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(3759
+ ,36.71
+ ,3922
+ ,5560
+ ,4138
+ ,36.72
+ ,3759
+ ,3922
+ ,4634
+ ,36.73
+ ,4138
+ ,3759
+ ,3996
+ ,36.73
+ ,4634
+ ,4138
+ ,4308
+ ,36.87
+ ,3996
+ ,4634
+ ,4429
+ ,37.31
+ ,4308
+ ,3996
+ ,5219
+ ,37.39
+ ,4429
+ ,4308
+ ,4929
+ ,37.42
+ ,5219
+ ,4429
+ ,5755
+ ,37.51
+ ,4929
+ ,5219
+ ,5592
+ ,37.67
+ ,5755
+ ,4929
+ ,4163
+ ,37.67
+ ,5592
+ ,5755
+ ,4962
+ ,37.71
+ ,4163
+ ,5592
+ ,5208
+ ,37.78
+ ,4962
+ ,4163
+ ,4755
+ ,37.79
+ ,5208
+ ,4962
+ ,4491
+ ,37.84
+ ,4755
+ ,5208
+ ,5732
+ ,37.88
+ ,4491
+ ,4755
+ ,5731
+ ,38.34
+ ,5732
+ ,4491
+ ,5040
+ ,38.58
+ ,5731
+ ,5732
+ ,6102
+ ,38.72
+ ,5040
+ ,5731
+ ,4904
+ ,38.83
+ ,6102
+ ,5040
+ ,5369
+ ,38.9
+ ,4904
+ ,6102
+ ,5578
+ ,38.92
+ ,5369
+ ,4904
+ ,4619
+ ,38.94
+ ,5578
+ ,5369
+ ,4731
+ ,39.1
+ ,4619
+ ,5578
+ ,5011
+ ,39.14
+ ,4731
+ ,4619
+ ,5299
+ ,39.16
+ ,5011
+ ,4731
+ ,4146
+ ,39.32
+ ,5299
+ ,5011
+ ,4625
+ ,39.34
+ ,4146
+ ,5299
+ ,4736
+ ,39.44
+ ,4625
+ ,4146
+ ,4219
+ ,39.92
+ ,4736
+ ,4625
+ ,5116
+ ,40.19
+ ,4219
+ ,4736
+ ,4205
+ ,40.2
+ ,5116
+ ,4219
+ ,4121
+ ,40.27
+ ,4205
+ ,5116
+ ,5103
+ ,40.28
+ ,4121
+ ,4205
+ ,4300
+ ,40.3
+ ,5103
+ ,4121
+ ,4578
+ ,40.34
+ ,4300
+ ,5103
+ ,3809
+ ,40.4
+ ,4578
+ ,4300
+ ,5526
+ ,40.43
+ ,3809
+ ,4578
+ ,4247
+ ,40.48
+ ,5526
+ ,3809
+ ,3830
+ ,40.48
+ ,4247
+ ,5526
+ ,4394
+ ,40.63
+ ,3830
+ ,4247
+ ,4826
+ ,40.74
+ ,4394
+ ,3830
+ ,4409
+ ,40.77
+ ,4826
+ ,4394
+ ,4569
+ ,40.91
+ ,4409
+ ,4826
+ ,4106
+ ,40.92
+ ,4569
+ ,4409
+ ,4794
+ ,41.03
+ ,4106
+ ,4569
+ ,3914
+ ,41
+ ,4794
+ ,4106
+ ,3793
+ ,41.04
+ ,3914
+ ,4794
+ ,4405
+ ,41.33
+ ,3793
+ ,3914
+ ,4022
+ ,41.44
+ ,4405
+ ,3793
+ ,4100
+ ,41.46
+ ,4022
+ ,4405
+ ,4788
+ ,41.55
+ ,4100
+ ,4022
+ ,3163
+ ,41.55
+ ,4788
+ ,4100
+ ,3585
+ ,41.81
+ ,3163
+ ,4788
+ ,3903
+ ,41.78
+ ,3585
+ ,3163
+ ,4178
+ ,41.84
+ ,3903
+ ,3585
+ ,3863
+ ,41.84
+ ,4178
+ ,3903
+ ,4187
+ ,41.86
+ ,3863
+ ,4178)
+ ,dim=c(4
+ ,58)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2')
+ ,1:58))
> y <- array(NA,dim=c(4,58),dimnames=list(c('Y','X','Y1','Y2'),1:58))
> 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 = '3'
> #'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
Y1 Y X Y2 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t
1 3922 3759 36.71 5560 1 0 0 0 0 0 0 0 0 0 0 1
2 3759 4138 36.72 3922 0 1 0 0 0 0 0 0 0 0 0 2
3 4138 4634 36.73 3759 0 0 1 0 0 0 0 0 0 0 0 3
4 4634 3996 36.73 4138 0 0 0 1 0 0 0 0 0 0 0 4
5 3996 4308 36.87 4634 0 0 0 0 1 0 0 0 0 0 0 5
6 4308 4429 37.31 3996 0 0 0 0 0 1 0 0 0 0 0 6
7 4429 5219 37.39 4308 0 0 0 0 0 0 1 0 0 0 0 7
8 5219 4929 37.42 4429 0 0 0 0 0 0 0 1 0 0 0 8
9 4929 5755 37.51 5219 0 0 0 0 0 0 0 0 1 0 0 9
10 5755 5592 37.67 4929 0 0 0 0 0 0 0 0 0 1 0 10
11 5592 4163 37.67 5755 0 0 0 0 0 0 0 0 0 0 1 11
12 4163 4962 37.71 5592 0 0 0 0 0 0 0 0 0 0 0 12
13 4962 5208 37.78 4163 1 0 0 0 0 0 0 0 0 0 0 13
