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(3.823082797
+ ,-999.00
+ ,3.00
+ ,0
+ ,6.30
+ ,3.00
+ ,0.529558673
+ ,-999.00
+ ,1.00
+ ,-0.036212173
+ ,-999.00
+ ,3.00
+ ,3.406028945
+ ,2.10
+ ,4.00
+ ,1.02325246
+ ,9.10
+ ,4.00
+ ,-1.638272164
+ ,15.80
+ ,1.00
+ ,2.204119983
+ ,5.20
+ ,4.00
+ ,0.51851394
+ ,10.90
+ ,1.00
+ ,1.717337583
+ ,8.30
+ ,1.00
+ ,-0.37161107
+ ,11.00
+ ,4.00
+ ,2.667452953
+ ,3.20
+ ,5.00
+ ,-0.259637311
+ ,7.60
+ ,2.00
+ ,2.272073788
+ ,-999.00
+ ,5.00
+ ,-1.124938737
+ ,6.30
+ ,1.00
+ ,0.477121255
+ ,8.60
+ ,2.00
+ ,-0.105130343
+ ,6.60
+ ,2.00
+ ,-0.698970004
+ ,9.50
+ ,2.00
+ ,0.149219113
+ ,4.80
+ ,1.00
+ ,1.77815125
+ ,12.00
+ ,1.00
+ ,2.723455672
+ ,-999.00
+ ,5.00
+ ,1.441852176
+ ,3.30
+ ,5.00
+ ,-0.920818754
+ ,11.00
+ ,2.00
+ ,2.315970345
+ ,-999.00
+ ,1.00
+ ,1.929418926
+ ,4.70
+ ,1.00
+ ,1.560265398
+ ,-999.00
+ ,1.00
+ ,-0.995678626
+ ,10.40
+ ,3.00
+ ,0.017033339
+ ,7.40
+ ,4.00
+ ,2.716837723
+ ,2.10
+ ,5.00
+ ,2
+ ,-999.00
+ ,1.00
+ ,1.544068044
+ ,-999.00
+ ,4.00
+ ,-2.301029996
+ ,7.70
+ ,4.00
+ ,-2
+ ,17.90
+ ,1.00
+ ,1.792391689
+ ,6.10
+ ,1.00
+ ,-0.913640169
+ ,8.20
+ ,1.00
+ ,0.130333768
+ ,8.40
+ ,3.00
+ ,-1.638272164
+ ,11.90
+ ,3.00
+ ,-1.318758763
+ ,10.80
+ ,3.00
+ ,0.230448921
+ ,13.80
+ ,1.00
+ ,0.544068044
+ ,14.30
+ ,1.00
+ ,2.397940009
+ ,-999.00
+ ,5.00
+ ,-0.318758763
+ ,15.20
+ ,2.00
+ ,1
+ ,10.00
+ ,4.00
+ ,0.209515015
+ ,11.90
+ ,2.00
+ ,2.283301229
+ ,6.50
+ ,4.00
+ ,0.397940009
+ ,7.50
+ ,5.00
+ ,0.632254777
+ ,-999.00
+ ,2.00
+ ,-0.552841969
+ ,10.60
+ ,3.00
+ ,0.626853415
+ ,7.40
+ ,1.00
+ ,0.832508913
+ ,8.40
+ ,2.00
+ ,-0.124938737
+ ,5.70
+ ,2.00
+ ,0.556302501
+ ,4.90
+ ,3.00
+ ,1.171141151
+ ,-999.00
+ ,5.00
+ ,1.744292983
+ ,3.20
+ ,5.00
+ ,0.146128036
+ ,-999.00
+ ,2.00
+ ,-1.22184875
+ ,8.10
+ ,2.00
+ ,-0.045757491
+ ,11.00
+ ,2.00
+ ,0.301029996
+ ,4.90
+ ,3.00
+ ,-0.982966661
+ ,13.20
+ ,2.00
+ ,0.622214023
