1
+ ,8854.34
+ ,8667.51
+ ,8366.33
+ ,9358.31
+ ,0
+ ,9332.9
+ ,9218.1
+ ,8854.34
+ ,8667.51
+ ,9248.66
+ ,0
+ ,9358.31
+ ,9332.9
+ ,9218.1
+ ,8854.34
+ ,9401.2
+ ,0
+ ,9248.66
+ ,9358.31
+ ,9332.9
+ ,9218.1
+ ,9652.04
+ ,0
+ ,9401.2
+ ,9248.66
+ ,9358.31
+ ,9332.9
+ ,9957.38
+ ,0
+ ,9652.04
+ ,9401.2
+ ,9248.66
+ ,9358.31
+ ,10110.63
+ ,0
+ ,9957.38
+ ,9652.04
+ ,9401.2
+ ,9248.66
+ ,10169.26
+ ,0
+ ,10110.63
+ ,9957.38
+ ,9652.04
+ ,9401.2
+ ,10343.78
+ ,0
+ ,10169.26
+ ,10110.63
+ ,9957.38
+ ,9652.04
+ ,10750.21
+ ,0
+ ,10343.78
+ ,10169.26
+ ,10110.63
+ ,9957.38
+ ,11337.5
+ ,0
+ ,10750.21
+ ,10343.78
+ ,10169.26
+ ,10110.63
+ ,11786.96
+ ,0
+ ,11337.5
+ ,10750.21
+ ,10343.78
+ ,10169.26
+ ,12083.04
+ ,0
+ ,11786.96
+ ,11337.5
+ ,10750.21
+ ,10343.78
+ ,12007.74
+ ,0
+ ,12083.04
+ ,11786.96
+ ,11337.5
+ ,10750.21
+ ,11745.93
+ ,0
+ ,12007.74
+ ,12083.04
+ ,11786.96
+ ,11337.5
+ ,11051.51
+ ,0
+ ,11745.93
+ ,12007.74
+ ,12083.04
+ ,11786.96
+ ,11445.9
+ ,0
+ ,11051.51
+ ,11745.93
+ ,12007.74
+ ,12083.04
+ ,11924.88
+ ,0
+ ,11445.9
+ ,11051.51
+ ,11745.93
+ ,12007.74
+ ,12247.63
+ ,0
+ ,11924.88
+ ,11445.9
+ ,11051.51
+ ,11745.93
+ ,12690.91
+ ,0
+ ,12247.63
+ ,11924.88
+ ,11445.9
+ ,11051.51
+ ,12910.7
+ ,0
+ ,12690.91
+ ,12247.63
+ ,11924.88
+ ,11445.9
+ ,13202.12
+ ,0
+ ,12910.7
+ ,12690.91
+ ,12247.63
+ ,11924.88
+ ,13654.67
+ ,0
+ ,13202.12
+ ,12910.7
+ ,12690.91
+ ,12247.63
+ ,13862.82
+ ,0
+ ,13654.67
+ ,13202.12
+ ,12910.7
+ ,12690.91
+ ,13523.93
+ ,0
+ ,13862.82
+ ,13654.67
+ ,13202.12
+ ,12910.7
+ ,14211.17
+ ,0
+ ,13523.93
+ ,13862.82
+ ,13654.67
+ ,13202.12
+ ,14510.35
+ ,0
+ ,14211.17
+ ,13523.93
+ ,13862.82
+ ,13654.67
+ ,14289.23
+ ,0
+ ,14510.35
+ ,14211.17
+ ,13523.93
+ ,13862.82
+ ,14111.82
+ ,0
+ ,14289.23
+ ,14510.35
+ ,14211.17
+ ,13523.93
+ ,13086.59
+ ,0
+ ,14111.82
+ ,14289.23
+ ,14510.35
+ ,14211.17
+ ,13351.54
+ ,0
+ ,13086.59
+ ,14111.82
+ ,14289.23
+ ,14510.35
+ ,13747.69
+ ,0
+ ,13351.54
+ ,13086.59
+ ,14111.82
+ ,14289.23
+ ,12855.61
+ ,0
+ ,13747.69
+ ,13351.54
+ ,13086.59
+ ,14111.82
+ ,12926.93
+ ,0
+ ,12855.61
+ ,13747.69
+ ,13351.54
+ ,13086.59
+ ,12121.95
+ ,1
+ ,12926.93
+ ,12855.61
+ ,13747.69
+ ,13351.54
+ ,11731.65
+ ,1
+ ,12121.95
+ ,12926.93
+ ,12855.61
+ ,13747.69
+ ,11639.51
+ ,1
+ ,11731.65
+ ,12121.95
+ ,12926.93
+ ,12855.61
+ ,12163.78
+ ,1
+ ,11639.51
+ ,11731.65
+ ,12121.95
+ ,12926.93
+ ,12029.53
+ ,1
+ ,12163.78
+ ,11639.51
+ ,11731.65
+ ,12121.95
+ ,11234.18
+ ,1
+ ,12029.53
+ ,12163.78
+ ,11639.51
+ ,11731.65
+ ,9852.13
+ ,1
+ ,11234.18
+ ,12029.53
+ ,12163.78
+ ,11639.51
+ ,9709.04
+ ,1
+ ,9852.13
+ ,11234.18
+ ,12029.53
+ ,12163.78
+ ,9332.75
+ ,1
+ ,9709.04
+ ,9852.13
+ ,11234.18
+ ,12029.53
+ ,7108.6
+ ,1
+ ,9332.75
+ ,9709.04
+ ,9852.13
+ ,11234.18
+ ,6691.49
+ ,1
+ ,7108.6
+ ,9332.75
+ ,9709.04
