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(3499
+ ,1
+ ,4164
+ ,3902
+ ,3186
+ ,3353
+ ,4145
+ ,1
+ ,3499
+ ,4164
+ ,3902
+ ,3186
+ ,3796
+ ,1
+ ,4145
+ ,3499
+ ,4164
+ ,3902
+ ,3711
+ ,1
+ ,3796
+ ,4145
+ ,3499
+ ,4164
+ ,3949
+ ,1
+ ,3711
+ ,3796
+ ,4145
+ ,3499
+ ,3740
+ ,1
+ ,3949
+ ,3711
+ ,3796
+ ,4145
+ ,3243
+ ,1
+ ,3740
+ ,3949
+ ,3711
+ ,3796
+ ,4407
+ ,1
+ ,3243
+ ,3740
+ ,3949
+ ,3711
+ ,4814
+ ,1
+ ,4407
+ ,3243
+ ,3740
+ ,3949
+ ,3908
+ ,1
+ ,4814
+ ,4407
+ ,3243
+ ,3740
+ ,5250
+ ,1
+ ,3908
+ ,4814
+ ,4407
+ ,3243
+ ,3937
+ ,1
+ ,5250
+ ,3908
+ ,4814
+ ,4407
+ ,4004
+ ,1
+ ,3937
+ ,5250
+ ,3908
+ ,4814
+ ,5560
+ ,1
+ ,4004
+ ,3937
+ ,5250
+ ,3908
+ ,3922
+ ,1
+ ,5560
+ ,4004
+ ,3937
+ ,5250
+ ,3759
+ ,1
+ ,3922
+ ,5560
+ ,4004
+ ,3937
+ ,4138
+ ,1
+ ,3759
+ ,3922
+ ,5560
+ ,4004
+ ,4634
+ ,1
+ ,4138
+ ,3759
+ ,3922
+ ,5560
+ ,3996
+ ,1
+ ,4634
+ ,4138
+ ,3759
+ ,3922
+ ,4308
+ ,1
+ ,3996
+ ,4634
+ ,4138
+ ,3759
+ ,4143
+ ,0
+ ,4308
+ ,3996
+ ,4634
+ ,4138
+ ,4429
+ ,0
+ ,4143
+ ,4308
+ ,3996
+ ,4634
+ ,5219
+ ,0
+ ,4429
+ ,4143
+ ,4308
+ ,3996
+ ,4929
+ ,0
+ ,5219
+ ,4429
+ ,4143
+ ,4308
+ ,5755
+ ,0
+ ,4929
+ ,5219
+ ,4429
+ ,4143
+ ,5592
+ ,0
+ ,5755
+ ,4929
+ ,5219
+ ,4429
+ ,4163
+ ,0
+ ,5592
+ ,5755
+ ,4929
+ ,5219
+ ,4962
+ ,0
+ ,4163
+ ,5592
+ ,5755
+ ,4929
+ ,5208
+ ,0
+ ,4962
+ ,4163
+ ,5592
+ ,5755
+ ,4755
+ ,0
+ ,5208
+ ,4962
+ ,4163
+ ,5592
+ ,4491
+ ,0
+ ,4755
+ ,5208
+ ,4962
+ ,4163
+ ,5732
+ ,0
+ ,4491
+ ,4755
+ ,5208
+ ,4962
+ ,5731
+ ,0
+ ,5732
+ ,4491
+ ,4755
+ ,5208
+ ,5040
+ ,0
+ ,5731
+ ,5732
+ ,4491
+ ,4755
+ ,6102
+ ,0
+ ,5040
+ ,5731
+ ,5732
+ ,4491
+ ,4904
+ ,0
+ ,6102
+ ,5040
+ ,5731
+ ,5732
+ ,5369
+ ,0
+ ,4904
+ ,6102
+ ,5040
+ ,5731
+ ,5578
+ ,0
+ ,5369
+ ,4904
+ ,6102
+ ,5040
+ ,4619
+ ,0
+ ,5578
+ ,5369
+ ,4904
+ ,6102
+ ,4731
+ ,0
+ ,4619
+ ,5578
+ ,5369
+ ,4904
+ ,5011
+ ,0
+ ,4731
+ ,4619
+ ,5578
+ ,5369
+ ,5299
+ ,0
+ ,5011
+ ,4731
+ ,4619
+ ,5578
+ ,4146
+ ,0
+ ,5299
+ ,5011
+ ,4731
+ ,4619
+ ,4625
+ ,0
+ ,4146
+ ,5299
+ ,5011
+ ,4731
+ ,4736
+ ,0
+ ,4625
+ ,4146
+ ,5299
+ ,5011
+ ,4219
+ ,0
+ ,4736
+ ,4625
+ ,4146
+ ,5299
+ ,5116
+ ,0
+ ,4219
+ ,4736
+ ,4625
+ ,4146
+ ,4205
+ ,0
+ ,5116
+ ,4219
+ ,4736
+ ,4625
+ ,4121
+ ,0
+ ,4205
+ ,5116
+ ,4219
+ ,4736
+ ,5103
+ ,1
+ ,4121
+ ,4205
+ ,5116
+ ,4219
+ ,4300
+ ,1
+ ,5103
+ ,4121
+ ,4205
+ ,5116
+ ,4578
+ ,1
+ ,4300
+ ,5103
+ ,4121
+ ,4205
+ ,3809
+ ,1
+ ,4578
+ ,4300
+ ,5103
+ ,4121
+ ,5526
+ ,1
+ ,3809
+ ,4578
+ ,4300
+ ,5103
+ ,4247