14 5208 4755 37.79 4962 0 1 0 0 0 0 0 0 0 0 0 14
15 4755 4491 37.84 5208 0 0 1 0 0 0 0 0 0 0 0 15
16 4491 5732 37.88 4755 0 0 0 1 0 0 0 0 0 0 0 16
17 5732 5731 38.34 4491 0 0 0 0 1 0 0 0 0 0 0 17
18 5731 5040 38.58 5732 0 0 0 0 0 1 0 0 0 0 0 18
19 5040 6102 38.72 5731 0 0 0 0 0 0 1 0 0 0 0 19
20 6102 4904 38.83 5040 0 0 0 0 0 0 0 1 0 0 0 20
21 4904 5369 38.90 6102 0 0 0 0 0 0 0 0 1 0 0 21
22 5369 5578 38.92 4904 0 0 0 0 0 0 0 0 0 1 0 22
23 5578 4619 38.94 5369 0 0 0 0 0 0 0 0 0 0 1 23
24 4619 4731 39.10 5578 0 0 0 0 0 0 0 0 0 0 0 24
25 4731 5011 39.14 4619 1 0 0 0 0 0 0 0 0 0 0 25
26 5011 5299 39.16 4731 0 1 0 0 0 0 0 0 0 0 0 26
27 5299 4146 39.32 5011 0 0 1 0 0 0 0 0 0 0 0 27
28 4146 4625 39.34 5299 0 0 0 1 0 0 0 0 0 0 0 28
29 4625 4736 39.44 4146 0 0 0 0 1 0 0 0 0 0 0 29
30 4736 4219 39.92 4625 0 0 0 0 0 1 0 0 0 0 0 30
31 4219 5116 40.19 4736 0 0 0 0 0 0 1 0 0 0 0 31
32 5116 4205 40.20 4219 0 0 0 0 0 0 0 1 0 0 0 32
33 4205 4121 40.27 5116 0 0 0 0 0 0 0 0 1 0 0 33
34 4121 5103 40.28 4205 0 0 0 0 0 0 0 0 0 1 0 34
35 5103 4300 40.30 4121 0 0 0 0 0 0 0 0 0 0 1 35
36 4300 4578 40.34 5103 0 0 0 0 0 0 0 0 0 0 0 36
37 4578 3809 40.40 4300 1 0 0 0 0 0 0 0 0 0 0 37
38 3809 5526 40.43 4578 0 1 0 0 0 0 0 0 0 0 0 38
39 5526 4247 40.48 3809 0 0 1 0 0 0 0 0 0 0 0 39
40 4247 3830 40.48 5526 0 0 0 1 0 0 0 0 0 0 0 40
41 3830 4394 40.63 4247 0 0 0 0 1 0 0 0 0 0 0 41
42 4394 4826 40.74 3830 0 0 0 0 0 1 0 0 0 0 0 42
43 4826 4409 40.77 4394 0 0 0 0 0 0 1 0 0 0 0 43
44 4409 4569 40.91 4826 0 0 0 0 0 0 0 1 0 0 0 44
45 4569 4106 40.92 4409 0 0 0 0 0 0 0 0 1 0 0 45
46 4106 4794 41.03 4569 0 0 0 0 0 0 0 0 0 1 0 46
47 4794 3914 41.00 4106 0 0 0 0 0 0 0 0 0 0 1 47
48 3914 3793 41.04 4794 0 0 0 0 0 0 0 0 0 0 0 48
49 3793 4405 41.33 3914 1 0 0 0 0 0 0 0 0 0 0 49
50 4405 4022 41.44 3793 0 1 0 0 0 0 0 0 0 0 0 50
51 4022 4100 41.46 4405 0 0 1 0 0 0 0 0 0 0 0 51
52 4100 4788 41.55 4022 0 0 0 1 0 0 0 0 0 0 0 52
53 4788 3163 41.55 4100 0 0 0 0 1 0 0 0 0 0 0 53
54 3163 3585 41.81 4788 0 0 0 0 0 1 0 0 0 0 0 54
55 3585 3903 41.78 3163 0 0 0 0 0 0 1 0 0 0 0 55
56 3903 4178 41.84 3585 0 0 0 0 0 0 0 1 0 0 0 56
57 4178 3863 41.84 3903 0 0 0 0 0 0 0 0 1 0 0 57
58 3863 4187 41.86 4178 0 0 0 0 0 0 0 0 0 1 0 58
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Y X Y2 M1 M2
-1.457e+04 2.861e-01 4.591e+02 1.730e-01 2.635e+02 2.705e+02
M3 M4 M5 M6 M7 M8
7.189e+02 2.010e+02 5.547e+02 3.041e+02 1.342e+02 8.037e+02
M9 M10 M11 t
3.238e+02 3.826e+02 1.149e+03 -5.118e+01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-875.922 -347.223 -4.976 370.553 919.757
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1.457e+04 1.496e+04 -0.974 0.33550
Y 2.861e-01 1.482e-01 1.931 0.06029 .
X 4.591e+02 4.169e+02 1.101 0.27712
Y2 1.730e-01 1.447e-01 1.195 0.23863
M1 2.635e+02 3.791e+02 0.695 0.49091
M2 2.705e+02 3.847e+02 0.703 0.48587
M3 7.189e+02 3.788e+02 1.898 0.06462 .
M4 2.010e+02 3.707e+02 0.542 0.59057
M5 5.547e+02 3.826e+02 1.450 0.15459