+ ,9.70
+ ,4.00
+ ,0.544068044
+ ,12.80
+ ,1.00
+ ,0.607455023
+ ,-999.00
+ ,1.00)
+ ,dim=c(3
+ ,62)
+ ,dimnames=list(c('logwb'
+ ,'sws'
+ ,'D')
+ ,1:62))
> y <- array(NA,dim=c(3,62),dimnames=list(c('logwb','sws','D'),1:62))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '2'
> #'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
sws logwb D
1 -999.0 3.82308280 3
2 6.3 0.00000000 3
3 -999.0 0.52955867 1
4 -999.0 -0.03621217 3
5 2.1 3.40602895 4
6 9.1 1.02325246 4
7 15.8 -1.63827216 1
8 5.2 2.20411998 4
9 10.9 0.51851394 1
10 8.3 1.71733758 1
11 11.0 -0.37161107 4
12 3.2 2.66745295 5
13 7.6 -0.25963731 2
14 -999.0 2.27207379 5
15 6.3 -1.12493874 1
16 8.6 0.47712126 2
17 6.6 -0.10513034 2
18 9.5 -0.69897000 2
19 4.8 0.14921911 1
20 12.0 1.77815125 1
21 -999.0 2.72345567 5
22 3.3 1.44185218 5
23 11.0 -0.92081875 2
24 -999.0 2.31597035 1
25 4.7 1.92941893 1
26 -999.0 1.56026540 1
27 10.4 -0.99567863 3
28 7.4 0.01703334 4
29 2.1 2.71683772 5
30 -999.0 2.00000000 1
31 -999.0 1.54406804 4
32 7.7 -2.30103000 4
33 17.9 -2.00000000 1
34 6.1 1.79239169 1
35 8.2 -0.91364017 1
36 8.4 0.13033377 3
37 11.9 -1.63827216 3
38 10.8 -1.31875876 3
39 13.8 0.23044892 1
40 14.3 0.54406804 1
41 -999.0 2.39794001 5
42 15.2 -0.31875876 2
43 10.0 1.00000000 4
44 11.9 0.20951501 2
45 6.5 2.28330123 4
46 7.5 0.39794001 5
47 -999.0 0.63225478 2
48 10.6 -0.55284197 3
49 7.4 0.62685342 1
50 8.4 0.83250891 2
51 5.7 -0.12493874 2
52 4.9 0.55630250 3
53 -999.0 1.17114115 5
54 3.2 1.74429298 5
55 -999.0 0.14612804 2
56 8.1 -1.22184875 2
57 11.0 -0.04575749 2
58 4.9 0.30103000 3
59 13.2 -0.98296666 2
60 9.7 0.62221402 4
61 12.8 0.54406804 1
62 -999.0 0.60745502 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) logwb D
-193.77 -129.45 19.18
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-867.44 -65.79 135.98 257.50 560.09
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -193.77 105.22 -1.842 0.07056 .