+ ,9852.13
+ ,6143.05
+ ,1
+ ,6691.49
+ ,7108.6
+ ,9332.75
+ ,9709.04)
+ ,dim=c(6
+ ,60)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:60))
> y <- array(NA,dim=c(6,60),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:60))
> 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
Y X Y1 Y2 Y3 Y4 M1 M2 M3 M4 M5 M6 M7 M8 M9
1 6802.96 0 6349.71 6303.79 6158.17 6091.43 1 0 0 0 0 0 0 0 0
2 7132.68 0 6802.96 6349.71 6303.79 6158.17 0 1 0 0 0 0 0 0 0
3 7073.29 0 7132.68 6802.96 6349.71 6303.79 0 0 1 0 0 0 0 0 0
4 7264.50 0 7073.29 7132.68 6802.96 6349.71 0 0 0 1 0 0 0 0 0
5 7105.33 0 7264.50 7073.29 7132.68 6802.96 0 0 0 0 1 0 0 0 0
6 7218.71 0 7105.33 7264.50 7073.29 7132.68 0 0 0 0 0 1 0 0 0
7 7225.72 0 7218.71 7105.33 7264.50 7073.29 0 0 0 0 0 0 1 0 0
8 7354.25 0 7225.72 7218.71 7105.33 7264.50 0 0 0 0 0 0 0 1 0
9 7745.46 0 7354.25 7225.72 7218.71 7105.33 0 0 0 0 0 0 0 0 1
10 8070.26 0 7745.46 7354.25 7225.72 7218.71 0 0 0 0 0 0 0 0 0
11 8366.33 0 8070.26 7745.46 7354.25 7225.72 0 0 0 0 0 0 0 0 0
12 8667.51 0 8366.33 8070.26 7745.46 7354.25 0 0 0 0 0 0 0 0 0
13 8854.34 0 8667.51 8366.33 8070.26 7745.46 1 0 0 0 0 0 0 0 0
14 9218.10 0 8854.34 8667.51 8366.33 8070.26 0 1 0 0 0 0 0 0 0
15 9332.90 0 9218.10 8854.34 8667.51 8366.33 0 0 1 0 0 0 0 0 0
16 9358.31 0 9332.90 9218.10 8854.34 8667.51 0 0 0 1 0 0 0 0 0
17 9248.66 0 9358.31 9332.90 9218.10 8854.34 0 0 0 0 1 0 0 0 0
18 9401.20 0 9248.66 9358.31 9332.90 9218.10 0 0 0 0 0 1 0 0 0
19 9652.04 0 9401.20 9248.66 9358.31 9332.90 0 0 0 0 0 0 1 0 0
20 9957.38 0 9652.04 9401.20 9248.66 9358.31 0 0 0 0 0 0 0 1 0
21 10110.63 0 9957.38 9652.04 9401.20 9248.66 0 0 0 0 0 0 0 0 1
22 10169.26 0 10110.63 9957.38 9652.04 9401.20 0 0 0 0 0 0 0 0 0
23 10343.78 0 10169.26 10110.63 9957.38 9652.04 0 0 0 0 0 0 0 0 0
24 10750.21 0 10343.78 10169.26 10110.63 9957.38 0 0 0 0 0 0 0 0 0
25 11337.50 0 10750.21 10343.78 10169.26 10110.63 1 0 0 0 0 0 0 0 0
26 11786.96 0 11337.50 10750.21 10343.78 10169.26 0 1 0 0 0 0 0 0 0
27 12083.04 0 11786.96 11337.50 10750.21 10343.78 0 0 1 0 0 0 0 0 0
28 12007.74 0 12083.04 11786.96 11337.50 10750.21 0 0 0 1 0 0 0 0 0
29 11745.93 0 12007.74 12083.04 11786.96 11337.50 0 0 0 0 1 0 0 0 0
30 11051.51 0 11745.93 12007.74 12083.04 11786.96 0 0 0 0 0 1 0 0 0
31 11445.90 0 11051.51 11745.93 12007.74 12083.04 0 0 0 0 0 0 1 0 0
32 11924.88 0 11445.90 11051.51 11745.93 12007.74 0 0 0 0 0 0 0 1 0
33 12247.63 0 11924.88 11445.90 11051.51 11745.93 0 0 0 0 0 0 0 0 1
34 12690.91 0 12247.63 11924.88 11445.90 11051.51 0 0 0 0 0 0 0 0 0
35 12910.70 0 12690.91 12247.63 11924.88 11445.90 0 0 0 0 0 0 0 0 0
36 13202.12 0 12910.70 12690.91 12247.63 11924.88 0 0 0 0 0 0 0 0 0
37 13654.67 0 13202.12 12910.70 12690.91 12247.63 1 0 0 0 0 0 0 0 0
38 13862.82 0 13654.67 13202.12 12910.70 12690.91 0 1 0 0 0 0 0 0 0
