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(2360
+ ,2
+ ,2267
+ ,1746
+ ,2069
+ ,2299
+ ,2214
+ ,2
+ ,2360
+ ,2267
+ ,1746
+ ,2069
+ ,2825
+ ,2
+ ,2214
+ ,2360
+ ,2267
+ ,1746
+ ,2355
+ ,2
+ ,2825
+ ,2214
+ ,2360
+ ,2267
+ ,2333
+ ,2
+ ,2355
+ ,2825
+ ,2214
+ ,2360
+ ,3016
+ ,2
+ ,2333
+ ,2355
+ ,2825
+ ,2214
+ ,2155
+ ,2
+ ,3016
+ ,2333
+ ,2355
+ ,2825
+ ,2172
+ ,2
+ ,2155
+ ,3016
+ ,2333
+ ,2355
+ ,2150
+ ,2
+ ,2172
+ ,2155
+ ,3016
+ ,2333
+ ,2533
+ ,2
+ ,2150
+ ,2172
+ ,2155
+ ,3016
+ ,2058
+ ,2
+ ,2533
+ ,2150
+ ,2172
+ ,2155
+ ,2160
+ ,2
+ ,2058
+ ,2533
+ ,2150
+ ,2172
+ ,2260
+ ,2
+ ,2160
+ ,2058
+ ,2533
+ ,2150
+ ,2498
+ ,2
+ ,2260
+ ,2160
+ ,2058
+ ,2533
+ ,2695
+ ,2
+ ,2498
+ ,2260
+ ,2160
+ ,2058
+ ,2799
+ ,2
+ ,2695
+ ,2498
+ ,2260
+ ,2160
+ ,2947
+ ,2
+ ,2799
+ ,2695
+ ,2498
+ ,2260
+ ,2930
+ ,2
+ ,2947
+ ,2799
+ ,2695
+ ,2498
+ ,2318
+ ,2
+ ,2930
+ ,2947
+ ,2799
+ ,2695
+ ,2540
+ ,2
+ ,2318
+ ,2930
+ ,2947
+ ,2799
+ ,2570
+ ,2
+ ,2540
+ ,2318
+ ,2930
+ ,2947
+ ,2669
+ ,2
+ ,2570
+ ,2540
+ ,2318
+ ,2930
+ ,2450
+ ,2
+ ,2669
+ ,2570
+ ,2540
+ ,2318
+ ,2842
+ ,2
+ ,2450
+ ,2669
+ ,2570
+ ,2540
+ ,3440
+ ,2
+ ,2842
+ ,2450
+ ,2669
+ ,2570
+ ,2678
+ ,2
+ ,3440
+ ,2842
+ ,2450
+ ,2669
+ ,2981
+ ,2
+ ,2678
+ ,3440
+ ,2842
+ ,2450
+ ,2260
+ ,2.21
+ ,2981
+ ,2678
+ ,3440
+ ,2842
+ ,2844
+ ,2.25
+ ,2260
+ ,2981
+ ,2678
+ ,3440
+ ,2546
+ ,2.25
+ ,2844
+ ,2260
+ ,2981
+ ,2678
+ ,2456
+ ,2.45
+ ,2546
+ ,2844
+ ,2260
+ ,2981
+ ,2295
+ ,2.5
+ ,2456
+ ,2546
+ ,2844
+ ,2260
+ ,2379
+ ,2.5
+ ,2295
+ ,2456
+ ,2546
+ ,2844
+ ,2479
+ ,2.64
+ ,2379
+ ,2295
+ ,2456
+ ,2546
+ ,2057
+ ,2.75
+ ,2479
+ ,2379
+ ,2295
+ ,2456
+ ,2280
+ ,2.93
+ ,2057
+ ,2479
+ ,2379
+ ,2295
+ ,2351
+ ,3
+ ,2280
+ ,2057
+ ,2479
+ ,2379
+ ,2276
+ ,3.17
+ ,2351
+ ,2280
+ ,2057
+ ,2479
+ ,2548
+ ,3.25
+ ,2276
+ ,2351
+ ,2280
+ ,2057
+ ,2311
+ ,3.39
+ ,2548
+ ,2276
+ ,2351
+ ,2280
+ ,2201
+ ,3.5
+ ,2311
+ ,2548
+ ,2276
+ ,2351
+ ,2725
+ ,3.5
+ ,2201
+ ,2311
+ ,2548
+ ,2276
+ ,2408
+ ,3.65
+ ,2725
+ ,2201
+ ,2311
+ ,2548
+ ,2139
+ ,3.75
+ ,2408
+ ,2725
+ ,2201
+ ,2311
+ ,1898
+ ,3.75
+ ,2139
+ ,2408
+ ,2725
+ ,2201
+ ,2537
+ ,3.9
+ ,1898
+ ,2139
+ ,2408
+ ,2725
+ ,2069
+ ,4
+ ,2537
+ ,1898
+ ,2139
+ ,2408
+ ,2063
+ ,4
+ ,2069
+ ,2537
+ ,1898
+ ,2139
+ ,2524
+ ,4
+ ,2063
+ ,2069
+ ,2537
+ ,1898
+ ,2437
+ ,4
+ ,2524
+ ,2063
+ ,2069
+ ,2537
+ ,2189
+ ,4
