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(2333
+ ,8
+ ,2355
+ ,2825
+ ,2214
+ ,2360
+ ,3016
+ ,8
+ ,2333
+ ,2355
+ ,2825
+ ,2214
+ ,2155
+ ,7.7
+ ,3016
+ ,2333
+ ,2355
+ ,2825
+ ,2172
+ ,6.9
+ ,2155
+ ,3016
+ ,2333
+ ,2355
+ ,2150
+ ,6.6
+ ,2172
+ ,2155
+ ,3016
+ ,2333
+ ,2533
+ ,6.9
+ ,2150
+ ,2172
+ ,2155
+ ,3016
+ ,2058
+ ,7.5
+ ,2533
+ ,2150
+ ,2172
+ ,2155
+ ,2160
+ ,7.9
+ ,2058
+ ,2533
+ ,2150
+ ,2172
+ ,2260
+ ,7.7
+ ,2160
+ ,2058
+ ,2533
+ ,2150
+ ,2498
+ ,6.5
+ ,2260
+ ,2160
+ ,2058
+ ,2533
+ ,2695
+ ,6.1
+ ,2498
+ ,2260
+ ,2160
+ ,2058
+ ,2799
+ ,6.4
+ ,2695
+ ,2498
+ ,2260
+ ,2160
+ ,2947
+ ,6.8
+ ,2799
+ ,2695
+ ,2498
+ ,2260
+ ,2930
+ ,7.1
+ ,2947
+ ,2799
+ ,2695
+ ,2498
+ ,2318
+ ,7.3
+ ,2930
+ ,2947
+ ,2799
+ ,2695
+ ,2540
+ ,7.2
+ ,2318
+ ,2930
+ ,2947
+ ,2799
+ ,2570
+ ,7
+ ,2540
+ ,2318
+ ,2930
+ ,2947
+ ,2669
+ ,7
+ ,2570
+ ,2540
+ ,2318
+ ,2930
+ ,2450
+ ,7
+ ,2669
+ ,2570
+ ,2540
+ ,2318
+ ,2842
+ ,7.3
+ ,2450
+ ,2669
+ ,2570
+ ,2540
+ ,3440
+ ,7.5
+ ,2842
+ ,2450
+ ,2669
+ ,2570
+ ,2678
+ ,7.2
+ ,3440
+ ,2842
+ ,2450
+ ,2669
+ ,2981
+ ,7.7
+ ,2678
+ ,3440
+ ,2842
+ ,2450
+ ,2260
+ ,8
+ ,2981
+ ,2678
+ ,3440
+ ,2842
+ ,2844
+ ,7.9
+ ,2260
+ ,2981
+ ,2678
+ ,3440
+ ,2546
+ ,8
+ ,2844
+ ,2260
+ ,2981
+ ,2678
+ ,2456
+ ,8
+ ,2546
+ ,2844
+ ,2260
+ ,2981
+ ,2295
+ ,7.9
+ ,2456
+ ,2546
+ ,2844
+ ,2260
+ ,2379
+ ,7.9
+ ,2295
+ ,2456
+ ,2546
+ ,2844
+ ,2479
+ ,8
+ ,2379
+ ,2295
+ ,2456
+ ,2546
+ ,2057
+ ,8.1
+ ,2479
+ ,2379
+ ,2295
+ ,2456
+ ,2280
+ ,8.1
+ ,2057
+ ,2479
+ ,2379
+ ,2295
+ ,2351
+ ,8.2
+ ,2280
+ ,2057
+ ,2479
+ ,2379
+ ,2276
+ ,8
+ ,2351
+ ,2280
+ ,2057
+ ,2479
+ ,2548
+ ,8.3
+ ,2276
+ ,2351
+ ,2280
+ ,2057
+ ,2311
+ ,8.5
+ ,2548
+ ,2276
+ ,2351
+ ,2280
+ ,2201
+ ,8.6
+ ,2311
+ ,2548
+ ,2276
+ ,2351
+ ,2725
+ ,8.7
+ ,2201
+ ,2311
+ ,2548
+ ,2276
+ ,2408
+ ,8.7
+ ,2725
+ ,2201
+ ,2311
+ ,2548
+ ,2139
+ ,8.5
+ ,2408
+ ,2725
+ ,2201
+ ,2311
+ ,1898
+ ,8.4
+ ,2139
+ ,2408
+ ,2725
+ ,2201
+ ,2537
+ ,8.5
+ ,1898
+ ,2139
+ ,2408
+ ,2725
+ ,2069
+ ,8.7
+ ,2537
+ ,1898
+ ,2139
+ ,2408
+ ,2063
+ ,8.7
+ ,2069
+ ,2537
+ ,1898
+ ,2139
+ ,2524
+ ,8.6
+ ,2063
+ ,2069
+ ,2537
+ ,1898
+ ,2437
+ ,7.9
+ ,2524
+ ,2063
+ ,2069
+ ,2537
+ ,2189
+ ,8.1
+ ,2437
+ ,2524
+ ,2063
+ ,2069
+ ,2793
+ ,8.2
+ ,2189
+ ,2437
+ ,2524
+ ,2063
+ ,2074
+ ,8.5
+ ,2793
+ ,2189
+ ,2437
+ ,2524
+ ,2622
+ ,8.6
+ ,2074
+ ,2793
+ ,2189
+ ,2437
+ ,2278
+ ,8.5
+ ,2622
+ ,2074
+ ,2793
+ ,2189
+ ,2144
+ ,8.3
+ ,2278
+ ,2622
+ ,2074
+ ,2793
+ ,2427
+ ,8.2
+ ,2144
+ ,2278
+ ,2622
+ ,2074
+ ,2139
+ ,8.7
+ ,2427
+ ,2144
+ ,2278
+ ,2622
+ ,1828
+ ,9.3
+ ,2139
+ ,2427
+ ,2144
+ ,2278
+ ,2072
+ ,9.3
+ ,1828
+ ,2139
+ ,2427
+ ,2144
+ ,1800
+ ,8.8
+ ,2072
+ ,1828
+ ,2139
+ ,2427
+ ,1758
+ ,7.4
+ ,1800
+ ,2072
+ ,1828
+ ,2139
+ ,2246
+ ,7.2
+ ,1758
+ ,1800
+ ,2072
+ ,1828
