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.
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Type 'contributors()' for more information and
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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(6.3
+ ,2
+ ,4.5
+ ,1
+ ,6.6
+ ,42
+ ,3
+ ,1
+ ,3
+ ,2.1
+ ,1.8
+ ,69
+ ,2547
+ ,4603
+ ,624
+ ,3
+ ,5
+ ,4
+ ,9.1
+ ,0.7
+ ,27
+ ,10.55
+ ,179.5
+ ,180
+ ,4
+ ,4
+ ,4
+ ,15.8
+ ,3.9
+ ,19
+ ,0.023
+ ,0.3
+ ,35
+ ,1
+ ,1
+ ,1
+ ,5.2
+ ,1
+ ,30.4
+ ,160
+ ,169
+ ,392
+ ,4
+ ,5
+ ,4
+ ,10.9
+ ,3.6
+ ,28
+ ,3.3
+ ,25.6
+ ,63
+ ,1
+ ,2
+ ,1
+ ,8.3
+ ,1.4
+ ,50
+ ,52.16
+ ,440
+ ,230
+ ,1
+ ,1
+ ,1
+ ,11
+ ,1.5
+ ,7
+ ,0.42
+ ,6.4
+ ,112
+ ,5
+ ,4
+ ,4
+ ,3.2
+ ,0.7
+ ,30
+ ,465
+ ,423
+ ,281
+ ,5
+ ,5
+ ,5
+ ,6.3
+ ,2.1
+ ,3.5
+ ,0.075
+ ,1.2
+ ,42
+ ,1
+ ,1
+ ,1
+ ,6.6
+ ,4.1
+ ,6
+ ,0.785
+ ,3.5
+ ,42
+ ,2
+ ,2
+ ,2
+ ,9.5
+ ,1.2
+ ,10.4
+ ,0.2
+ ,5
+ ,120
+ ,2
+ ,2
+ ,2
+ ,3.3
+ ,0.5
+ ,20
+ ,27.66
+ ,115
+ ,148
+ ,5
+ ,5
+ ,5
+ ,11
+ ,3.4
+ ,3.9
+ ,0.12
+ ,1
+ ,16
+ ,3
+ ,1
+ ,2
+ ,4.7
+ ,1.5
+ ,41
+ ,85
+ ,325
+ ,310
+ ,1
+ ,3
+ ,1
+ ,10.4
+ ,3.4
+ ,9
+ ,0.101
+ ,4
+ ,28
+ ,5
+ ,1
+ ,3
+ ,7.4
+ ,0.8
+ ,7.6
+ ,1.04
+ ,5.5
+ ,68
+ ,5
+ ,3
+ ,4
+ ,2.1
+ ,0.8
+ ,46
+ ,521
+ ,655
+ ,336
+ ,5
+ ,5
+ ,5
+ ,17.9
+ ,2
+ ,24
+ ,0.1
+ ,0.25
+ ,50
+ ,1
+ ,1
+ ,1
+ ,6.1
+ ,1.9
+ ,100
+ ,62
+ ,1320
+ ,267
+ ,1
+ ,1
+ ,1
+ ,11.9
+ ,1.3
+ ,3.2
+ ,0.023
+ ,0.4
+ ,19
+ ,4
+ ,1
+ ,3
+ ,13.8
+ ,5.6
+ ,5
+ ,1.7
+ ,6.3
+ ,12
+ ,2
+ ,1
+ ,1
+ ,14.3
+ ,14.3
+ ,6.5
+ ,3.5
+ ,10.8
+ ,120
+ ,2
+ ,1
+ ,1
+ ,15.2
+ ,1.8
+ ,12
+ ,0.48
+ ,15.5
+ ,140
+ ,2
+ ,2
+ ,2
+ ,10
+ ,0.9
+ ,20.2
+ ,10
+ ,115
+ ,170
+ ,4
+ ,4
+ ,4
+ ,11.9
+ ,1.8
+ ,13
+ ,1.62
+ ,11.4
+ ,17
+ ,2
+ ,1
+ ,2
+ ,6.5
+ ,1.9
+ ,27
+ ,192
+ ,180
+ ,115
+ ,4
+ ,4
+ ,4
+ ,7.5
+ ,0.9
+ ,18
+ ,2.5
+ ,12.1
+ ,31
+ ,5
+ ,5
+ ,5
+ ,10.6
+ ,2.6
+ ,4.7
+ ,0.28
+ ,1.9
+ ,21
+ ,3
+ ,1
+ ,3
+ ,7.4
+ ,2.4
+ ,9.8
+ ,4.235
+ ,50.4
+ ,52
+ ,1
+ ,1
+ ,1
+ ,8.4
+ ,1.2
+ ,29
+ ,6.8
+ ,179
+ ,164
+ ,2
+ ,3
+ ,2
+ ,5.7
+ ,0.9
+ ,7
+ ,0.75
+ ,12.3
+ ,225
+ ,2
+ ,2
+ ,2
+ ,4.9
+ ,0.5
+ ,6
+ ,3.6
+ ,21
+ ,225
+ ,3
+ ,2
+ ,3
+ ,3.2
+ ,0.6
+ ,20
+ ,55.5
+ ,175
+ ,151
+ ,5
+ ,5
+ ,5
+ ,11
+ ,2.3
+ ,4.5
+ ,0.9
+ ,2.6
+ ,60
+ ,2
+ ,1
+ ,2
+ ,4.9
+ ,0.5
+ ,7.5
+ ,2
+ ,12.3
+ ,200
+ ,3
+ ,1
+ ,3
+ ,13.2
+ ,2.6
+ ,2.3
+ ,0.104
+ ,2.5
+ ,46
+ ,3
+ ,2
+ ,2
+ ,9.7
+ ,0.6
+ ,24
+ ,4.19
+ ,58
+ ,210
+ ,4
+ ,3
+ ,4
+ ,12.8
+ ,6.6
+ ,3
+ ,3.5
+ ,3.9
+ ,14
+ ,2
+ ,1
+ ,1)
+ ,dim=c(9
+ ,39)
+ ,dimnames=list(c('SWS'