logwb -129.45 39.53 -3.275 0.00177 **
D 19.18 37.20 0.515 0.60819
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 396.4 on 59 degrees of freedom
Multiple R-squared: 0.1577, Adjusted R-squared: 0.1292
F-statistic: 5.525 on 2 and 59 DF, p-value: 0.006319
> 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,] 0.8421806 0.3156388 0.15781940
[2,] 0.9163990 0.1672019 0.08360095
[3,] 0.8784153 0.2431694 0.12158472
[4,] 0.9223707 0.1552586 0.07762928
[5,] 0.9333575 0.1332851 0.06664254
[6,] 0.8931270 0.2137460 0.10687301
[7,] 0.8660992 0.2678015 0.13390076
[8,] 0.8193539 0.3612923 0.18064614
[9,] 0.9091591 0.1816817 0.09084086
[10,] 0.8698024 0.2603953 0.13019764
[11,] 0.8333493 0.3333014 0.16665069
[12,] 0.7819216 0.4361567 0.21807835
[13,] 0.7166461 0.5667077 0.28335386
[14,] 0.6563191 0.6873619 0.34368095
[15,] 0.6382817 0.7234367 0.36171833
[16,] 0.6963499 0.6073002 0.30365011
[17,] 0.6687371 0.6625258 0.33126289
[18,] 0.5942751 0.8114499 0.40572493
[19,] 0.6567928 0.6864143 0.34320717
[20,] 0.6604690 0.6790621 0.33953103
[21,] 0.7462977 0.5074045 0.25370225
[22,] 0.6807070 0.6385859 0.31929296
[23,] 0.6154689 0.7690621 0.38453107
[24,] 0.6354565 0.7290871 0.36454354
[25,] 0.6977328 0.6045344 0.30226718
[26,] 0.8081160 0.3837679 0.19188396
[27,] 0.7598789 0.4802421 0.24012106
[28,] 0.6981814 0.6036373 0.30181864
[29,] 0.6951138 0.6097723 0.30488617
[30,] 0.6256548 0.7486904 0.37434522
[31,] 0.5617087 0.8765827 0.43829134
[32,] 0.4871195 0.9742390 0.51288052
[33,] 0.4109560 0.8219121 0.58904395
[34,] 0.3562099 0.7124198 0.64379008
[35,] 0.3173392 0.6346784 0.68266079
[36,] 0.3985240 0.7970480 0.60147601
[37,] 0.3313116 0.6626232 0.66868840
[38,] 0.2801495 0.5602991 0.71985046
[39,] 0.2309174 0.4618349 0.76908256
[40,] 0.2355621 0.4711242 0.76443790
[41,] 0.1793890 0.3587780 0.82061099
[42,] 0.3127652 0.6255303 0.68723483
[43,] 0.2375453 0.4750907 0.76245466
[44,] 0.2012904 0.4025809 0.79870957
[45,] 0.1812748 0.3625496 0.81872519
[46,] 0.1329031 0.2658063 0.86709685
[47,] 0.1029086 0.2058172 0.89709141
[48,] 0.3244935 0.6489871 0.67550646
[49,] 0.2276096 0.4552191 0.77239045
[50,] 0.5159504 0.9680992 0.48404961
[51,] 0.3582489 0.7164978 0.64175109
> postscript(file="/var/www/html/rcomp/tmp/1xeyh1293054092.ps",horizontal=F,onefile=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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2xeyh1293054092.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3xeyh1293054092.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4q6fk1293054092.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5q6fk1293054092.ps",horizontal=F,onefile=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 = 62
Frequency = 1
1 2 3 4 5 6
-367.845038 142.545974 -755.849856 -867.441795 560.090506 258.633284
7 8 9 10 11 12
-21.681750 407.599958 252.620372 405.211517 79.964216 446.404091
13 14 15 16 17 18
129.410826 -606.978872 35.270728 225.786327 148.412194 74.437954
19 20 21 22 23 24
198.714102 416.784020 -548.546197 287.846569 47.219000 -524.593762
25 26 27 28 29 30
429.066052 -622.421926 17.752532 126.675345 451.697090 -565.497026
31 32 33 34 35 36
-682.045651 -173.104575 -66.408452 412.727485 64.523932 161.518052
37 38 39 40 41 42
-63.933037 -23.671115 218.229532 259.328424 -590.685130 129.357385
43 44 45 46 47 48
256.523187 194.443935 419.150196 156.909157 -761.731196 75.279002
49 50 51 52 53 54
263.145226 271.592274 144.947941 213.160922 -749.497746 326.898396