+ ,2437
+ ,2524
+ ,2063
+ ,2069
+ ,2793
+ ,4
+ ,2189
+ ,2437
+ ,2524
+ ,2063
+ ,2074
+ ,4
+ ,2793
+ ,2189
+ ,2437
+ ,2524
+ ,2622
+ ,4
+ ,2074
+ ,2793
+ ,2189
+ ,2437
+ ,2278
+ ,4
+ ,2622
+ ,2074
+ ,2793
+ ,2189
+ ,2144
+ ,4
+ ,2278
+ ,2622
+ ,2074
+ ,2793
+ ,2427
+ ,4
+ ,2144
+ ,2278
+ ,2622
+ ,2074
+ ,2139
+ ,4
+ ,2427
+ ,2144
+ ,2278
+ ,2622
+ ,1828
+ ,4.18
+ ,2139
+ ,2427
+ ,2144
+ ,2278
+ ,2072
+ ,4.25
+ ,1828
+ ,2139
+ ,2427
+ ,2144
+ ,1800
+ ,4.25
+ ,2072
+ ,1828
+ ,2139
+ ,2427)
+ ,dim=c(6
+ ,61)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:61))
> y <- array(NA,dim=c(6,61),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:61))
> 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 2360 2.00 2267 1746 2069 2299 1 0 0 0 0 0 0 0 0 0 0 1
2 2214 2.00 2360 2267 1746 2069 0 1 0 0 0 0 0 0 0 0 0 2
3 2825 2.00 2214 2360 2267 1746 0 0 1 0 0 0 0 0 0 0 0 3
4 2355 2.00 2825 2214 2360 2267 0 0 0 1 0 0 0 0 0 0 0 4
5 2333 2.00 2355 2825 2214 2360 0 0 0 0 1 0 0 0 0 0 0 5
6 3016 2.00 2333 2355 2825 2214 0 0 0 0 0 1 0 0 0 0 0 6
7 2155 2.00 3016 2333 2355 2825 0 0 0 0 0 0 1 0 0 0 0 7
8 2172 2.00 2155 3016 2333 2355 0 0 0 0 0 0 0 1 0 0 0 8
9 2150 2.00 2172 2155 3016 2333 0 0 0 0 0 0 0 0 1 0 0 9
10 2533 2.00 2150 2172 2155 3016 0 0 0 0 0 0 0 0 0 1 0 10
11 2058 2.00 2533 2150 2172 2155 0 0 0 0 0 0 0 0 0 0 1 11
12 2160 2.00 2058 2533 2150 2172 0 0 0 0 0 0 0 0 0 0 0 12
13 2260 2.00 2160 2058 2533 2150 1 0 0 0 0 0 0 0 0 0 0 13
14 2498 2.00 2260 2160 2058 2533 0 1 0 0 0 0 0 0 0 0 0 14
15 2695 2.00 2498 2260 2160 2058 0 0 1 0 0 0 0 0 0 0 0 15
16 2799 2.00 2695 2498 2260 2160 0 0 0 1 0 0 0 0 0 0 0 16
17 2947 2.00 2799 2695 2498 2260 0 0 0 0 1 0 0 0 0 0 0 17
18 2930 2.00 2947 2799 2695 2498 0 0 0 0 0 1 0 0 0 0 0 18
19 2318 2.00 2930 2947 2799 2695 0 0 0 0 0 0 1 0 0 0 0 19
20 2540 2.00 2318 2930 2947 2799 0 0 0 0 0 0 0 1 0 0 0 20
21 2570 2.00 2540 2318 2930 2947 0 0 0 0 0 0 0 0 1 0 0 21
22 2669 2.00 2570 2540 2318 2930 0 0 0 0 0 0 0 0 0 1 0 22
23 2450 2.00 2669 2570 2540 2318 0 0 0 0 0 0 0 0 0 0 1 23
24 2842 2.00 2450 2669 2570 2540 0 0 0 0 0 0 0 0 0 0 0 24
25 3440 2.00 2842 2450 2669 2570 1 0 0 0 0 0 0 0 0 0 0 25
26 2678 2.00 3440 2842 2450 2669 0 1 0 0 0 0 0 0 0 0 0 26
27 2981 2.00 2678 3440 2842 2450 0 0 1 0 0 0 0 0 0 0 0 27
28 2260 2.21 2981 2678 3440 2842 0 0 0 1 0 0 0 0 0 0 0 28
29 2844 2.25 2260 2981 2678 3440 0 0 0 0 1 0 0 0 0 0 0 29
