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(1852
+ ,18.2
+ ,2187
+ ,1855
+ ,2218
+ ,2253
+ ,1570
+ ,18
+ ,1852
+ ,2187
+ ,1855
+ ,2218
+ ,1851
+ ,19
+ ,1570
+ ,1852
+ ,2187
+ ,1855
+ ,1954
+ ,20.7
+ ,1851
+ ,1570
+ ,1852
+ ,2187
+ ,1828
+ ,21.2
+ ,1954
+ ,1851
+ ,1570
+ ,1852
+ ,2251
+ ,20.7
+ ,1828
+ ,1954
+ ,1851
+ ,1570
+ ,2277
+ ,19.6
+ ,2251
+ ,1828
+ ,1954
+ ,1851
+ ,2085
+ ,18.6
+ ,2277
+ ,2251
+ ,1828
+ ,1954
+ ,2282
+ ,18.7
+ ,2085
+ ,2277
+ ,2251
+ ,1828
+ ,2266
+ ,23.8
+ ,2282
+ ,2085
+ ,2277
+ ,2251
+ ,1878
+ ,24.9
+ ,2266
+ ,2282
+ ,2085
+ ,2277
+ ,2267
+ ,24.8
+ ,1878
+ ,2266
+ ,2282
+ ,2085
+ ,2069
+ ,23.8
+ ,2267
+ ,1878
+ ,2266
+ ,2282
+ ,1746
+ ,22.3
+ ,2069
+ ,2267
+ ,1878
+ ,2266
+ ,2299
+ ,21.7
+ ,1746
+ ,2069
+ ,2267
+ ,1878
+ ,2360
+ ,20.7
+ ,2299
+ ,1746
+ ,2069
+ ,2267
+ ,2214
+ ,19.7
+ ,2360
+ ,2299
+ ,1746
+ ,2069
+ ,2825
+ ,18.4
+ ,2214
+ ,2360
+ ,2299
+ ,1746
+ ,2355
+ ,17.4
+ ,2825
+ ,2214
+ ,2360
+ ,2299
+ ,2333
+ ,17
+ ,2355
+ ,2825
+ ,2214
+ ,2360
+ ,3016
+ ,18
+ ,2333
+ ,2355
+ ,2825
+ ,2214
+ ,2155
+ ,23.8
+ ,3016
+ ,2333
+ ,2355
+ ,2825
+ ,2172
+ ,25.5
+ ,2155
+ ,3016
+ ,2333
+ ,2355
+ ,2150
+ ,25.6
+ ,2172
+ ,2155
+ ,3016
+ ,2333
+ ,2533
+ ,23.7
+ ,2150
+ ,2172
+ ,2155
+ ,3016
+ ,2058
+ ,22
+ ,2533
+ ,2150
+ ,2172
+ ,2155
+ ,2160
+ ,21.3
+ ,2058
+ ,2533
+ ,2150
+ ,2172
+ ,2260
+ ,20.7
+ ,2160
+ ,2058
+ ,2533
+ ,2150
+ ,2498
+ ,20.4
+ ,2260
+ ,2160
+ ,2058
+ ,2533
+ ,2695
+ ,20.3
+ ,2498
+ ,2260
+ ,2160
+ ,2058
+ ,2799
+ ,20.4
+ ,2695
+ ,2498
+ ,2260
+ ,2160
+ ,2946
+ ,19.8
+ ,2799
+ ,2695
+ ,2498
+ ,2260
+ ,2930
+ ,19.5
+ ,2946
+ ,2799
+ ,2695
+ ,2498
+ ,2318
+ ,23.1
+ ,2930
+ ,2946
+ ,2799
+ ,2695
+ ,2540
+ ,23.5
+ ,2318
+ ,2930
+ ,2946
+ ,2799
+ ,2570
+ ,23.5
+ ,2540
+ ,2318
+ ,2930
+ ,2946
+ ,2669
+ ,22.9
+ ,2570
+ ,2540
+ ,2318
+ ,2930
+ ,2450
+ ,21.9
+ ,2669
+ ,2570
+ ,2540
+ ,2318
+ ,2842
+ ,21.5
+ ,2450
+ ,2669
+ ,2570
+ ,2540
+ ,3440
+ ,20.5
+ ,2842
+ ,2450
+ ,2669
+ ,2570
+ ,2678
+ ,20.2
+ ,3440
+ ,2842
+ ,2450
+ ,2669
+ ,2981
+ ,19.4
+ ,2678
+ ,3440
+ ,2842
+ ,2450
+ ,2260
+ ,19.2
+ ,2981
+ ,2678
+ ,3440
+ ,2842
+ ,2844
+ ,18.8
+ ,2260
+ ,2981
+ ,2678
+ ,3440
+ ,2546
+ ,18.8
+ ,2844
+ ,2260
+ ,2981
+ ,2678
+ ,2456
+ ,22.6
+ ,2546
+ ,2844
+ ,2260
+ ,2981
+ ,2295
+ ,23.3
+ ,2456
+ ,2546
+ ,2844
+ ,2260
+ ,2379
+ ,23
+ ,2295
+ ,2456
+ ,2546
+ ,2844
+ ,2479
+ ,21.4
+ ,2379
+ ,2295
+ ,2456
+ ,2546
+ ,2057
+ ,19.9
+ ,2479
+ ,2379
+ ,2295
+ ,2456
+ ,2280
+ ,18.8
+ ,2057
+ ,2479
+ ,2379
+ ,2295
+ ,2351
+ ,18.6
+ ,2280
+ ,2057
+ ,2479
+ ,2379
+ ,2276