M6 3.041e+02 3.792e+02 0.802 0.42713
M7 1.342e+02 3.909e+02 0.343 0.73313
M8 8.037e+02 3.842e+02 2.092 0.04254 *
M9 3.238e+02 3.637e+02 0.890 0.37843
M10 3.826e+02 3.854e+02 0.993 0.32646
M11 1.149e+03 3.860e+02 2.977 0.00481 **
t -5.118e+01 4.109e+01 -1.246 0.21981
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 535.1 on 42 degrees of freedom
Multiple R-squared: 0.4717, Adjusted R-squared: 0.283
F-statistic: 2.5 on 15 and 42 DF, p-value: 0.009925
> 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,] 0.7749488 0.4501024 0.22505120
[2,] 0.8300501 0.3398999 0.16994994
[3,] 0.8924716 0.2150569 0.10752843
[4,] 0.9233146 0.1533707 0.07668537
[5,] 0.8916043 0.2167914 0.10839569
[6,] 0.8255558 0.3488884 0.17444422
[7,] 0.7553782 0.4892436 0.24462181
[8,] 0.6809397 0.6381205 0.31906025
[9,] 0.6018491 0.7963018 0.39815090
[10,] 0.7376086 0.5247828 0.26239140
[11,] 0.7251734 0.5496532 0.27482659
[12,] 0.6291110 0.7417779 0.37088897
[13,] 0.5621982 0.8756036 0.43780181
[14,] 0.4591502 0.9183003 0.54084983
[15,] 0.3582041 0.7164082 0.64179591
[16,] 0.4300824 0.8601649 0.56991757
[17,] 0.3139779 0.6279557 0.68602215
[18,] 0.2328509 0.4657019 0.76714905
[19,] 0.1659012 0.3318023 0.83409884
[20,] 0.2123001 0.4246002 0.78769991
[21,] 0.2202661 0.4405322 0.77973391
> postscript(file="/var/www/html/rcomp/tmp/1e8d31258494695.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2kpch1258494695.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3pdni1258494695.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4aiz41258494695.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/56n8o1258494695.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 = 58
Frequency = 1
1 2 3 4 5 6
-606.328260 -554.849250 -691.389111 490.698697 -689.135910 -201.642562
7 8 9 10 11 12
-176.225409 43.741541 -129.455852 712.235451 99.669923 -347.600367
13 14 15 16 17 18
383.788754 660.762924 -179.472224 -169.359225 603.891767 777.488024
19 20 21 22 23 24
-60.311832 795.122486 -220.669695 374.926745 53.168591 152.993635
25 26 27 28 29 30
120.136159 333.370736 432.068497 -347.820769 -49.576761 207.863357
31 32 33 34 35 36
-487.787703 136.358011 -406.845279 -626.427134 -124.854706 4.872258
37 38 39 40 41 42
401.933675 -875.922024 919.756970 32.199529 -696.304670 67.493159
43 44 45 46 47 48
728.558543 -491.494115 399.539754 -346.090234 -27.983809 189.734474
49 50 51 52 53 54
-299.530328 436.637614 -480.964132 -5.718231 831.125574 -851.201979
55 56 57 58
-4.233600 -483.727923 357.431072 -114.644827
> postscript(file="/var/www/html/rcomp/tmp/6nrku1258494695.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 = 58
Frequency = 1
lag(myerror, k = 1) myerror
0 -606.328260 NA
1 -554.849250 -606.328260
2 -691.389111 -554.849250
3 490.698697 -691.389111
4 -689.135910 490.698697
5 -201.642562 -689.135910
6 -176.225409 -201.642562
7 43.741541 -176.225409
8 -129.455852 43.741541
9 712.235451 -129.455852