30 2546 2.25 2844 2260 2981 2678 0 0 0 0 0 1 0 0 0 0 0 30
31 2456 2.45 2546 2844 2260 2981 0 0 0 0 0 0 1 0 0 0 0 31
32 2295 2.50 2456 2546 2844 2260 0 0 0 0 0 0 0 1 0 0 0 32
33 2379 2.50 2295 2456 2546 2844 0 0 0 0 0 0 0 0 1 0 0 33
34 2479 2.64 2379 2295 2456 2546 0 0 0 0 0 0 0 0 0 1 0 34
35 2057 2.75 2479 2379 2295 2456 0 0 0 0 0 0 0 0 0 0 1 35
36 2280 2.93 2057 2479 2379 2295 0 0 0 0 0 0 0 0 0 0 0 36
37 2351 3.00 2280 2057 2479 2379 1 0 0 0 0 0 0 0 0 0 0 37
38 2276 3.17 2351 2280 2057 2479 0 1 0 0 0 0 0 0 0 0 0 38
39 2548 3.25 2276 2351 2280 2057 0 0 1 0 0 0 0 0 0 0 0 39
40 2311 3.39 2548 2276 2351 2280 0 0 0 1 0 0 0 0 0 0 0 40
41 2201 3.50 2311 2548 2276 2351 0 0 0 0 1 0 0 0 0 0 0 41
42 2725 3.50 2201 2311 2548 2276 0 0 0 0 0 1 0 0 0 0 0 42
43 2408 3.65 2725 2201 2311 2548 0 0 0 0 0 0 1 0 0 0 0 43
44 2139 3.75 2408 2725 2201 2311 0 0 0 0 0 0 0 1 0 0 0 44
45 1898 3.75 2139 2408 2725 2201 0 0 0 0 0 0 0 0 1 0 0 45
46 2537 3.90 1898 2139 2408 2725 0 0 0 0 0 0 0 0 0 1 0 46
47 2069 4.00 2537 1898 2139 2408 0 0 0 0 0 0 0 0 0 0 1 47
48 2063 4.00 2069 2537 1898 2139 0 0 0 0 0 0 0 0 0 0 0 48
49 2524 4.00 2063 2069 2537 1898 1 0 0 0 0 0 0 0 0 0 0 49
50 2437 4.00 2524 2063 2069 2537 0 1 0 0 0 0 0 0 0 0 0 50
51 2189 4.00 2437 2524 2063 2069 0 0 1 0 0 0 0 0 0 0 0 51
52 2793 4.00 2189 2437 2524 2063 0 0 0 1 0 0 0 0 0 0 0 52
53 2074 4.00 2793 2189 2437 2524 0 0 0 0 1 0 0 0 0 0 0 53
54 2622 4.00 2074 2793 2189 2437 0 0 0 0 0 1 0 0 0 0 0 54
55 2278 4.00 2622 2074 2793 2189 0 0 0 0 0 0 1 0 0 0 0 55
56 2144 4.00 2278 2622 2074 2793 0 0 0 0 0 0 0 1 0 0 0 56
57 2427 4.00 2144 2278 2622 2074 0 0 0 0 0 0 0 0 1 0 0 57
58 2139 4.00 2427 2144 2278 2622 0 0 0 0 0 0 0 0 0 1 0 58
59 1828 4.18 2139 2427 2144 2278 0 0 0 0 0 0 0 0 0 0 1 59
60 2072 4.25 1828 2139 2427 2144 0 0 0 0 0 0 0 0 0 0 0 60
61 1800 4.25 2072 1828 2139 2427 1 0 0 0 0 0 0 0 0 0 0 61
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
2.544e+03 -3.329e+02 -8.973e-03 1.895e-01 5.896e-02 -1.040e-01
M1 M2 M3 M4 M5 M6
2.549e+02 1.804e+02 2.958e+02 2.076e+02 1.756e+02 4.489e+02
M7 M8 M9 M10 M11 t
5.544e+01 -8.282e+01 -2.929e+00 2.606e+02 -1.494e+02 1.113e+01
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-464.74 -149.33 -26.69 105.08 699.87
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.544e+03 1.052e+03 2.418 0.0199 *
X -3.329e+02 1.915e+02 -1.738 0.0893 .