+ ,1987
+ ,7.5
+ ,2246
+ ,1758
+ ,1800
+ ,2072
+ ,1868
+ ,8.3
+ ,1987
+ ,2246
+ ,1758
+ ,1800
+ ,2514
+ ,8.8
+ ,1868
+ ,1987
+ ,2246
+ ,1758
+ ,2121
+ ,8.9
+ ,2514
+ ,1868
+ ,1987
+ ,2246)
+ ,dim=c(6
+ ,63)
+ ,dimnames=list(c('Y'
+ ,'X'
+ ,'Y1'
+ ,'Y2'
+ ,'Y3'
+ ,'Y4')
+ ,1:63))
> y <- array(NA,dim=c(6,63),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:63))
> 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 2333 8.0 2355 2825 2214 2360 1 0 0 0 0 0 0 0 0 0 0 1
2 3016 8.0 2333 2355 2825 2214 0 1 0 0 0 0 0 0 0 0 0 2
3 2155 7.7 3016 2333 2355 2825 0 0 1 0 0 0 0 0 0 0 0 3
4 2172 6.9 2155 3016 2333 2355 0 0 0 1 0 0 0 0 0 0 0 4
5 2150 6.6 2172 2155 3016 2333 0 0 0 0 1 0 0 0 0 0 0 5
6 2533 6.9 2150 2172 2155 3016 0 0 0 0 0 1 0 0 0 0 0 6
7 2058 7.5 2533 2150 2172 2155 0 0 0 0 0 0 1 0 0 0 0 7
8 2160 7.9 2058 2533 2150 2172 0 0 0 0 0 0 0 1 0 0 0 8
9 2260 7.7 2160 2058 2533 2150 0 0 0 0 0 0 0 0 1 0 0 9
10 2498 6.5 2260 2160 2058 2533 0 0 0 0 0 0 0 0 0 1 0 10
11 2695 6.1 2498 2260 2160 2058 0 0 0 0 0 0 0 0 0 0 1 11
12 2799 6.4 2695 2498 2260 2160 0 0 0 0 0 0 0 0 0 0 0 12
13 2947 6.8 2799 2695 2498 2260 1 0 0 0 0 0 0 0 0 0 0 13
14 2930 7.1 2947 2799 2695 2498 0 1 0 0 0 0 0 0 0 0 0 14
15 2318 7.3 2930 2947 2799 2695 0 0 1 0 0 0 0 0 0 0 0 15
16 2540 7.2 2318 2930 2947 2799 0 0 0 1 0 0 0 0 0 0 0 16
17 2570 7.0 2540 2318 2930 2947 0 0 0 0 1 0 0 0 0 0 0 17
18 2669 7.0 2570 2540 2318 2930 0 0 0 0 0 1 0 0 0 0 0 18
19 2450 7.0 2669 2570 2540 2318 0 0 0 0 0 0 1 0 0 0 0 19
20 2842 7.3 2450 2669 2570 2540 0 0 0 0 0 0 0 1 0 0 0 20
21 3440 7.5 2842 2450 2669 2570 0 0 0 0 0 0 0 0 1 0 0 21
22 2678 7.2 3440 2842 2450 2669 0 0 0 0 0 0 0 0 0 1 0 22
23 2981 7.7 2678 3440 2842 2450 0 0 0 0 0 0 0 0 0 0 1 23
24 2260 8.0 2981 2678 3440 2842 0 0 0 0 0 0 0 0 0 0 0 24
25 2844 7.9 2260 2981 2678 3440 1 0 0 0 0 0 0 0 0 0 0 25
26 2546 8.0 2844 2260 2981 2678 0 1 0 0 0 0 0 0 0 0 0 26
27 2456 8.0 2546 2844 2260 2981 0 0 1 0 0 0 0 0 0 0 0 27
28 2295 7.9 2456 2546 2844 2260 0 0 0 1 0 0 0 0 0 0 0 28
29 2379 7.9 2295 2456 2546 2844 0 0 0 0 1 0 0 0 0 0 0 29
30 2479 8.0 2379 2295 2456 2546 0 0 0 0 0 1 0 0 0 0 0 30
31 2057 8.1 2479 2379 2295 2456 0 0 0 0 0 0 1 0 0 0 0 31
32 2280 8.1 2057 2479 2379 2295 0 0 0 0 0 0 0 1 0 0 0 32
33 2351 8.2 2280 2057 2479 2379 0 0 0 0 0 0 0 0 1 0 0 33
34 2276 8.0 2351 2280 2057 2479 0 0 0 0 0 0 0 0 0 1 0 34
35 2548 8.3 2276 2351 2280 2057 0 0 0 0 0 0 0 0 0 0 1 35
36 2311 8.5 2548 2276 2351 2280 0 0 0 0 0 0 0 0 0 0 0 36
37 2201 8.6 2311 2548 2276 2351 1 0 0 0 0 0 0 0 0 0 0 37
38 2725 8.7 2201 2311 2548 2276 0 1 0 0 0 0 0 0 0 0 0 38
39 2408 8.7 2725 2201 2311 2548 0 0 1 0 0 0 0 0 0 0 0 39
40 2139 8.5 2408 2725 2201 2311 0 0 0 1 0 0 0 0 0 0 0 40
41 1898 8.4 2139 2408 2725 2201 0 0 0 0 1 0 0 0 0 0 0 41
42 2537 8.5 1898 2139 2408 2725 0 0 0 0 0 1 0 0 0 0 0 42