+ ,1
+ ,5526
+ ,3809
+ ,4578
+ ,4300
+ ,3830
+ ,1
+ ,4247
+ ,5526
+ ,3809
+ ,4578
+ ,4394
+ ,1
+ ,3830
+ ,4247
+ ,5526
+ ,3809)
+ ,dim=c(6
+ ,57)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:57))
> y <- array(NA,dim=c(6,57),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:57))
> 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 M10 M11 t
1 3499 1 4164 3902 3186 3353 1 0 0 0 0 0 0 0 0 0 0 1
2 4145 1 3499 4164 3902 3186 0 1 0 0 0 0 0 0 0 0 0 2
3 3796 1 4145 3499 4164 3902 0 0 1 0 0 0 0 0 0 0 0 3
4 3711 1 3796 4145 3499 4164 0 0 0 1 0 0 0 0 0 0 0 4
5 3949 1 3711 3796 4145 3499 0 0 0 0 1 0 0 0 0 0 0 5
6 3740 1 3949 3711 3796 4145 0 0 0 0 0 1 0 0 0 0 0 6
7 3243 1 3740 3949 3711 3796 0 0 0 0 0 0 1 0 0 0 0 7
8 4407 1 3243 3740 3949 3711 0 0 0 0 0 0 0 1 0 0 0 8
9 4814 1 4407 3243 3740 3949 0 0 0 0 0 0 0 0 1 0 0 9
10 3908 1 4814 4407 3243 3740 0 0 0 0 0 0 0 0 0 1 0 10
11 5250 1 3908 4814 4407 3243 0 0 0 0 0 0 0 0 0 0 1 11
12 3937 1 5250 3908 4814 4407 0 0 0 0 0 0 0 0 0 0 0 12
13 4004 1 3937 5250 3908 4814 1 0 0 0 0 0 0 0 0 0 0 13
14 5560 1 4004 3937 5250 3908 0 1 0 0 0 0 0 0 0 0 0 14
15 3922 1 5560 4004 3937 5250 0 0 1 0 0 0 0 0 0 0 0 15
16 3759 1 3922 5560 4004 3937 0 0 0 1 0 0 0 0 0 0 0 16
17 4138 1 3759 3922 5560 4004 0 0 0 0 1 0 0 0 0 0 0 17
18 4634 1 4138 3759 3922 5560 0 0 0 0 0 1 0 0 0 0 0 18
19 3996 1 4634 4138 3759 3922 0 0 0 0 0 0 1 0 0 0 0 19
20 4308 1 3996 4634 4138 3759 0 0 0 0 0 0 0 1 0 0 0 20
21 4143 0 4308 3996 4634 4138 0 0 0 0 0 0 0 0 1 0 0 21
22 4429 0 4143 4308 3996 4634 0 0 0 0 0 0 0 0 0 1 0 22
23 5219 0 4429 4143 4308 3996 0 0 0 0 0 0 0 0 0 0 1 23
24 4929 0 5219 4429 4143 4308 0 0 0 0 0 0 0 0 0 0 0 24
25 5755 0 4929 5219 4429 4143 1 0 0 0 0 0 0 0 0 0 0 25
26 5592 0 5755 4929 5219 4429 0 1 0 0 0 0 0 0 0 0 0 26
27 4163 0 5592 5755 4929 5219 0 0 1 0 0 0 0 0 0 0 0 27
28 4962 0 4163 5592 5755 4929 0 0 0 1 0 0 0 0 0 0 0 28
29 5208 0 4962 4163 5592 5755 0 0 0 0 1 0 0 0 0 0 0 29
30 4755 0 5208 4962 4163 5592 0 0 0 0 0 1 0 0 0 0 0 30
31 4491 0 4755 5208 4962 4163 0 0 0 0 0 0 1 0 0 0 0 31
32 5732 0 4491 4755 5208 4962 0 0 0 0 0 0 0 1 0 0 0 32
33 5731 0 5732 4491 4755 5208 0 0 0 0 0 0 0 0 1 0 0 33
34 5040 0 5731 5732 4491 4755 0 0 0 0 0 0 0 0 0 1 0 34
35 6102 0 5040 5731 5732 4491 0 0 0 0 0 0 0 0 0 0 1 35
36 4904 0 6102 5040 5731 5732 0 0 0 0 0 0 0 0 0 0 0 36
37 5369 0 4904 6102 5040 5731 1 0 0 0 0 0 0 0 0 0 0 37
38 5578 0 5369 4904 6102 5040 0 1 0 0 0 0 0 0 0 0 0 38
39 4619 0 5578 5369 4904 6102 0 0 1 0 0 0 0 0 0 0 0 39