+ ,'PS'
+ ,'L'
+ ,'BW'
+ ,'BRW'
+ ,'Tg'
+ ,'P'
+ ,'S'
+ ,'D')
+ ,1:39))
> y <- array(NA,dim=c(9,39),dimnames=list(c('SWS','PS','L','BW','BRW','Tg','P','S','D'),1:39))
> 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
PS SWS L BW BRW Tg P S D
1 2.0 6.3 4.5 1.000 6.60 42 3 1 3
2 1.8 2.1 69.0 2547.000 4603.00 624 3 5 4
3 0.7 9.1 27.0 10.550 179.50 180 4 4 4
4 3.9 15.8 19.0 0.023 0.30 35 1 1 1
5 1.0 5.2 30.4 160.000 169.00 392 4 5 4
6 3.6 10.9 28.0 3.300 25.60 63 1 2 1
7 1.4 8.3 50.0 52.160 440.00 230 1 1 1
8 1.5 11.0 7.0 0.420 6.40 112 5 4 4
9 0.7 3.2 30.0 465.000 423.00 281 5 5 5
10 2.1 6.3 3.5 0.075 1.20 42 1 1 1
11 4.1 6.6 6.0 0.785 3.50 42 2 2 2
12 1.2 9.5 10.4 0.200 5.00 120 2 2 2
13 0.5 3.3 20.0 27.660 115.00 148 5 5 5
14 3.4 11.0 3.9 0.120 1.00 16 3 1 2
15 1.5 4.7 41.0 85.000 325.00 310 1 3 1
16 3.4 10.4 9.0 0.101 4.00 28 5 1 3
17 0.8 7.4 7.6 1.040 5.50 68 5 3 4
18 0.8 2.1 46.0 521.000 655.00 336 5 5 5
19 2.0 17.9 24.0 0.100 0.25 50 1 1 1
20 1.9 6.1 100.0 62.000 1320.00 267 1 1 1
21 1.3 11.9 3.2 0.023 0.40 19 4 1 3
22 5.6 13.8 5.0 1.700 6.30 12 2 1 1
23 14.3 14.3 6.5 3.500 10.80 120 2 1 1
24 1.8 15.2 12.0 0.480 15.50 140 2 2 2
25 0.9 10.0 20.2 10.000 115.00 170 4 4 4
26 1.8 11.9 13.0 1.620 11.40 17 2 1 2
27 1.9 6.5 27.0 192.000 180.00 115 4 4 4
28 0.9 7.5 18.0 2.500 12.10 31 5 5 5
29 2.6 10.6 4.7 0.280 1.90 21 3 1 3
30 2.4 7.4 9.8 4.235 50.40 52 1 1 1
31 1.2 8.4 29.0 6.800 179.00 164 2 3 2
32 0.9 5.7 7.0 0.750 12.30 225 2 2 2
33 0.5 4.9 6.0 3.600 21.00 225 3 2 3
34 0.6 3.2 20.0 55.500 175.00 151 5 5 5
35 2.3 11.0 4.5 0.900 2.60 60 2 1 2
36 0.5 4.9 7.5 2.000 12.30 200 3 1 3
37 2.6 13.2 2.3 0.104 2.50 46 3 2 2
38 0.6 9.7 24.0 4.190 58.00 210 4 3 4
39 6.6 12.8 3.0 3.500 3.90 14 2 1 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) SWS L BW BRW Tg
3.1953114 0.0908237 -0.0094174 0.0030686 -0.0007954 -0.0009269
P S D
1.8050127 0.3744348 -2.8907237
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-2.110677 -1.104072 0.002009 0.708669 8.882466
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.1953114 1.8469505 1.730 0.09390 .
SWS 0.0908237 0.1218993 0.745 0.46203
L -0.0094174 0.0364989 -0.258 0.79815
BW 0.0030686 0.0043307 0.709 0.48406
BRW -0.0007954 0.0025864 -0.308 0.76056
Tg -0.0009269 0.0052989 -0.175 0.86231
P 1.8050127 0.7523052 2.399 0.02284 *
S 0.3744348 0.4658796 0.804 0.42788
D -2.8907237 0.9533107 -3.032 0.00497 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.997 on 30 degrees of freedom
Multiple R-squared: 0.463, Adjusted R-squared: 0.3198