Y1 -8.973e-03 1.659e-01 -0.054 0.9571
Y2 1.895e-01 1.671e-01 1.134 0.2632
Y3 5.896e-02 1.669e-01 0.353 0.7255
Y4 -1.040e-01 1.641e-01 -0.634 0.5297
M1 2.549e+02 1.715e+02 1.486 0.1446
M2 1.804e+02 1.883e+02 0.958 0.3434
M3 2.958e+02 1.725e+02 1.715 0.0935 .
M4 2.076e+02 1.908e+02 1.088 0.2827
M5 1.756e+02 1.877e+02 0.936 0.3546
M6 4.489e+02 1.821e+02 2.465 0.0178 *
M7 5.544e+01 2.082e+02 0.266 0.7913
M8 -8.282e+01 1.795e+02 -0.461 0.6468
M9 -2.929e+00 1.834e+02 -0.016 0.9873
M10 2.606e+02 1.860e+02 1.401 0.1684
M11 -1.494e+02 1.739e+02 -0.859 0.3950
t 1.113e+01 8.574e+00 1.299 0.2010
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 252.4 on 43 degrees of freedom
Multiple R-squared: 0.5502, Adjusted R-squared: 0.3724
F-statistic: 3.095 on 17 and 43 DF, p-value: 0.001396
> 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,] 0.6087574 0.7824852 0.3912426
[2,] 0.4323827 0.8647655 0.5676173
[3,] 0.3247432 0.6494864 0.6752568
[4,] 0.3129030 0.6258061 0.6870970
[5,] 0.7602063 0.4795875 0.2397937
[6,] 0.8068330 0.3863340 0.1931670
[7,] 0.8111059 0.3777882 0.1888941
[8,] 0.7969711 0.4060578 0.2030289
[9,] 0.8268692 0.3462616 0.1731308
[10,] 0.7762323 0.4475355 0.2237677
[11,] 0.8149783 0.3700434 0.1850217
[12,] 0.7583416 0.4833168 0.2416584
[13,] 0.7022344 0.5955311 0.2977656
[14,] 0.5998461 0.8003079 0.4001539
[15,] 0.4814746 0.9629491 0.5185254
[16,] 0.3867794 0.7735588 0.6132206
[17,] 0.4109129 0.8218258 0.5890871
[18,] 0.2996265 0.5992530 0.7003735
[19,] 0.2929591 0.5859182 0.7070409
[20,] 0.1770051 0.3540101 0.8229949
> postscript(file="/var/www/html/rcomp/tmp/1fv591258654864.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2pidr1258654864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3hjmx1258654864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4hmq91258654864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5uoyk1258654864.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 = 61
Frequency = 1
1 2 3 4 5 6
22.5316173 -162.8523334 238.3944775 -72.6614526 -175.5628181 260.6934927
7 8 9 10 11 12
-116.4636894 -157.0116663 -149.3291970 77.3936773 -81.6607038 -213.9718240
13 14 15 16 17 18
-314.0024484 36.7415486 35.0129124 177.5242507 306.2922262 -0.3439045
19 20 21 22 23 24
-243.8697382 105.0774492 178.3717952 -4.7242025 93.6178793 325.6521775
25 26 27 28 29 30
699.8748254 -44.4709085 -34.0076796 -455.4115573 205.9173781 -331.7092223
31 32 33 34 35 36
-12.1234494 -83.0813967 3.7734815 -118.6674847 -120.0876247 -42.1480270
37 38 39 40 41 42
-129.1287687 -90.5270425 10.4330178 -67.1966118 -161.6424282 98.0509953
43 44 45 46 47 48
281.0889754 52.2397148 -264.4787685 271.7860318 270.2169798 -35.3481752
49 50 51 52 53 54
185.4660278 261.1087359 -249.8327281 417.7453710 -175.0043580 -26.6913611
55 56 57 58 59 60
91.3679016 82.7758990 231.6626888 -225.7880219 -162.0865307 -34.1841513
61
-464.7412534
> postscript(file="/var/www/html/rcomp/tmp/6ofzy1258654864.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 = 61
Frequency = 1
lag(myerror, k = 1) myerror
0 22.5316173 NA
1 -162.8523334 22.5316173
2 238.3944775 -162.8523334
3 -72.6614526 238.3944775
4 -175.5628181 -72.6614526
5 260.6934927 -175.5628181
6 -116.4636894 260.6934927