39 13523.93 0 13862.82 13654.67 13202.12 12910.70 0 0 1 0 0 0 0 0 0
40 14211.17 0 13523.93 13862.82 13654.67 13202.12 0 0 0 1 0 0 0 0 0
41 14510.35 0 14211.17 13523.93 13862.82 13654.67 0 0 0 0 1 0 0 0 0
42 14289.23 0 14510.35 14211.17 13523.93 13862.82 0 0 0 0 0 1 0 0 0
43 14111.82 0 14289.23 14510.35 14211.17 13523.93 0 0 0 0 0 0 1 0 0
44 13086.59 0 14111.82 14289.23 14510.35 14211.17 0 0 0 0 0 0 0 1 0
45 13351.54 0 13086.59 14111.82 14289.23 14510.35 0 0 0 0 0 0 0 0 1
46 13747.69 0 13351.54 13086.59 14111.82 14289.23 0 0 0 0 0 0 0 0 0
47 12855.61 0 13747.69 13351.54 13086.59 14111.82 0 0 0 0 0 0 0 0 0
48 12926.93 0 12855.61 13747.69 13351.54 13086.59 0 0 0 0 0 0 0 0 0
49 12121.95 1 12926.93 12855.61 13747.69 13351.54 1 0 0 0 0 0 0 0 0
50 11731.65 1 12121.95 12926.93 12855.61 13747.69 0 1 0 0 0 0 0 0 0
51 11639.51 1 11731.65 12121.95 12926.93 12855.61 0 0 1 0 0 0 0 0 0
52 12163.78 1 11639.51 11731.65 12121.95 12926.93 0 0 0 1 0 0 0 0 0
53 12029.53 1 12163.78 11639.51 11731.65 12121.95 0 0 0 0 1 0 0 0 0
54 11234.18 1 12029.53 12163.78 11639.51 11731.65 0 0 0 0 0 1 0 0 0
55 9852.13 1 11234.18 12029.53 12163.78 11639.51 0 0 0 0 0 0 1 0 0
56 9709.04 1 9852.13 11234.18 12029.53 12163.78 0 0 0 0 0 0 0 1 0
57 9332.75 1 9709.04 9852.13 11234.18 12029.53 0 0 0 0 0 0 0 0 1
58 7108.60 1 9332.75 9709.04 9852.13 11234.18 0 0 0 0 0 0 0 0 0
59 6691.49 1 7108.60 9332.75 9709.04 9852.13 0 0 0 0 0 0 0 0 0
60 6143.05 1 6691.49 7108.60 9332.75 9709.04 0 0 0 0 0 0 0 0 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
57 0 0 57
58 1 0 58
59 0 1 59
60 0 0 60
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
-8.26383 -293.37416 1.02470 -0.21100 0.31681 -0.04904
M1 M2 M3 M4 M5 M6
-99.37526 -2.92769 -229.80564 73.40714 -312.34395 -434.54794
M7 M8 M9 M10 M11 t
-401.50195 -270.91887 2.58703 -299.75662 -158.83668 -20.29065
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1198.13 -155.70 35.66 258.95 789.09
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -8.26383 458.15971 -0.018 0.986
X -293.37416 402.16121 -0.729 0.470
Y1 1.02470 0.15192 6.745 3.37e-08 ***
Y2 -0.21100 0.21810 -0.967 0.339
Y3 0.31681 0.25122 1.261 0.214
Y4 -0.04904 0.19642 -0.250 0.804
M1 -99.37526 319.65128 -0.311 0.757
M2 -2.92769 323.52299 -0.009 0.993
M3 -229.80564 316.48137 -0.726 0.472
M4 73.40714 316.18102 0.232 0.818
M5 -312.34395 313.75873 -0.995 0.325
M6 -434.54794 318.30452 -1.365 0.179
M7 -401.50195 308.73162 -1.300 0.201
M8 -270.91887 309.46373 -0.875 0.386
M9 2.58703 306.97533 0.008 0.993
M10 -299.75662 296.03272 -1.013 0.317
M11 -158.83668 293.55402 -0.541 0.591
t -20.29065 16.46742 -1.232 0.225
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 449.9 on 42 degrees of freedom
Multiple R-squared: 0.9749, Adjusted R-squared: 0.9647