F-statistic: 3.233 on 8 and 30 DF, p-value: 0.009005
> 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,] 0.1716267081 0.3432534162 0.828373292
[2,] 0.0750712231 0.1501424462 0.924928777
[3,] 0.0325524905 0.0651049809 0.967447510
[4,] 0.0118644031 0.0237288062 0.988135597
[5,] 0.0044385889 0.0088771779 0.995561411
[6,] 0.0029666547 0.0059333094 0.997033345
[7,] 0.0009843710 0.0019687420 0.999015629
[8,] 0.0007925811 0.0015851623 0.999207419
[9,] 0.0002831707 0.0005663413 0.999716829
[10,] 0.0002855193 0.0005710386 0.999714481
[11,] 0.0004878620 0.0009757240 0.999512138
[12,] 0.9935129875 0.0129740249 0.006487012
[13,] 0.9827931069 0.0344137861 0.017206893
[14,] 0.9577196445 0.0845607110 0.042280356
[15,] 0.9168598158 0.1662803684 0.083140184
[16,] 0.8686859140 0.2626281721 0.131314086
> postscript(file="/var/www/html/rcomp/tmp/105gk1292343946.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/205gk1292343946.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/305gk1292343946.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4sfgn1292343946.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5sfgn1292343946.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 = 39
Frequency = 1
1 2 3 4 5
1.198687e+00 -2.365497e-01 5.481719e-02 1.924913e-01 9.616312e-02
6 7 8 9 10
8.387151e-02 -9.638821e-01 -1.480742e+00 2.229824e-01 -8.836091e-01
11 12 13 14 15
1.823614e+00 -1.223051e+00 8.934791e-01 -7.504119e-01 -1.488638e+00
16 17 18 19 20
-1.353623e+00 -1.517094e+00 6.372446e-01 -1.837524e+00 9.108786e-01
21 22 23 24 25
-1.850433e+00 1.155896e-01 8.882466e+00 -1.099647e+00 5.015086e-02
26 27 28 29 30
-5.368454e-01 8.743095e-01 7.800933e-01 1.389035e+00 -5.885466e-01
31 32 33 34 35
-1.163480e+00 -1.108496e+00 -3.613687e-01 9.676379e-01 -8.576374e-05
36 37 38 39
2.009193e-03 -2.110677e+00 1.971845e-01 1.182000e+00
> postscript(file="/var/www/html/rcomp/tmp/6sfgn1292343946.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 = 39
Frequency = 1
lag(myerror, k = 1) myerror
0 1.198687e+00 NA
1 -2.365497e-01 1.198687e+00
2 5.481719e-02 -2.365497e-01
3 1.924913e-01 5.481719e-02
4 9.616312e-02 1.924913e-01
5 8.387151e-02 9.616312e-02
6 -9.638821e-01 8.387151e-02
7 -1.480742e+00 -9.638821e-01
8 2.229824e-01 -1.480742e+00
9 -8.836091e-01 2.229824e-01
10 1.823614e+00 -8.836091e-01
11 -1.223051e+00 1.823614e+00
12 8.934791e-01 -1.223051e+00
13 -7.504119e-01 8.934791e-01
14 -1.488638e+00 -7.504119e-01
15 -1.353623e+00 -1.488638e+00
16 -1.517094e+00 -1.353623e+00