7 -157.0116663 -116.4636894
8 -149.3291970 -157.0116663
9 77.3936773 -149.3291970
10 -81.6607038 77.3936773
11 -213.9718240 -81.6607038
12 -314.0024484 -213.9718240
13 36.7415486 -314.0024484
14 35.0129124 36.7415486
15 177.5242507 35.0129124
16 306.2922262 177.5242507
17 -0.3439045 306.2922262
18 -243.8697382 -0.3439045
19 105.0774492 -243.8697382
20 178.3717952 105.0774492
21 -4.7242025 178.3717952
22 93.6178793 -4.7242025
23 325.6521775 93.6178793
24 699.8748254 325.6521775
25 -44.4709085 699.8748254
26 -34.0076796 -44.4709085
27 -455.4115573 -34.0076796
28 205.9173781 -455.4115573
29 -331.7092223 205.9173781
30 -12.1234494 -331.7092223
31 -83.0813967 -12.1234494
32 3.7734815 -83.0813967
33 -118.6674847 3.7734815
34 -120.0876247 -118.6674847
35 -42.1480270 -120.0876247
36 -129.1287687 -42.1480270
37 -90.5270425 -129.1287687
38 10.4330178 -90.5270425
39 -67.1966118 10.4330178
40 -161.6424282 -67.1966118
41 98.0509953 -161.6424282
42 281.0889754 98.0509953
43 52.2397148 281.0889754
44 -264.4787685 52.2397148
45 271.7860318 -264.4787685
46 270.2169798 271.7860318
47 -35.3481752 270.2169798
48 185.4660278 -35.3481752
49 261.1087359 185.4660278
50 -249.8327281 261.1087359
51 417.7453710 -249.8327281
52 -175.0043580 417.7453710
53 -26.6913611 -175.0043580
54 91.3679016 -26.6913611
55 82.7758990 91.3679016
56 231.6626888 82.7758990
57 -225.7880219 231.6626888
58 -162.0865307 -225.7880219
59 -34.1841513 -162.0865307
60 -464.7412534 -34.1841513
61 NA -464.7412534
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -162.8523334 22.5316173
[2,] 238.3944775 -162.8523334
[3,] -72.6614526 238.3944775
[4,] -175.5628181 -72.6614526
[5,] 260.6934927 -175.5628181
[6,] -116.4636894 260.6934927
[7,] -157.0116663 -116.4636894
[8,] -149.3291970 -157.0116663
[9,] 77.3936773 -149.3291970
[10,] -81.6607038 77.3936773
[11,] -213.9718240 -81.6607038
[12,] -314.0024484 -213.9718240
[13,] 36.7415486 -314.0024484
[14,] 35.0129124 36.7415486
[15,] 177.5242507 35.0129124
[16,] 306.2922262 177.5242507
[17,] -0.3439045 306.2922262
[18,] -243.8697382 -0.3439045
[19,] 105.0774492 -243.8697382
[20,] 178.3717952 105.0774492
[21,] -4.7242025 178.3717952
[22,] 93.6178793 -4.7242025
[23,] 325.6521775 93.6178793
[24,] 699.8748254 325.6521775
[25,] -44.4709085 699.8748254
[26,] -34.0076796 -44.4709085
[27,] -455.4115573 -34.0076796
[28,] 205.9173781 -455.4115573
[29,] -331.7092223 205.9173781
[30,] -12.1234494 -331.7092223
[31,] -83.0813967 -12.1234494
[32,] 3.7734815 -83.0813967
[33,] -118.6674847 3.7734815
[34,] -120.0876247 -118.6674847
[35,] -42.1480270 -120.0876247
[36,] -129.1287687 -42.1480270
[37,] -90.5270425 -129.1287687
[38,] 10.4330178 -90.5270425
[39,] -67.1966118 10.4330178
[40,] -161.6424282 -67.1966118
[41,] 98.0509953 -161.6424282
[42,] 281.0889754 98.0509953
[43,] 52.2397148 281.0889754
[44,] -264.4787685 52.2397148
[45,] 271.7860318 -264.4787685
[46,] 270.2169798 271.7860318
[47,] -35.3481752 270.2169798
[48,] 185.4660278 -35.3481752
[49,] 261.1087359 185.4660278
[50,] -249.8327281 261.1087359
[51,] 417.7453710 -249.8327281
[52,] -175.0043580 417.7453710
[53,] -26.6913611 -175.0043580
[54,] 91.3679016 -26.6913611
[55,] 82.7758990 91.3679016
[56,] 231.6626888 82.7758990
[57,] -225.7880219 231.6626888