+ ,18.4
+ ,2351
+ ,2280
+ ,2057
+ ,2479
+ ,2548
+ ,18.6
+ ,2276
+ ,2351
+ ,2280
+ ,2057
+ ,2311
+ ,19.9
+ ,2548
+ ,2276
+ ,2351
+ ,2280
+ ,2201
+ ,19.2
+ ,2311
+ ,2548
+ ,2276
+ ,2351
+ ,2725
+ ,18.4
+ ,2201
+ ,2311
+ ,2548
+ ,2276)
+ ,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 1852 18.2 2187 1855 2218 2253 1 0 0 0 0 0 0 0 0 0 0 1
2 1570 18.0 1852 2187 1855 2218 0 1 0 0 0 0 0 0 0 0 0 2
3 1851 19.0 1570 1852 2187 1855 0 0 1 0 0 0 0 0 0 0 0 3
4 1954 20.7 1851 1570 1852 2187 0 0 0 1 0 0 0 0 0 0 0 4
5 1828 21.2 1954 1851 1570 1852 0 0 0 0 1 0 0 0 0 0 0 5
6 2251 20.7 1828 1954 1851 1570 0 0 0 0 0 1 0 0 0 0 0 6
7 2277 19.6 2251 1828 1954 1851 0 0 0 0 0 0 1 0 0 0 0 7
8 2085 18.6 2277 2251 1828 1954 0 0 0 0 0 0 0 1 0 0 0 8
9 2282 18.7 2085 2277 2251 1828 0 0 0 0 0 0 0 0 1 0 0 9
10 2266 23.8 2282 2085 2277 2251 0 0 0 0 0 0 0 0 0 1 0 10
11 1878 24.9 2266 2282 2085 2277 0 0 0 0 0 0 0 0 0 0 1 11
12 2267 24.8 1878 2266 2282 2085 0 0 0 0 0 0 0 0 0 0 0 12
13 2069 23.8 2267 1878 2266 2282 1 0 0 0 0 0 0 0 0 0 0 13
14 1746 22.3 2069 2267 1878 2266 0 1 0 0 0 0 0 0 0 0 0 14
15 2299 21.7 1746 2069 2267 1878 0 0 1 0 0 0 0 0 0 0 0 15
16 2360 20.7 2299 1746 2069 2267 0 0 0 1 0 0 0 0 0 0 0 16
17 2214 19.7 2360 2299 1746 2069 0 0 0 0 1 0 0 0 0 0 0 17
18 2825 18.4 2214 2360 2299 1746 0 0 0 0 0 1 0 0 0 0 0 18
19 2355 17.4 2825 2214 2360 2299 0 0 0 0 0 0 1 0 0 0 0 19
20 2333 17.0 2355 2825 2214 2360 0 0 0 0 0 0 0 1 0 0 0 20
21 3016 18.0 2333 2355 2825 2214 0 0 0 0 0 0 0 0 1 0 0 21
22 2155 23.8 3016 2333 2355 2825 0 0 0 0 0 0 0 0 0 1 0 22
23 2172 25.5 2155 3016 2333 2355 0 0 0 0 0 0 0 0 0 0 1 23
24 2150 25.6 2172 2155 3016 2333 0 0 0 0 0 0 0 0 0 0 0 24
25 2533 23.7 2150 2172 2155 3016 1 0 0 0 0 0 0 0 0 0 0 25
26 2058 22.0 2533 2150 2172 2155 0 1 0 0 0 0 0 0 0 0 0 26
27 2160 21.3 2058 2533 2150 2172 0 0 1 0 0 0 0 0 0 0 0 27
28 2260 20.7 2160 2058 2533 2150 0 0 0 1 0 0 0 0 0 0 0 28
29 2498 20.4 2260 2160 2058 2533 0 0 0 0 1 0 0 0 0 0 0 29
30 2695 20.3 2498 2260 2160 2058 0 0 0 0 0 1 0 0 0 0 0 30
31 2799 20.4 2695 2498 2260 2160 0 0 0 0 0 0 1 0 0 0 0 31
32 2946 19.8 2799 2695 2498 2260 0 0 0 0 0 0 0 1 0 0 0 32
33 2930 19.5 2946 2799 2695 2498 0 0 0 0 0 0 0 0 1 0 0 33
34 2318 23.1 2930 2946 2799 2695 0 0 0 0 0 0 0 0 0 1 0 34
35 2540 23.5 2318 2930 2946 2799 0 0 0 0 0 0 0 0 0 0 1 35
36 2570 23.5 2540 2318 2930 2946 0 0 0 0 0 0 0 0 0 0 0 36
37 2669 22.9 2570 2540 2318 2930 1 0 0 0 0 0 0 0 0 0 0 37
38 2450 21.9 2669 2570 2540 2318 0 1 0 0 0 0 0 0 0 0 0 38
39 2842 21.5 2450 2669 2570 2540 0 0 1 0 0 0 0 0 0 0 0 39