17 6.372446e-01 -1.517094e+00
18 -1.837524e+00 6.372446e-01
19 9.108786e-01 -1.837524e+00
20 -1.850433e+00 9.108786e-01
21 1.155896e-01 -1.850433e+00
22 8.882466e+00 1.155896e-01
23 -1.099647e+00 8.882466e+00
24 5.015086e-02 -1.099647e+00
25 -5.368454e-01 5.015086e-02
26 8.743095e-01 -5.368454e-01
27 7.800933e-01 8.743095e-01
28 1.389035e+00 7.800933e-01
29 -5.885466e-01 1.389035e+00
30 -1.163480e+00 -5.885466e-01
31 -1.108496e+00 -1.163480e+00
32 -3.613687e-01 -1.108496e+00
33 9.676379e-01 -3.613687e-01
34 -8.576374e-05 9.676379e-01
35 2.009193e-03 -8.576374e-05
36 -2.110677e+00 2.009193e-03
37 1.971845e-01 -2.110677e+00
38 1.182000e+00 1.971845e-01
39 NA 1.182000e+00
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -2.365497e-01 1.198687e+00
[2,] 5.481719e-02 -2.365497e-01
[3,] 1.924913e-01 5.481719e-02
[4,] 9.616312e-02 1.924913e-01
[5,] 8.387151e-02 9.616312e-02
[6,] -9.638821e-01 8.387151e-02
[7,] -1.480742e+00 -9.638821e-01
[8,] 2.229824e-01 -1.480742e+00
[9,] -8.836091e-01 2.229824e-01
[10,] 1.823614e+00 -8.836091e-01
[11,] -1.223051e+00 1.823614e+00
[12,] 8.934791e-01 -1.223051e+00
[13,] -7.504119e-01 8.934791e-01
[14,] -1.488638e+00 -7.504119e-01
[15,] -1.353623e+00 -1.488638e+00
[16,] -1.517094e+00 -1.353623e+00
[17,] 6.372446e-01 -1.517094e+00
[18,] -1.837524e+00 6.372446e-01
[19,] 9.108786e-01 -1.837524e+00
[20,] -1.850433e+00 9.108786e-01
[21,] 1.155896e-01 -1.850433e+00
[22,] 8.882466e+00 1.155896e-01
[23,] -1.099647e+00 8.882466e+00
[24,] 5.015086e-02 -1.099647e+00
[25,] -5.368454e-01 5.015086e-02
[26,] 8.743095e-01 -5.368454e-01
[27,] 7.800933e-01 8.743095e-01
[28,] 1.389035e+00 7.800933e-01
[29,] -5.885466e-01 1.389035e+00
[30,] -1.163480e+00 -5.885466e-01
[31,] -1.108496e+00 -1.163480e+00
[32,] -3.613687e-01 -1.108496e+00
[33,] 9.676379e-01 -3.613687e-01
[34,] -8.576374e-05 9.676379e-01
[35,] 2.009193e-03 -8.576374e-05
[36,] -2.110677e+00 2.009193e-03
[37,] 1.971845e-01 -2.110677e+00
[38,] 1.182000e+00 1.971845e-01
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -2.365497e-01 1.198687e+00
2 5.481719e-02 -2.365497e-01
3 1.924913e-01 5.481719e-02
4 9.616312e-02 1.924913e-01
5 8.387151e-02 9.616312e-02
6 -9.638821e-01 8.387151e-02
7 -1.480742e+00 -9.638821e-01
8 2.229824e-01 -1.480742e+00
9 -8.836091e-01 2.229824e-01
10 1.823614e+00 -8.836091e-01
11 -1.223051e+00 1.823614e+00
12 8.934791e-01 -1.223051e+00
13 -7.504119e-01 8.934791e-01
14 -1.488638e+00 -7.504119e-01
15 -1.353623e+00 -1.488638e+00
16 -1.517094e+00 -1.353623e+00