40 4731 0 4619 5578 5369 4904 0 0 0 1 0 0 0 0 0 0 0 40
41 5011 0 4731 4619 5578 5369 0 0 0 0 1 0 0 0 0 0 0 41
42 5299 0 5011 4731 4619 5578 0 0 0 0 0 1 0 0 0 0 0 42
43 4146 0 5299 5011 4731 4619 0 0 0 0 0 0 1 0 0 0 0 43
44 4625 0 4146 5299 5011 4731 0 0 0 0 0 0 0 1 0 0 0 44
45 4736 0 4625 4146 5299 5011 0 0 0 0 0 0 0 0 1 0 0 45
46 4219 0 4736 4625 4146 5299 0 0 0 0 0 0 0 0 0 1 0 46
47 5116 0 4219 4736 4625 4146 0 0 0 0 0 0 0 0 0 0 1 47
48 4205 0 5116 4219 4736 4625 0 0 0 0 0 0 0 0 0 0 0 48
49 4121 0 4205 5116 4219 4736 1 0 0 0 0 0 0 0 0 0 0 49
50 5103 1 4121 4205 5116 4219 0 1 0 0 0 0 0 0 0 0 0 50
51 4300 1 5103 4121 4205 5116 0 0 1 0 0 0 0 0 0 0 0 51
52 4578 1 4300 5103 4121 4205 0 0 0 1 0 0 0 0 0 0 0 52
53 3809 1 4578 4300 5103 4121 0 0 0 0 1 0 0 0 0 0 0 53
54 5526 1 3809 4578 4300 5103 0 0 0 0 0 1 0 0 0 0 0 54
55 4247 1 5526 3809 4578 4300 0 0 0 0 0 0 1 0 0 0 0 55
56 3830 1 4247 5526 3809 4578 0 0 0 0 0 0 0 1 0 0 0 56
57 4394 1 3830 4247 5526 3809 0 0 0 0 0 0 0 0 1 0 0 57
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
815.44005 -146.98586 0.32207 -0.09803 0.38574 0.12049
M1 M2 M3 M4 M5 M6
756.04155 1003.38138 -76.43364 546.36980 196.75508 882.12846
M7 M8 M9 M10 M11 t
58.57740 847.25487 597.63691 482.01412 1430.83046 -1.58386
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-672.83 -240.73 -83.28 229.57 1009.44
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 815.44005 1073.55646 0.760 0.452079
X -146.98586 193.28943 -0.760 0.451562
Y1 0.32207 0.15600 2.064 0.045668 *
Y2 -0.09803 0.15672 -0.626 0.535254
Y3 0.38574 0.15882 2.429 0.019858 *
Y4 0.12049 0.17061 0.706 0.484230
M1 756.04155 385.70046 1.960 0.057147 .
M2 1003.38138 327.00956 3.068 0.003904 **
M3 -76.43364 327.67708 -0.233 0.816780
M4 546.36980 392.63877 1.392 0.171951
M5 196.75508 335.58480 0.586 0.561049
M6 882.12846 378.26228 2.332 0.024954 *
M7 58.57740 314.27992 0.186 0.853108
M8 847.25487 376.57453 2.250 0.030172 *
M9 597.63691 315.11334 1.897 0.065308 .
M10 482.01412 365.35485 1.319 0.194761
M11 1430.83046 367.60310 3.892 0.000377 ***
t -1.58386 4.61848 -0.343 0.733485
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 438.6 on 39 degrees of freedom
Multiple R-squared: 0.701, Adjusted R-squared: 0.5707
F-statistic: 5.379 on 17 and 39 DF, p-value: 7.012e-06
> 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,] 0.4611570 0.9223141 0.53884296
[2,] 0.3222646 0.6445292 0.67773541
[3,] 0.2823879 0.5647757 0.71761214
[4,] 0.4572472 0.9144945 0.54275277
[5,] 0.8986205 0.2027590 0.10137948