55 56 57 58 59 60
-824.661691 5.349807 160.498180 180.115167 41.373776 207.317713
61 62
257.828424 -745.765951
> postscript(file="/var/www/html/rcomp/tmp/6q6fk1293054092.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 62
Frequency = 1
lag(myerror, k = 1) myerror
0 -367.845038 NA
1 142.545974 -367.845038
2 -755.849856 142.545974
3 -867.441795 -755.849856
4 560.090506 -867.441795
5 258.633284 560.090506
6 -21.681750 258.633284
7 407.599958 -21.681750
8 252.620372 407.599958
9 405.211517 252.620372
10 79.964216 405.211517
11 446.404091 79.964216
12 129.410826 446.404091
13 -606.978872 129.410826
14 35.270728 -606.978872
15 225.786327 35.270728
16 148.412194 225.786327
17 74.437954 148.412194
18 198.714102 74.437954
19 416.784020 198.714102
20 -548.546197 416.784020
21 287.846569 -548.546197
22 47.219000 287.846569
23 -524.593762 47.219000
24 429.066052 -524.593762
25 -622.421926 429.066052
26 17.752532 -622.421926
27 126.675345 17.752532
28 451.697090 126.675345
29 -565.497026 451.697090
30 -682.045651 -565.497026
31 -173.104575 -682.045651
32 -66.408452 -173.104575
33 412.727485 -66.408452
34 64.523932 412.727485
35 161.518052 64.523932
36 -63.933037 161.518052
37 -23.671115 -63.933037
38 218.229532 -23.671115
39 259.328424 218.229532
40 -590.685130 259.328424
41 129.357385 -590.685130
42 256.523187 129.357385
43 194.443935 256.523187
44 419.150196 194.443935
45 156.909157 419.150196
46 -761.731196 156.909157
47 75.279002 -761.731196
48 263.145226 75.279002
49 271.592274 263.145226
50 144.947941 271.592274
51 213.160922 144.947941
52 -749.497746 213.160922
53 326.898396 -749.497746
54 -824.661691 326.898396
55 5.349807 -824.661691
56 160.498180 5.349807
57 180.115167 160.498180
58 41.373776 180.115167
59 207.317713 41.373776
60 257.828424 207.317713
61 -745.765951 257.828424
62 NA -745.765951
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 142.545974 -367.845038
[2,] -755.849856 142.545974
[3,] -867.441795 -755.849856
[4,] 560.090506 -867.441795
[5,] 258.633284 560.090506
[6,] -21.681750 258.633284
[7,] 407.599958 -21.681750
[8,] 252.620372 407.599958
[9,] 405.211517 252.620372
[10,] 79.964216 405.211517
[11,] 446.404091 79.964216
[12,] 129.410826 446.404091
[13,] -606.978872 129.410826
[14,] 35.270728 -606.978872
[15,] 225.786327 35.270728
[16,] 148.412194 225.786327
[17,] 74.437954 148.412194
[18,] 198.714102 74.437954
[19,] 416.784020 198.714102
[20,] -548.546197 416.784020
[21,] 287.846569 -548.546197
[22,] 47.219000 287.846569
[23,] -524.593762 47.219000
[24,] 429.066052 -524.593762
[25,] -622.421926 429.066052
[26,] 17.752532 -622.421926
[27,] 126.675345 17.752532
[28,] 451.697090 126.675345
[29,] -565.497026 451.697090
[30,] -682.045651 -565.497026
[31,] -173.104575 -682.045651
[32,] -66.408452 -173.104575
[33,] 412.727485 -66.408452
[34,] 64.523932 412.727485
[35,] 161.518052 64.523932
[36,] -63.933037 161.518052
[37,] -23.671115 -63.933037
[38,] 218.229532 -23.671115
[39,] 259.328424 218.229532
[40,] -590.685130 259.328424
[41,] 129.357385 -590.685130
[42,] 256.523187 129.357385
[43,] 194.443935 256.523187
[44,] 419.150196 194.443935
[45,] 156.909157 419.150196
[46,] -761.731196 156.909157
[47,] 75.279002 -761.731196
[48,] 263.145226 75.279002
[49,] 271.592274 263.145226
[50,] 144.947941 271.592274
[51,] 213.160922 144.947941
[52,] -749.497746 213.160922
[53,] 326.898396 -749.497746
[54,] -824.661691 326.898396
[55,] 5.349807 -824.661691
[56,] 160.498180 5.349807