[58,] -162.0865307 -225.7880219
[59,] -34.1841513 -162.0865307
[60,] -464.7412534 -34.1841513
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -162.8523334 22.5316173
2 238.3944775 -162.8523334
3 -72.6614526 238.3944775
4 -175.5628181 -72.6614526
5 260.6934927 -175.5628181
6 -116.4636894 260.6934927
7 -157.0116663 -116.4636894
8 -149.3291970 -157.0116663
9 77.3936773 -149.3291970
10 -81.6607038 77.3936773
11 -213.9718240 -81.6607038
12 -314.0024484 -213.9718240
13 36.7415486 -314.0024484
14 35.0129124 36.7415486
15 177.5242507 35.0129124
16 306.2922262 177.5242507
17 -0.3439045 306.2922262
18 -243.8697382 -0.3439045
19 105.0774492 -243.8697382
20 178.3717952 105.0774492
21 -4.7242025 178.3717952
22 93.6178793 -4.7242025
23 325.6521775 93.6178793
24 699.8748254 325.6521775
25 -44.4709085 699.8748254
26 -34.0076796 -44.4709085
27 -455.4115573 -34.0076796
28 205.9173781 -455.4115573
29 -331.7092223 205.9173781
30 -12.1234494 -331.7092223
31 -83.0813967 -12.1234494
32 3.7734815 -83.0813967
33 -118.6674847 3.7734815
34 -120.0876247 -118.6674847
35 -42.1480270 -120.0876247
36 -129.1287687 -42.1480270
37 -90.5270425 -129.1287687
38 10.4330178 -90.5270425
39 -67.1966118 10.4330178
40 -161.6424282 -67.1966118
41 98.0509953 -161.6424282
42 281.0889754 98.0509953
43 52.2397148 281.0889754
44 -264.4787685 52.2397148
45 271.7860318 -264.4787685
46 270.2169798 271.7860318
47 -35.3481752 270.2169798
48 185.4660278 -35.3481752
49 261.1087359 185.4660278
50 -249.8327281 261.1087359
51 417.7453710 -249.8327281
52 -175.0043580 417.7453710
53 -26.6913611 -175.0043580
54 91.3679016 -26.6913611
55 82.7758990 91.3679016
56 231.6626888 82.7758990
57 -225.7880219 231.6626888
58 -162.0865307 -225.7880219
59 -34.1841513 -162.0865307
60 -464.7412534 -34.1841513
> 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/7y1lo1258654864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/85i2a1258654864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9t7se1258654864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ngtj1258654864.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11hpg31258654864.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/12f3qp1258654864.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/13fzid1258654864.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/14rrm81258654865.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/15iwhl1258654865.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/16jxvo1258654865.tab")
+ }
> system("convert tmp/1fv591258654864.ps tmp/1fv591258654864.png")
> system("convert tmp/2pidr1258654864.ps tmp/2pidr1258654864.png")
> system("convert tmp/3hjmx1258654864.ps tmp/3hjmx1258654864.png")
> system("convert tmp/4hmq91258654864.ps tmp/4hmq91258654864.png")
> system("convert tmp/5uoyk1258654864.ps tmp/5uoyk1258654864.png")
> system("convert tmp/6ofzy1258654864.ps tmp/6ofzy1258654864.png")
> system("convert tmp/7y1lo1258654864.ps tmp/7y1lo1258654864.png")
> system("convert tmp/85i2a1258654864.ps tmp/85i2a1258654864.png")
> system("convert tmp/9t7se1258654864.ps tmp/9t7se1258654864.png")
> system("convert tmp/10ngtj1258654864.ps tmp/10ngtj1258654864.png")
>
>
> proc.time()
user system elapsed
2.407 1.550 2.809