[6,] 0.8298377 0.3403246 0.17016231
[7,] 0.7611462 0.4777076 0.23885382
[8,] 0.7285398 0.5429205 0.27146023
[9,] 0.6465258 0.7069483 0.35347417
[10,] 0.9146312 0.1707377 0.08536884
[11,] 0.9338303 0.1323394 0.06616969
[12,] 0.8917503 0.2164994 0.10824972
[13,] 0.8203169 0.3593662 0.17968310
[14,] 0.8098168 0.3803665 0.19018323
[15,] 0.7428166 0.5143669 0.25718345
[16,] 0.7117627 0.5764745 0.28823727
> postscript(file="/var/www/html/rcomp/tmp/1ukni1258622710.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/24mez1258622710.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3xu0v1258622710.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4f00g1258622710.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/51p561258622710.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 = 57
Frequency = 1
1 2 3 4 5 6 7
-515.44692 -131.40949 140.40537 -165.13782 248.16523 -672.82591 -179.20703
8 9 10 11 12 13 14
255.71389 542.24951 -46.61940 290.72712 -408.14009 -240.72737 510.72900
15 16 17 18 19 20 21
-195.66932 -167.44000 -153.60340 -35.08691 289.70263 -57.84209 -518.64906
22 23 24 25 26 27 28
154.62010 -154.37347 787.69842 939.64687 -102.75934 -300.21494 38.14311
29 30 31 32 33 34 35
201.26815 -365.56193 229.56747 532.92396 502.65816 207.26467 97.59244
36 37 38 39 40 41 42
-226.91631 240.23765 -390.11436 44.70643 -170.17828 194.28606 64.03648
43 44 45 46 47 48 49
-256.78290 -286.80234 -336.73333 -315.26536 -233.94610 -152.64202 -423.71023
50 51 52 53 54 55 56
113.55418 310.77246 464.61299 -490.11604 1009.43826 -83.28017 -443.99342
57
-189.52528
> postscript(file="/var/www/html/rcomp/tmp/6ilrx1258622710.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 = 57
Frequency = 1
lag(myerror, k = 1) myerror
0 -515.44692 NA
1 -131.40949 -515.44692
2 140.40537 -131.40949
3 -165.13782 140.40537
4 248.16523 -165.13782
5 -672.82591 248.16523
6 -179.20703 -672.82591
7 255.71389 -179.20703
8 542.24951 255.71389
9 -46.61940 542.24951
10 290.72712 -46.61940
11 -408.14009 290.72712
12 -240.72737 -408.14009
13 510.72900 -240.72737
14 -195.66932 510.72900
15 -167.44000 -195.66932
16 -153.60340 -167.44000
17 -35.08691 -153.60340
18 289.70263 -35.08691
19 -57.84209 289.70263
20 -518.64906 -57.84209
21 154.62010 -518.64906
22 -154.37347 154.62010
23 787.69842 -154.37347
24 939.64687 787.69842
25 -102.75934 939.64687
26 -300.21494 -102.75934
27 38.14311 -300.21494
28 201.26815 38.14311
29 -365.56193 201.26815
30 229.56747 -365.56193
31 532.92396 229.56747