43 2069 8.7 2537 1898 2139 2408 0 0 0 0 0 0 1 0 0 0 0 43
44 2063 8.7 2069 2537 1898 2139 0 0 0 0 0 0 0 1 0 0 0 44
45 2524 8.6 2063 2069 2537 1898 0 0 0 0 0 0 0 0 1 0 0 45
46 2437 7.9 2524 2063 2069 2537 0 0 0 0 0 0 0 0 0 1 0 46
47 2189 8.1 2437 2524 2063 2069 0 0 0 0 0 0 0 0 0 0 1 47
48 2793 8.2 2189 2437 2524 2063 0 0 0 0 0 0 0 0 0 0 0 48
49 2074 8.5 2793 2189 2437 2524 1 0 0 0 0 0 0 0 0 0 0 49
50 2622 8.6 2074 2793 2189 2437 0 1 0 0 0 0 0 0 0 0 0 50
51 2278 8.5 2622 2074 2793 2189 0 0 1 0 0 0 0 0 0 0 0 51
52 2144 8.3 2278 2622 2074 2793 0 0 0 1 0 0 0 0 0 0 0 52
53 2427 8.2 2144 2278 2622 2074 0 0 0 0 1 0 0 0 0 0 0 53
54 2139 8.7 2427 2144 2278 2622 0 0 0 0 0 1 0 0 0 0 0 54
55 1828 9.3 2139 2427 2144 2278 0 0 0 0 0 0 1 0 0 0 0 55
56 2072 9.3 1828 2139 2427 2144 0 0 0 0 0 0 0 1 0 0 0 56
57 1800 8.8 2072 1828 2139 2427 0 0 0 0 0 0 0 0 1 0 0 57
58 1758 7.4 1800 2072 1828 2139 0 0 0 0 0 0 0 0 0 1 0 58
59 2246 7.2 1758 1800 2072 1828 0 0 0 0 0 0 0 0 0 0 1 59
60 1987 7.5 2246 1758 1800 2072 0 0 0 0 0 0 0 0 0 0 0 60
61 1868 8.3 1987 2246 1758 1800 1 0 0 0 0 0 0 0 0 0 0 61
62 2514 8.8 1868 1987 2246 1758 0 1 0 0 0 0 0 0 0 0 0 62
63 2121 8.9 2514 1868 1987 2246 0 0 1 0 0 0 0 0 0 0 0 63
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X Y1 Y2 Y3 Y4
1908.34256 -146.92384 0.13237 0.29892 0.19761 0.04613
M1 M2 M3 M4 M5 M6
-39.76380 341.29459 -112.55365 -273.95529 -182.80880 122.83462
M7 M8 M9 M10 M11 t
-212.27344 -9.44724 216.52381 -57.74343 97.31393 0.83515
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-498.96 -141.55 30.06 135.30 645.01
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1908.34256 640.87825 2.978 0.00466 **
X -146.92384 75.02945 -1.958 0.05642 .
Y1 0.13237 0.14406 0.919 0.36307
Y2 0.29892 0.14326 2.087 0.04262 *
Y3 0.19761 0.14374 1.375 0.17602
Y4 0.04613 0.14268 0.323 0.74798
M1 -39.76380 162.33470 -0.245 0.80761
M2 341.29459 159.34315 2.142 0.03765 *
M3 -112.55365 163.53503 -0.688 0.49483
M4 -273.95529 173.84932 -1.576 0.12207
M5 -182.80880 173.78368 -1.052 0.29845
M6 122.83462 182.52251 0.673 0.50440
M7 -212.27344 167.68062 -1.266 0.21205
M8 -9.44724 177.97564 -0.053 0.95790
M9 216.52381 169.47188 1.278 0.20793
M10 -57.74343 170.39645 -0.339 0.73628
M11 97.31393 165.83668 0.587 0.56027
t 0.83515 3.14920 0.265 0.79207
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 248.9 on 45 degrees of freedom
Multiple R-squared: 0.5932, Adjusted R-squared: 0.4395
F-statistic: 3.86 on 17 and 45 DF, p-value: 0.0001443
> 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,] 0.8252124 0.34957529 0.17478764
[2,] 0.8589494 0.28210112 0.14105056
[3,] 0.7915959 0.41680814 0.20840407
[4,] 0.9574062 0.08518762 0.04259381
[5,] 0.9439572 0.11208566 0.05604283
[6,] 0.9421696 0.11566080 0.05783040
[7,] 0.9272102 0.14557962 0.07278981
[8,] 0.9138187 0.17236266 0.08618133