40 3440 20.5 2842 2450 2669 2570 0 0 0 1 0 0 0 0 0 0 0 40
41 2678 20.2 3440 2842 2450 2669 0 0 0 0 1 0 0 0 0 0 0 41
42 2981 19.4 2678 3440 2842 2450 0 0 0 0 0 1 0 0 0 0 0 42
43 2260 19.2 2981 2678 3440 2842 0 0 0 0 0 0 1 0 0 0 0 43
44 2844 18.8 2260 2981 2678 3440 0 0 0 0 0 0 0 1 0 0 0 44
45 2546 18.8 2844 2260 2981 2678 0 0 0 0 0 0 0 0 1 0 0 45
46 2456 22.6 2546 2844 2260 2981 0 0 0 0 0 0 0 0 0 1 0 46
47 2295 23.3 2456 2546 2844 2260 0 0 0 0 0 0 0 0 0 0 1 47
48 2379 23.0 2295 2456 2546 2844 0 0 0 0 0 0 0 0 0 0 0 48
49 2479 21.4 2379 2295 2456 2546 1 0 0 0 0 0 0 0 0 0 0 49
50 2057 19.9 2479 2379 2295 2456 0 1 0 0 0 0 0 0 0 0 0 50
51 2280 18.8 2057 2479 2379 2295 0 0 1 0 0 0 0 0 0 0 0 51
52 2351 18.6 2280 2057 2479 2379 0 0 0 1 0 0 0 0 0 0 0 52
53 2276 18.4 2351 2280 2057 2479 0 0 0 0 1 0 0 0 0 0 0 53
54 2548 18.6 2276 2351 2280 2057 0 0 0 0 0 1 0 0 0 0 0 54
55 2311 19.9 2548 2276 2351 2280 0 0 0 0 0 0 1 0 0 0 0 55
56 2201 19.2 2311 2548 2276 2351 0 0 0 0 0 0 0 1 0 0 0 56
57 2725 18.4 2201 2311 2548 2276 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
-521.12504 43.92473 0.26761 0.35365 0.04248 0.08787
M1 M2 M3 M4 M5 M6
127.55180 -192.61394 225.21262 443.73510 133.32615 512.43119
M7 M8 M9 M10 M11 t
188.75016 228.36932 514.60558 -216.10345 -264.76807 1.75132
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-466.92 -151.78 -23.89 113.07 580.72
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -521.12504 784.36378 -0.664 0.5103
X 43.92473 28.00947 1.568 0.1249
Y1 0.26761 0.15759 1.698 0.0974 .
Y2 0.35365 0.16571 2.134 0.0392 *
Y3 0.04248 0.16676 0.255 0.8003
Y4 0.08787 0.16145 0.544 0.5894
M1 127.55180 191.76934 0.665 0.5099
M2 -192.61394 216.30964 -0.890 0.3787
M3 225.21262 206.89073 1.089 0.2830
M4 443.73510 212.27328 2.090 0.0431 *
M5 133.32615 252.33025 0.528 0.6002
M6 512.43119 246.67126 2.077 0.0444 *
M7 188.75016 241.79160 0.781 0.4397
M8 228.36932 254.53488 0.897 0.3751
M9 514.60558 236.68530 2.174 0.0358 *
M10 -216.10345 201.71932 -1.071 0.2906
M11 -264.76807 185.60999 -1.426 0.1617
t 1.75132 2.68830 0.651 0.5186
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 236.8 on 39 degrees of freedom
Multiple R-squared: 0.6885, Adjusted R-squared: 0.5527
F-statistic: 5.07 on 17 and 39 DF, p-value: 1.382e-05
> 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,] 0.034820665 0.06964133 0.9651793
[2,] 0.015773029 0.03154606 0.9842270
[3,] 0.008660329 0.01732066 0.9913397
[4,] 0.061871243 0.12374249 0.9381288
[5,] 0.066061588 0.13212318 0.9339384
[6,] 0.083984359 0.16796872 0.9160156