F-statistic: 95.79 on 17 and 42 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,] 2.655529e-02 5.311058e-02 0.9734447
[2,] 9.086187e-03 1.817237e-02 0.9909138
[3,] 2.932079e-03 5.864158e-03 0.9970679
[4,] 6.587986e-04 1.317597e-03 0.9993412
[5,] 1.622364e-04 3.244727e-04 0.9998378
[6,] 3.607281e-05 7.214562e-05 0.9999639
[7,] 5.740455e-05 1.148091e-04 0.9999426
[8,] 2.447942e-05 4.895884e-05 0.9999755
[9,] 1.137247e-05 2.274494e-05 0.9999886
[10,] 6.483215e-04 1.296643e-03 0.9993517
[11,] 2.960904e-04 5.921807e-04 0.9997039
[12,] 1.116665e-04 2.233330e-04 0.9998883
[13,] 6.976818e-05 1.395364e-04 0.9999302
[14,] 2.299281e-05 4.598563e-05 0.9999770
[15,] 5.750274e-06 1.150055e-05 0.9999942
[16,] 1.302429e-06 2.604858e-06 0.9999987
[17,] 7.307996e-06 1.461599e-05 0.9999927
[18,] 6.578443e-06 1.315689e-05 0.9999934
[19,] 5.192880e-05 1.038576e-04 0.9999481
> postscript(file="/var/www/html/rcomp/tmp/1veja1258678474.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2eqim1258678474.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3taz01258678474.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/45kh21258678474.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5zqk51258678474.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 = 60
Frequency = 1
1 2 3 4 5 6
102.202315 -141.850563 -203.705114 -306.332671 -350.157653 144.148168
7 8 9 10 11 12
-74.852788 19.928938 -16.027150 260.994922 145.784236 -44.067764
13 14 15 16 17 18
-67.435136 14.402326 -37.850137 -380.664058 -192.169001 202.053184
19 20 21 22 23 24
258.273621 264.457319 -149.164654 67.503220 9.217071 77.063811
25 26 27 28 29 30
393.316874 198.168562 284.572414 -448.335395 -278.065660 -649.365085
31 32 33 34 35 36
426.972034 324.257648 193.363449 570.621640 151.248902 93.674852
37 38 39 40 41 42
289.040027 -29.097622 -320.168066 346.246141 231.996524 109.384054
43 44 45 46 47 48
-25.418214 -1086.889242 22.686144 299.013648 -747.617237 48.641162
49 50 51 52 53 54
-717.124080 -41.622703 277.150903 789.085982 588.395789 193.779679
55 56 57 58 59 60
-584.974653 478.245337 -50.857789 -1198.133431 441.367028 -175.312062
> postscript(file="/var/www/html/rcomp/tmp/6eyxb1258678474.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 102.202315 NA
1 -141.850563 102.202315
2 -203.705114 -141.850563
3 -306.332671 -203.705114
4 -350.157653 -306.332671
5 144.148168 -350.157653
6 -74.852788 144.148168
7 19.928938 -74.852788
8 -16.027150 19.928938
9 260.994922 -16.027150
10 145.784236 260.994922
11 -44.067764 145.784236
12 -67.435136 -44.067764
13 14.402326 -67.435136
14 -37.850137 14.402326
15 -380.664058 -37.850137
16 -192.169001 -380.664058
17 202.053184 -192.169001
18 258.273621 202.053184
19 264.457319 258.273621
20 -149.164654 264.457319
21 67.503220 -149.164654
22 9.217071 67.503220
23 77.063811 9.217071
24 393.316874 77.063811