[9,] 0.8699852 0.26002964 0.13001482
[10,] 0.8051101 0.38977972 0.19488986
[11,] 0.7404171 0.51916572 0.25958286
[12,] 0.6565594 0.68688125 0.34344063
[13,] 0.6091610 0.78167800 0.39083900
[14,] 0.4997089 0.99941787 0.50029107
[15,] 0.4177859 0.83557175 0.58221412
[16,] 0.3574242 0.71484836 0.64257582
[17,] 0.2750193 0.55003864 0.72498068
[18,] 0.2023095 0.40461902 0.79769049
[19,] 0.1596171 0.31923417 0.84038292
[20,] 0.1199569 0.23991370 0.88004315
[21,] 0.4947084 0.98941679 0.50529161
[22,] 0.5426339 0.91473225 0.45736612
> postscript(file="/var/www/html/rcomp/tmp/1mkpg1258743757.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2v5fi1258743757.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3235j1258743757.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4yo9j1258743757.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/53vay1258743757.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 = 63
Frequency = 1
1 2 3 4 5 6
-63.566985 266.940738 -204.263500 -208.401674 -245.290903 11.774059
7 8 9 10 11 12
-48.565143 -139.504558 -241.878715 125.715042 48.410658 171.280868
13 14 15 16 17 18
292.681963 -162.719657 -363.949791 55.973594 114.693269 -41.397010
19 20 21 22 23 24
36.163879 251.807414 645.013588 -45.256390 30.063973 -498.961151
25 26 27 28 29 30
237.134544 -314.575919 41.812442 45.532434 117.714720 -5.534103
31 32 33 34 35 36
-80.949073 -44.814981 -112.938071 58.829297 183.117044 34.078717
37 38 39 40 41 42
-60.689371 131.224701 265.043729 45.220931 -270.559948 227.436350
43 44 45 46 47 48
178.327667 -100.363584 144.672293 232.034243 -245.987229 437.197647
49 50 51 52 53 54
-208.688067 -60.243631 68.546684 61.674715 283.442862 -192.279297
55 56 57 58 59 60
-84.977330 32.875709 -434.869094 -371.322191 -15.604445 -143.596081
61 62 63
-196.872084 139.373767 192.810437
> postscript(file="/var/www/html/rcomp/tmp/6ce4p1258743757.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 = 63
Frequency = 1
lag(myerror, k = 1) myerror
0 -63.566985 NA
1 266.940738 -63.566985
2 -204.263500 266.940738
3 -208.401674 -204.263500
4 -245.290903 -208.401674
5 11.774059 -245.290903
6 -48.565143 11.774059
7 -139.504558 -48.565143
8 -241.878715 -139.504558
9 125.715042 -241.878715
10 48.410658 125.715042
11 171.280868 48.410658
12 292.681963 171.280868
13 -162.719657 292.681963
14 -363.949791 -162.719657
15 55.973594 -363.949791
16 114.693269 55.973594
17 -41.397010 114.693269
18 36.163879 -41.397010
19 251.807414 36.163879
20 645.013588 251.807414
21 -45.256390 645.013588
22 30.063973 -45.256390
23 -498.961151 30.063973
24 237.134544 -498.961151
25 -314.575919 237.134544
26 41.812442 -314.575919
27 45.532434 41.812442
28 117.714720 45.532434
29 -5.534103 117.714720
30 -80.949073 -5.534103
31 -44.814981 -80.949073
32 -112.938071 -44.814981