32 502.65816 532.92396
33 207.26467 502.65816
34 97.59244 207.26467
35 -226.91631 97.59244
36 240.23765 -226.91631
37 -390.11436 240.23765
38 44.70643 -390.11436
39 -170.17828 44.70643
40 194.28606 -170.17828
41 64.03648 194.28606
42 -256.78290 64.03648
43 -286.80234 -256.78290
44 -336.73333 -286.80234
45 -315.26536 -336.73333
46 -233.94610 -315.26536
47 -152.64202 -233.94610
48 -423.71023 -152.64202
49 113.55418 -423.71023
50 310.77246 113.55418
51 464.61299 310.77246
52 -490.11604 464.61299
53 1009.43826 -490.11604
54 -83.28017 1009.43826
55 -443.99342 -83.28017
56 -189.52528 -443.99342
57 NA -189.52528
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -131.40949 -515.44692
[2,] 140.40537 -131.40949
[3,] -165.13782 140.40537
[4,] 248.16523 -165.13782
[5,] -672.82591 248.16523
[6,] -179.20703 -672.82591
[7,] 255.71389 -179.20703
[8,] 542.24951 255.71389
[9,] -46.61940 542.24951
[10,] 290.72712 -46.61940
[11,] -408.14009 290.72712
[12,] -240.72737 -408.14009
[13,] 510.72900 -240.72737
[14,] -195.66932 510.72900
[15,] -167.44000 -195.66932
[16,] -153.60340 -167.44000
[17,] -35.08691 -153.60340
[18,] 289.70263 -35.08691
[19,] -57.84209 289.70263
[20,] -518.64906 -57.84209
[21,] 154.62010 -518.64906
[22,] -154.37347 154.62010
[23,] 787.69842 -154.37347
[24,] 939.64687 787.69842
[25,] -102.75934 939.64687
[26,] -300.21494 -102.75934
[27,] 38.14311 -300.21494
[28,] 201.26815 38.14311
[29,] -365.56193 201.26815
[30,] 229.56747 -365.56193
[31,] 532.92396 229.56747
[32,] 502.65816 532.92396
[33,] 207.26467 502.65816
[34,] 97.59244 207.26467
[35,] -226.91631 97.59244
[36,] 240.23765 -226.91631
[37,] -390.11436 240.23765
[38,] 44.70643 -390.11436
[39,] -170.17828 44.70643
[40,] 194.28606 -170.17828
[41,] 64.03648 194.28606
[42,] -256.78290 64.03648
[43,] -286.80234 -256.78290
[44,] -336.73333 -286.80234
[45,] -315.26536 -336.73333
[46,] -233.94610 -315.26536
[47,] -152.64202 -233.94610
[48,] -423.71023 -152.64202
[49,] 113.55418 -423.71023
[50,] 310.77246 113.55418
[51,] 464.61299 310.77246
[52,] -490.11604 464.61299
[53,] 1009.43826 -490.11604
[54,] -83.28017 1009.43826
[55,] -443.99342 -83.28017
[56,] -189.52528 -443.99342
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -131.40949 -515.44692
2 140.40537 -131.40949
3 -165.13782 140.40537
4 248.16523 -165.13782
5 -672.82591 248.16523
6 -179.20703 -672.82591
7 255.71389 -179.20703
8 542.24951 255.71389
9 -46.61940 542.24951
10 290.72712 -46.61940
11 -408.14009 290.72712
12 -240.72737 -408.14009