[7,] 0.161759278 0.32351856 0.8382407
[8,] 0.483453700 0.96690740 0.5165463
[9,] 0.381526812 0.76305362 0.6184732
[10,] 0.367802762 0.73560552 0.6321972
[11,] 0.266823537 0.53364707 0.7331765
[12,] 0.423011514 0.84602303 0.5769885
[13,] 0.304326357 0.60865271 0.6956736
[14,] 0.221128256 0.44225651 0.7788717
[15,] 0.129905006 0.25981001 0.8700950
[16,] 0.082614414 0.16522883 0.9173856
> postscript(file="/var/www/html/rcomp/tmp/1ac0s1258741239.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/20slx1258741239.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/316m01258741239.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4mdct1258741239.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5xhyx1258741239.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
-89.051801 -53.120949 -23.893153 -206.250212 -131.080610 -56.839317
7 8 9 10 11 12
241.704072 -107.990477 -168.080725 297.771162 -151.148769 93.716902
13 14 15 16 17 18
-173.175559 -178.570258 155.234885 -19.642572 6.165578 315.801187
19 20 21 22 23 24
48.599482 -86.662339 423.402831 -172.120852 -151.779434 -171.827933
25 26 27 28 29 30
141.760689 40.063340 -255.659718 -223.227228 260.298484 19.182647
31 32 33 34 35 36
290.623366 306.212401 -89.994899 -200.597473 204.798366 113.065621
37 38 39 40 41 42
49.980114 200.560564 193.367294 580.723748 -157.496870 -205.185303
43 44 45 46 47 48
-466.919875 158.892432 -274.315241 74.947163 98.129837 -34.954590
49 50 51 52 53 54
70.486557 -8.932697 -69.049308 -131.603736 22.113419 -72.959213
55 56 57
-114.007045 -270.452017 108.988034
> postscript(file="/var/www/html/rcomp/tmp/6cd0i1258741239.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 -89.051801 NA
1 -53.120949 -89.051801
2 -23.893153 -53.120949
3 -206.250212 -23.893153
4 -131.080610 -206.250212
5 -56.839317 -131.080610
6 241.704072 -56.839317
7 -107.990477 241.704072
8 -168.080725 -107.990477
9 297.771162 -168.080725
10 -151.148769 297.771162
11 93.716902 -151.148769
12 -173.175559 93.716902
13 -178.570258 -173.175559
14 155.234885 -178.570258
15 -19.642572 155.234885
16 6.165578 -19.642572
17 315.801187 6.165578
18 48.599482 315.801187
19 -86.662339 48.599482
20 423.402831 -86.662339
21 -172.120852 423.402831
22 -151.779434 -172.120852
23 -171.827933 -151.779434
24 141.760689 -171.827933
25 40.063340 141.760689
26 -255.659718 40.063340
27 -223.227228 -255.659718
28 260.298484 -223.227228
29 19.182647 260.298484
30 290.623366 19.182647
31 306.212401 290.623366
32 -89.994899 306.212401
33 -200.597473 -89.994899
34 204.798366 -200.597473