33 58.829297 -112.938071
34 183.117044 58.829297
35 34.078717 183.117044
36 -60.689371 34.078717
37 131.224701 -60.689371
38 265.043729 131.224701
39 45.220931 265.043729
40 -270.559948 45.220931
41 227.436350 -270.559948
42 178.327667 227.436350
43 -100.363584 178.327667
44 144.672293 -100.363584
45 232.034243 144.672293
46 -245.987229 232.034243
47 437.197647 -245.987229
48 -208.688067 437.197647
49 -60.243631 -208.688067
50 68.546684 -60.243631
51 61.674715 68.546684
52 283.442862 61.674715
53 -192.279297 283.442862
54 -84.977330 -192.279297
55 32.875709 -84.977330
56 -434.869094 32.875709
57 -371.322191 -434.869094
58 -15.604445 -371.322191
59 -143.596081 -15.604445
60 -196.872084 -143.596081
61 139.373767 -196.872084
62 192.810437 139.373767
63 NA 192.810437
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 266.940738 -63.566985
[2,] -204.263500 266.940738
[3,] -208.401674 -204.263500
[4,] -245.290903 -208.401674
[5,] 11.774059 -245.290903
[6,] -48.565143 11.774059
[7,] -139.504558 -48.565143
[8,] -241.878715 -139.504558
[9,] 125.715042 -241.878715
[10,] 48.410658 125.715042
[11,] 171.280868 48.410658
[12,] 292.681963 171.280868
[13,] -162.719657 292.681963
[14,] -363.949791 -162.719657
[15,] 55.973594 -363.949791
[16,] 114.693269 55.973594
[17,] -41.397010 114.693269
[18,] 36.163879 -41.397010
[19,] 251.807414 36.163879
[20,] 645.013588 251.807414
[21,] -45.256390 645.013588
[22,] 30.063973 -45.256390
[23,] -498.961151 30.063973
[24,] 237.134544 -498.961151
[25,] -314.575919 237.134544
[26,] 41.812442 -314.575919
[27,] 45.532434 41.812442
[28,] 117.714720 45.532434
[29,] -5.534103 117.714720
[30,] -80.949073 -5.534103
[31,] -44.814981 -80.949073
[32,] -112.938071 -44.814981
[33,] 58.829297 -112.938071
[34,] 183.117044 58.829297
[35,] 34.078717 183.117044
[36,] -60.689371 34.078717
[37,] 131.224701 -60.689371
[38,] 265.043729 131.224701
[39,] 45.220931 265.043729
[40,] -270.559948 45.220931
[41,] 227.436350 -270.559948
[42,] 178.327667 227.436350
[43,] -100.363584 178.327667
[44,] 144.672293 -100.363584
[45,] 232.034243 144.672293
[46,] -245.987229 232.034243
[47,] 437.197647 -245.987229
[48,] -208.688067 437.197647
[49,] -60.243631 -208.688067
[50,] 68.546684 -60.243631
[51,] 61.674715 68.546684
[52,] 283.442862 61.674715
[53,] -192.279297 283.442862
[54,] -84.977330 -192.279297
[55,] 32.875709 -84.977330
[56,] -434.869094 32.875709
[57,] -371.322191 -434.869094
[58,] -15.604445 -371.322191
[59,] -143.596081 -15.604445
[60,] -196.872084 -143.596081
[61,] 139.373767 -196.872084
[62,] 192.810437 139.373767
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 266.940738 -63.566985
2 -204.263500 266.940738
3 -208.401674 -204.263500
4 -245.290903 -208.401674
5 11.774059 -245.290903
6 -48.565143 11.774059
7 -139.504558 -48.565143
8 -241.878715 -139.504558