25 198.168562 393.316874
26 284.572414 198.168562
27 -448.335395 284.572414
28 -278.065660 -448.335395
29 -649.365085 -278.065660
30 426.972034 -649.365085
31 324.257648 426.972034
32 193.363449 324.257648
33 570.621640 193.363449
34 151.248902 570.621640
35 93.674852 151.248902
36 289.040027 93.674852
37 -29.097622 289.040027
38 -320.168066 -29.097622
39 346.246141 -320.168066
40 231.996524 346.246141
41 109.384054 231.996524
42 -25.418214 109.384054
43 -1086.889242 -25.418214
44 22.686144 -1086.889242
45 299.013648 22.686144
46 -747.617237 299.013648
47 48.641162 -747.617237
48 -717.124080 48.641162
49 -41.622703 -717.124080
50 277.150903 -41.622703
51 789.085982 277.150903
52 588.395789 789.085982
53 193.779679 588.395789
54 -584.974653 193.779679
55 478.245337 -584.974653
56 -50.857789 478.245337
57 -1198.133431 -50.857789
58 441.367028 -1198.133431
59 -175.312062 441.367028
60 NA -175.312062
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -141.850563 102.202315
[2,] -203.705114 -141.850563
[3,] -306.332671 -203.705114
[4,] -350.157653 -306.332671
[5,] 144.148168 -350.157653
[6,] -74.852788 144.148168
[7,] 19.928938 -74.852788
[8,] -16.027150 19.928938
[9,] 260.994922 -16.027150
[10,] 145.784236 260.994922
[11,] -44.067764 145.784236
[12,] -67.435136 -44.067764
[13,] 14.402326 -67.435136
[14,] -37.850137 14.402326
[15,] -380.664058 -37.850137
[16,] -192.169001 -380.664058
[17,] 202.053184 -192.169001
[18,] 258.273621 202.053184
[19,] 264.457319 258.273621
[20,] -149.164654 264.457319
[21,] 67.503220 -149.164654
[22,] 9.217071 67.503220
[23,] 77.063811 9.217071
[24,] 393.316874 77.063811
[25,] 198.168562 393.316874
[26,] 284.572414 198.168562
[27,] -448.335395 284.572414
[28,] -278.065660 -448.335395
[29,] -649.365085 -278.065660
[30,] 426.972034 -649.365085
[31,] 324.257648 426.972034
[32,] 193.363449 324.257648
[33,] 570.621640 193.363449
[34,] 151.248902 570.621640
[35,] 93.674852 151.248902
[36,] 289.040027 93.674852
[37,] -29.097622 289.040027
[38,] -320.168066 -29.097622
[39,] 346.246141 -320.168066
[40,] 231.996524 346.246141
[41,] 109.384054 231.996524
[42,] -25.418214 109.384054
[43,] -1086.889242 -25.418214
[44,] 22.686144 -1086.889242
[45,] 299.013648 22.686144
[46,] -747.617237 299.013648
[47,] 48.641162 -747.617237
[48,] -717.124080 48.641162
[49,] -41.622703 -717.124080
[50,] 277.150903 -41.622703
[51,] 789.085982 277.150903
[52,] 588.395789 789.085982
[53,] 193.779679 588.395789
[54,] -584.974653 193.779679
[55,] 478.245337 -584.974653
[56,] -50.857789 478.245337
[57,] -1198.133431 -50.857789
[58,] 441.367028 -1198.133431
[59,] -175.312062 441.367028
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -141.850563 102.202315
2 -203.705114 -141.850563
3 -306.332671 -203.705114
4 -350.157653 -306.332671
5 144.148168 -350.157653