35 113.065621 204.798366
36 49.980114 113.065621
37 200.560564 49.980114
38 193.367294 200.560564
39 580.723748 193.367294
40 -157.496870 580.723748
41 -205.185303 -157.496870
42 -466.919875 -205.185303
43 158.892432 -466.919875
44 -274.315241 158.892432
45 74.947163 -274.315241
46 98.129837 74.947163
47 -34.954590 98.129837
48 70.486557 -34.954590
49 -8.932697 70.486557
50 -69.049308 -8.932697
51 -131.603736 -69.049308
52 22.113419 -131.603736
53 -72.959213 22.113419
54 -114.007045 -72.959213
55 -270.452017 -114.007045
56 108.988034 -270.452017
57 NA 108.988034
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -53.120949 -89.051801
[2,] -23.893153 -53.120949
[3,] -206.250212 -23.893153
[4,] -131.080610 -206.250212
[5,] -56.839317 -131.080610
[6,] 241.704072 -56.839317
[7,] -107.990477 241.704072
[8,] -168.080725 -107.990477
[9,] 297.771162 -168.080725
[10,] -151.148769 297.771162
[11,] 93.716902 -151.148769
[12,] -173.175559 93.716902
[13,] -178.570258 -173.175559
[14,] 155.234885 -178.570258
[15,] -19.642572 155.234885
[16,] 6.165578 -19.642572
[17,] 315.801187 6.165578
[18,] 48.599482 315.801187
[19,] -86.662339 48.599482
[20,] 423.402831 -86.662339
[21,] -172.120852 423.402831
[22,] -151.779434 -172.120852
[23,] -171.827933 -151.779434
[24,] 141.760689 -171.827933
[25,] 40.063340 141.760689
[26,] -255.659718 40.063340
[27,] -223.227228 -255.659718
[28,] 260.298484 -223.227228
[29,] 19.182647 260.298484
[30,] 290.623366 19.182647
[31,] 306.212401 290.623366
[32,] -89.994899 306.212401
[33,] -200.597473 -89.994899
[34,] 204.798366 -200.597473
[35,] 113.065621 204.798366
[36,] 49.980114 113.065621
[37,] 200.560564 49.980114
[38,] 193.367294 200.560564
[39,] 580.723748 193.367294
[40,] -157.496870 580.723748
[41,] -205.185303 -157.496870
[42,] -466.919875 -205.185303
[43,] 158.892432 -466.919875
[44,] -274.315241 158.892432
[45,] 74.947163 -274.315241
[46,] 98.129837 74.947163
[47,] -34.954590 98.129837
[48,] 70.486557 -34.954590
[49,] -8.932697 70.486557
[50,] -69.049308 -8.932697
[51,] -131.603736 -69.049308
[52,] 22.113419 -131.603736
[53,] -72.959213 22.113419
[54,] -114.007045 -72.959213
[55,] -270.452017 -114.007045
[56,] 108.988034 -270.452017
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -53.120949 -89.051801
2 -23.893153 -53.120949
3 -206.250212 -23.893153
4 -131.080610 -206.250212
5 -56.839317 -131.080610
6 241.704072 -56.839317
7 -107.990477 241.704072
8 -168.080725 -107.990477
9 297.771162 -168.080725
10 -151.148769 297.771162
11 93.716902 -151.148769
12 -173.175559 93.716902