9 125.715042 -241.878715
10 48.410658 125.715042
11 171.280868 48.410658
12 292.681963 171.280868
13 -162.719657 292.681963
14 -363.949791 -162.719657
15 55.973594 -363.949791
16 114.693269 55.973594
17 -41.397010 114.693269
18 36.163879 -41.397010
19 251.807414 36.163879
20 645.013588 251.807414
21 -45.256390 645.013588
22 30.063973 -45.256390
23 -498.961151 30.063973
24 237.134544 -498.961151
25 -314.575919 237.134544
26 41.812442 -314.575919
27 45.532434 41.812442
28 117.714720 45.532434
29 -5.534103 117.714720
30 -80.949073 -5.534103
31 -44.814981 -80.949073
32 -112.938071 -44.814981
33 58.829297 -112.938071
34 183.117044 58.829297
35 34.078717 183.117044
36 -60.689371 34.078717
37 131.224701 -60.689371
38 265.043729 131.224701
39 45.220931 265.043729
40 -270.559948 45.220931
41 227.436350 -270.559948
42 178.327667 227.436350
43 -100.363584 178.327667
44 144.672293 -100.363584
45 232.034243 144.672293
46 -245.987229 232.034243
47 437.197647 -245.987229
48 -208.688067 437.197647
49 -60.243631 -208.688067
50 68.546684 -60.243631
51 61.674715 68.546684
52 283.442862 61.674715
53 -192.279297 283.442862
54 -84.977330 -192.279297
55 32.875709 -84.977330
56 -434.869094 32.875709
57 -371.322191 -434.869094
58 -15.604445 -371.322191
59 -143.596081 -15.604445
60 -196.872084 -143.596081
61 139.373767 -196.872084
62 192.810437 139.373767
> 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/7rcwq1258743757.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8s54f1258743757.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9ffhq1258743757.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10j28r1258743757.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/116ark1258743757.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/12judm1258743757.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/13hp7d1258743757.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/14aa8q1258743757.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/15qxor1258743757.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/16jqg71258743757.tab")
+ }
>
> system("convert tmp/1mkpg1258743757.ps tmp/1mkpg1258743757.png")
> system("convert tmp/2v5fi1258743757.ps tmp/2v5fi1258743757.png")
> system("convert tmp/3235j1258743757.ps tmp/3235j1258743757.png")
> system("convert tmp/4yo9j1258743757.ps tmp/4yo9j1258743757.png")
> system("convert tmp/53vay1258743757.ps tmp/53vay1258743757.png")
> system("convert tmp/6ce4p1258743757.ps tmp/6ce4p1258743757.png")
> system("convert tmp/7rcwq1258743757.ps tmp/7rcwq1258743757.png")
> system("convert tmp/8s54f1258743757.ps tmp/8s54f1258743757.png")
> system("convert tmp/9ffhq1258743757.ps tmp/9ffhq1258743757.png")
> system("convert tmp/10j28r1258743757.ps tmp/10j28r1258743757.png")
>
>
> proc.time()
user system elapsed
2.448 1.575 3.277