17 6.372446e-01 -1.517094e+00
18 -1.837524e+00 6.372446e-01
19 9.108786e-01 -1.837524e+00
20 -1.850433e+00 9.108786e-01
21 1.155896e-01 -1.850433e+00
22 8.882466e+00 1.155896e-01
23 -1.099647e+00 8.882466e+00
24 5.015086e-02 -1.099647e+00
25 -5.368454e-01 5.015086e-02
26 8.743095e-01 -5.368454e-01
27 7.800933e-01 8.743095e-01
28 1.389035e+00 7.800933e-01
29 -5.885466e-01 1.389035e+00
30 -1.163480e+00 -5.885466e-01
31 -1.108496e+00 -1.163480e+00
32 -3.613687e-01 -1.108496e+00
33 9.676379e-01 -3.613687e-01
34 -8.576374e-05 9.676379e-01
35 2.009193e-03 -8.576374e-05
36 -2.110677e+00 2.009193e-03
37 1.971845e-01 -2.110677e+00
38 1.182000e+00 1.971845e-01
> 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/7lox81292343946.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8efwt1292343946.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9efwt1292343946.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
Warning messages:
1: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced
2: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10efwt1292343946.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11spck1292343946.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/123ybn1292343946.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/13rh8z1292343946.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/14dip41292343946.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/15596p1292343946.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/162j4z1292343946.tab")
+ }
>
> try(system("convert tmp/105gk1292343946.ps tmp/105gk1292343946.png",intern=TRUE))
character(0)
> try(system("convert tmp/205gk1292343946.ps tmp/205gk1292343946.png",intern=TRUE))
character(0)
> try(system("convert tmp/305gk1292343946.ps tmp/305gk1292343946.png",intern=TRUE))
character(0)
> try(system("convert tmp/4sfgn1292343946.ps tmp/4sfgn1292343946.png",intern=TRUE))
character(0)
> try(system("convert tmp/5sfgn1292343946.ps tmp/5sfgn1292343946.png",intern=TRUE))
character(0)
> try(system("convert tmp/6sfgn1292343946.ps tmp/6sfgn1292343946.png",intern=TRUE))
character(0)
> try(system("convert tmp/7lox81292343946.ps tmp/7lox81292343946.png",intern=TRUE))
character(0)
> try(system("convert tmp/8efwt1292343946.ps tmp/8efwt1292343946.png",intern=TRUE))
character(0)
> try(system("convert tmp/9efwt1292343946.ps tmp/9efwt1292343946.png",intern=TRUE))
character(0)
> try(system("convert tmp/10efwt1292343946.ps tmp/10efwt1292343946.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.276 1.625 5.363