13 -178.570258 -173.175559
14 155.234885 -178.570258
15 -19.642572 155.234885
16 6.165578 -19.642572
17 315.801187 6.165578
18 48.599482 315.801187
19 -86.662339 48.599482
20 423.402831 -86.662339
21 -172.120852 423.402831
22 -151.779434 -172.120852
23 -171.827933 -151.779434
24 141.760689 -171.827933
25 40.063340 141.760689
26 -255.659718 40.063340
27 -223.227228 -255.659718
28 260.298484 -223.227228
29 19.182647 260.298484
30 290.623366 19.182647
31 306.212401 290.623366
32 -89.994899 306.212401
33 -200.597473 -89.994899
34 204.798366 -200.597473
35 113.065621 204.798366
36 49.980114 113.065621
37 200.560564 49.980114
38 193.367294 200.560564
39 580.723748 193.367294
40 -157.496870 580.723748
41 -205.185303 -157.496870
42 -466.919875 -205.185303
43 158.892432 -466.919875
44 -274.315241 158.892432
45 74.947163 -274.315241
46 98.129837 74.947163
47 -34.954590 98.129837
48 70.486557 -34.954590
49 -8.932697 70.486557
50 -69.049308 -8.932697
51 -131.603736 -69.049308
52 22.113419 -131.603736
53 -72.959213 22.113419
54 -114.007045 -72.959213
55 -270.452017 -114.007045
56 108.988034 -270.452017
> 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/7erh51258741239.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/84nsv1258741239.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9unem1258741239.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/103j4r1258741239.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/115j9u1258741239.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/12pby61258741239.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/13t91r1258741239.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/14b4sv1258741239.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/15bbec1258741239.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/165j441258741239.tab")
+ }
> system("convert tmp/1ac0s1258741239.ps tmp/1ac0s1258741239.png")
> system("convert tmp/20slx1258741239.ps tmp/20slx1258741239.png")
> system("convert tmp/316m01258741239.ps tmp/316m01258741239.png")
> system("convert tmp/4mdct1258741239.ps tmp/4mdct1258741239.png")
> system("convert tmp/5xhyx1258741239.ps tmp/5xhyx1258741239.png")
> system("convert tmp/6cd0i1258741239.ps tmp/6cd0i1258741239.png")
> system("convert tmp/7erh51258741239.ps tmp/7erh51258741239.png")
> system("convert tmp/84nsv1258741239.ps tmp/84nsv1258741239.png")
> system("convert tmp/9unem1258741239.ps tmp/9unem1258741239.png")
> system("convert tmp/103j4r1258741239.ps tmp/103j4r1258741239.png")
>
>
> proc.time()
user system elapsed
2.395 1.568 2.811