[57,] 180.115167 160.498180
[58,] 41.373776 180.115167
[59,] 207.317713 41.373776
[60,] 257.828424 207.317713
[61,] -745.765951 257.828424
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 142.545974 -367.845038
2 -755.849856 142.545974
3 -867.441795 -755.849856
4 560.090506 -867.441795
5 258.633284 560.090506
6 -21.681750 258.633284
7 407.599958 -21.681750
8 252.620372 407.599958
9 405.211517 252.620372
10 79.964216 405.211517
11 446.404091 79.964216
12 129.410826 446.404091
13 -606.978872 129.410826
14 35.270728 -606.978872
15 225.786327 35.270728
16 148.412194 225.786327
17 74.437954 148.412194
18 198.714102 74.437954
19 416.784020 198.714102
20 -548.546197 416.784020
21 287.846569 -548.546197
22 47.219000 287.846569
23 -524.593762 47.219000
24 429.066052 -524.593762
25 -622.421926 429.066052
26 17.752532 -622.421926
27 126.675345 17.752532
28 451.697090 126.675345
29 -565.497026 451.697090
30 -682.045651 -565.497026
31 -173.104575 -682.045651
32 -66.408452 -173.104575
33 412.727485 -66.408452
34 64.523932 412.727485
35 161.518052 64.523932
36 -63.933037 161.518052
37 -23.671115 -63.933037
38 218.229532 -23.671115
39 259.328424 218.229532
40 -590.685130 259.328424
41 129.357385 -590.685130
42 256.523187 129.357385
43 194.443935 256.523187
44 419.150196 194.443935
45 156.909157 419.150196
46 -761.731196 156.909157
47 75.279002 -761.731196
48 263.145226 75.279002
49 271.592274 263.145226
50 144.947941 271.592274
51 213.160922 144.947941
52 -749.497746 213.160922
53 326.898396 -749.497746
54 -824.661691 326.898396
55 5.349807 -824.661691
56 160.498180 5.349807
57 180.115167 160.498180
58 41.373776 180.115167
59 207.317713 41.373776
60 257.828424 207.317713
61 -745.765951 257.828424
> 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/7jxfn1293054092.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8boeq1293054092.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9boeq1293054092.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10boeq1293054092.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11pycy1293054092.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/12bya41293054092.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/13pq8d1293054092.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/14ar611293054092.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/15wrn71293054092.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/16ha3v1293054092.tab")
+ }
>
> try(system("convert tmp/1xeyh1293054092.ps tmp/1xeyh1293054092.png",intern=TRUE))
character(0)
> try(system("convert tmp/2xeyh1293054092.ps tmp/2xeyh1293054092.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xeyh1293054092.ps tmp/3xeyh1293054092.png",intern=TRUE))
character(0)
> try(system("convert tmp/4q6fk1293054092.ps tmp/4q6fk1293054092.png",intern=TRUE))
character(0)
> try(system("convert tmp/5q6fk1293054092.ps tmp/5q6fk1293054092.png",intern=TRUE))
character(0)
> try(system("convert tmp/6q6fk1293054092.ps tmp/6q6fk1293054092.png",intern=TRUE))
character(0)
> try(system("convert tmp/7jxfn1293054092.ps tmp/7jxfn1293054092.png",intern=TRUE))
character(0)
> try(system("convert tmp/8boeq1293054092.ps tmp/8boeq1293054092.png",intern=TRUE))
character(0)
> try(system("convert tmp/9boeq1293054092.ps tmp/9boeq1293054092.png",intern=TRUE))
character(0)
> try(system("convert tmp/10boeq1293054092.ps tmp/10boeq1293054092.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.536 1.675 15.014