10 99.669923 712.235451
11 -347.600367 99.669923
12 383.788754 -347.600367
13 660.762924 383.788754
14 -179.472224 660.762924
15 -169.359225 -179.472224
16 603.891767 -169.359225
17 777.488024 603.891767
18 -60.311832 777.488024
19 795.122486 -60.311832
20 -220.669695 795.122486
21 374.926745 -220.669695
22 53.168591 374.926745
23 152.993635 53.168591
24 120.136159 152.993635
25 333.370736 120.136159
26 432.068497 333.370736
27 -347.820769 432.068497
28 -49.576761 -347.820769
29 207.863357 -49.576761
30 -487.787703 207.863357
31 136.358011 -487.787703
32 -406.845279 136.358011
33 -626.427134 -406.845279
34 -124.854706 -626.427134
35 4.872258 -124.854706
36 401.933675 4.872258
37 -875.922024 401.933675
38 919.756970 -875.922024
39 32.199529 919.756970
40 -696.304670 32.199529
41 67.493159 -696.304670
42 728.558543 67.493159
43 -491.494115 728.558543
44 399.539754 -491.494115
45 -346.090234 399.539754
46 -27.983809 -346.090234
47 189.734474 -27.983809
48 -299.530328 189.734474
49 436.637614 -299.530328
50 -480.964132 436.637614
51 -5.718231 -480.964132
52 831.125574 -5.718231
53 -851.201979 831.125574
54 -4.233600 -851.201979
55 -483.727923 -4.233600
56 357.431072 -483.727923
57 -114.644827 357.431072
58 NA -114.644827
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -554.849250 -606.328260
[2,] -691.389111 -554.849250
[3,] 490.698697 -691.389111
[4,] -689.135910 490.698697
[5,] -201.642562 -689.135910
[6,] -176.225409 -201.642562
[7,] 43.741541 -176.225409
[8,] -129.455852 43.741541
[9,] 712.235451 -129.455852
[10,] 99.669923 712.235451
[11,] -347.600367 99.669923
[12,] 383.788754 -347.600367
[13,] 660.762924 383.788754
[14,] -179.472224 660.762924
[15,] -169.359225 -179.472224
[16,] 603.891767 -169.359225
[17,] 777.488024 603.891767
[18,] -60.311832 777.488024
[19,] 795.122486 -60.311832
[20,] -220.669695 795.122486
[21,] 374.926745 -220.669695
[22,] 53.168591 374.926745
[23,] 152.993635 53.168591
[24,] 120.136159 152.993635
[25,] 333.370736 120.136159
[26,] 432.068497 333.370736
[27,] -347.820769 432.068497
[28,] -49.576761 -347.820769
[29,] 207.863357 -49.576761
[30,] -487.787703 207.863357
[31,] 136.358011 -487.787703
[32,] -406.845279 136.358011
[33,] -626.427134 -406.845279
[34,] -124.854706 -626.427134
[35,] 4.872258 -124.854706
[36,] 401.933675 4.872258
[37,] -875.922024 401.933675
[38,] 919.756970 -875.922024
[39,] 32.199529 919.756970
[40,] -696.304670 32.199529
[41,] 67.493159 -696.304670
[42,] 728.558543 67.493159
[43,] -491.494115 728.558543
[44,] 399.539754 -491.494115
[45,] -346.090234 399.539754
[46,] -27.983809 -346.090234
[47,] 189.734474 -27.983809
[48,] -299.530328 189.734474
[49,] 436.637614 -299.530328
[50,] -480.964132 436.637614
[51,] -5.718231 -480.964132
[52,] 831.125574 -5.718231
[53,] -851.201979 831.125574
[54,] -4.233600 -851.201979
[55,] -483.727923 -4.233600
[56,] 357.431072 -483.727923
[57,] -114.644827 357.431072