6 -74.852788 144.148168
7 19.928938 -74.852788
8 -16.027150 19.928938
9 260.994922 -16.027150
10 145.784236 260.994922
11 -44.067764 145.784236
12 -67.435136 -44.067764
13 14.402326 -67.435136
14 -37.850137 14.402326
15 -380.664058 -37.850137
16 -192.169001 -380.664058
17 202.053184 -192.169001
18 258.273621 202.053184
19 264.457319 258.273621
20 -149.164654 264.457319
21 67.503220 -149.164654
22 9.217071 67.503220
23 77.063811 9.217071
24 393.316874 77.063811
25 198.168562 393.316874
26 284.572414 198.168562
27 -448.335395 284.572414
28 -278.065660 -448.335395
29 -649.365085 -278.065660
30 426.972034 -649.365085
31 324.257648 426.972034
32 193.363449 324.257648
33 570.621640 193.363449
34 151.248902 570.621640
35 93.674852 151.248902
36 289.040027 93.674852
37 -29.097622 289.040027
38 -320.168066 -29.097622
39 346.246141 -320.168066
40 231.996524 346.246141
41 109.384054 231.996524
42 -25.418214 109.384054
43 -1086.889242 -25.418214
44 22.686144 -1086.889242
45 299.013648 22.686144
46 -747.617237 299.013648
47 48.641162 -747.617237
48 -717.124080 48.641162
49 -41.622703 -717.124080
50 277.150903 -41.622703
51 789.085982 277.150903
52 588.395789 789.085982
53 193.779679 588.395789
54 -584.974653 193.779679
55 478.245337 -584.974653
56 -50.857789 478.245337
57 -1198.133431 -50.857789
58 441.367028 -1198.133431
59 -175.312062 441.367028
> 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/7v1q81258678474.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/85ckc1258678474.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/991ve1258678474.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/101foc1258678474.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/119pnj1258678474.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/12pod81258678474.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/13vaf01258678474.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/14noyt1258678474.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/159w0k1258678475.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/167s8j1258678475.tab")
+ }
>
> system("convert tmp/1veja1258678474.ps tmp/1veja1258678474.png")
> system("convert tmp/2eqim1258678474.ps tmp/2eqim1258678474.png")
> system("convert tmp/3taz01258678474.ps tmp/3taz01258678474.png")
> system("convert tmp/45kh21258678474.ps tmp/45kh21258678474.png")
> system("convert tmp/5zqk51258678474.ps tmp/5zqk51258678474.png")
> system("convert tmp/6eyxb1258678474.ps tmp/6eyxb1258678474.png")
> system("convert tmp/7v1q81258678474.ps tmp/7v1q81258678474.png")
> system("convert tmp/85ckc1258678474.ps tmp/85ckc1258678474.png")
> system("convert tmp/991ve1258678474.ps tmp/991ve1258678474.png")
> system("convert tmp/101foc1258678474.ps tmp/101foc1258678474.png")
>
>
> proc.time()
user system elapsed
2.377 1.549 2.998