13 510.72900 -240.72737
14 -195.66932 510.72900
15 -167.44000 -195.66932
16 -153.60340 -167.44000
17 -35.08691 -153.60340
18 289.70263 -35.08691
19 -57.84209 289.70263
20 -518.64906 -57.84209
21 154.62010 -518.64906
22 -154.37347 154.62010
23 787.69842 -154.37347
24 939.64687 787.69842
25 -102.75934 939.64687
26 -300.21494 -102.75934
27 38.14311 -300.21494
28 201.26815 38.14311
29 -365.56193 201.26815
30 229.56747 -365.56193
31 532.92396 229.56747
32 502.65816 532.92396
33 207.26467 502.65816
34 97.59244 207.26467
35 -226.91631 97.59244
36 240.23765 -226.91631
37 -390.11436 240.23765
38 44.70643 -390.11436
39 -170.17828 44.70643
40 194.28606 -170.17828
41 64.03648 194.28606
42 -256.78290 64.03648
43 -286.80234 -256.78290
44 -336.73333 -286.80234
45 -315.26536 -336.73333
46 -233.94610 -315.26536
47 -152.64202 -233.94610
48 -423.71023 -152.64202
49 113.55418 -423.71023
50 310.77246 113.55418
51 464.61299 310.77246
52 -490.11604 464.61299
53 1009.43826 -490.11604
54 -83.28017 1009.43826
55 -443.99342 -83.28017
56 -189.52528 -443.99342
> 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/7ob7h1258622710.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/80y0z1258622710.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/93v2k1258622710.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10qcvz1258622710.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11sxkj1258622710.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/12frzn1258622710.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/13ccyd1258622710.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/14i86o1258622710.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/15kct31258622710.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/16dg3k1258622710.tab")
+ }
>
> system("convert tmp/1ukni1258622710.ps tmp/1ukni1258622710.png")
> system("convert tmp/24mez1258622710.ps tmp/24mez1258622710.png")
> system("convert tmp/3xu0v1258622710.ps tmp/3xu0v1258622710.png")
> system("convert tmp/4f00g1258622710.ps tmp/4f00g1258622710.png")
> system("convert tmp/51p561258622710.ps tmp/51p561258622710.png")
> system("convert tmp/6ilrx1258622710.ps tmp/6ilrx1258622710.png")
> system("convert tmp/7ob7h1258622710.ps tmp/7ob7h1258622710.png")
> system("convert tmp/80y0z1258622710.ps tmp/80y0z1258622710.png")
> system("convert tmp/93v2k1258622710.ps tmp/93v2k1258622710.png")
> system("convert tmp/10qcvz1258622710.ps tmp/10qcvz1258622710.png")
>
>
> proc.time()
user system elapsed
2.333 1.544 2.846