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -554.849250 -606.328260
2 -691.389111 -554.849250
3 490.698697 -691.389111
4 -689.135910 490.698697
5 -201.642562 -689.135910
6 -176.225409 -201.642562
7 43.741541 -176.225409
8 -129.455852 43.741541
9 712.235451 -129.455852
10 99.669923 712.235451
11 -347.600367 99.669923
12 383.788754 -347.600367
13 660.762924 383.788754
14 -179.472224 660.762924
15 -169.359225 -179.472224
16 603.891767 -169.359225
17 777.488024 603.891767
18 -60.311832 777.488024
19 795.122486 -60.311832
20 -220.669695 795.122486
21 374.926745 -220.669695
22 53.168591 374.926745
23 152.993635 53.168591
24 120.136159 152.993635
25 333.370736 120.136159
26 432.068497 333.370736
27 -347.820769 432.068497
28 -49.576761 -347.820769
29 207.863357 -49.576761
30 -487.787703 207.863357
31 136.358011 -487.787703
32 -406.845279 136.358011
33 -626.427134 -406.845279
34 -124.854706 -626.427134
35 4.872258 -124.854706
36 401.933675 4.872258
37 -875.922024 401.933675
38 919.756970 -875.922024
39 32.199529 919.756970
40 -696.304670 32.199529
41 67.493159 -696.304670
42 728.558543 67.493159
43 -491.494115 728.558543
44 399.539754 -491.494115
45 -346.090234 399.539754
46 -27.983809 -346.090234
47 189.734474 -27.983809
48 -299.530328 189.734474
49 436.637614 -299.530328
50 -480.964132 436.637614
51 -5.718231 -480.964132
52 831.125574 -5.718231
53 -851.201979 831.125574
54 -4.233600 -851.201979
55 -483.727923 -4.233600
56 357.431072 -483.727923
57 -114.644827 357.431072
> 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/70tnj1258494695.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8k0k81258494695.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/99tqe1258494695.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10prry1258494695.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11u83s1258494695.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/12f1j61258494695.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/13avtp1258494695.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/14n8sb1258494695.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/158uhi1258494695.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/16ossu1258494695.tab")
+ }
>
> system("convert tmp/1e8d31258494695.ps tmp/1e8d31258494695.png")
> system("convert tmp/2kpch1258494695.ps tmp/2kpch1258494695.png")
> system("convert tmp/3pdni1258494695.ps tmp/3pdni1258494695.png")
> system("convert tmp/4aiz41258494695.ps tmp/4aiz41258494695.png")
> system("convert tmp/56n8o1258494695.ps tmp/56n8o1258494695.png")
> system("convert tmp/6nrku1258494695.ps tmp/6nrku1258494695.png")
> system("convert tmp/70tnj1258494695.ps tmp/70tnj1258494695.png")
> system("convert tmp/8k0k81258494695.ps tmp/8k0k81258494695.png")
> system("convert tmp/99tqe1258494695.ps tmp/99tqe1258494695.png")
> system("convert tmp/10prry1258494695.ps tmp/10prry1258494695.png")
>
>
> proc.time()
user system elapsed
2.359 1.546 2.769