R version 2.8.0 (2008-10-20)
Copyright (C) 2008 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.
Natural language support but running in an English locale
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(6.3
+ ,2.0
+ ,4.5
+ ,1.000
+ ,6.600
+ ,42.0
+ ,3
+ ,1
+ ,3
+ ,2.1
+ ,1.8
+ ,69.0
+ ,2547.000
+ ,44.500
+ ,624.0
+ ,3
+ ,5
+ ,4
+ ,9.1
+ ,0.7
+ ,27.0
+ ,10.55
+ ,179.500
+ ,180.0
+ ,4
+ ,4
+ ,4
+ ,15.8
+ ,3.9
+ ,19.0
+ ,0.023
+ ,0.300
+ ,35.0
+ ,1
+ ,1
+ ,1
+ ,5.2
+ ,1.0
+ ,30.4
+ ,160.000
+ ,169.000
+ ,392.0
+ ,4
+ ,5
+ ,4
+ ,10.9
+ ,3.6
+ ,28.0
+ ,3.300
+ ,25.600
+ ,63.0
+ ,1
+ ,2
+ ,1
+ ,8.3
+ ,1.4
+ ,50.0
+ ,52.16
+ ,440.000
+ ,230.0
+ ,1
+ ,1
+ ,1
+ ,11.0
+ ,1.5
+ ,7.0
+ ,0.425
+ ,6.400
+ ,112.0
+ ,5
+ ,4
+ ,4
+ ,3.2
+ ,0.7
+ ,30.0
+ ,465.000
+ ,423.000
+ ,281.0
+ ,5
+ ,5
+ ,5
+ ,6.3
+ ,2.1
+ ,3.5
+ ,0.075
+ ,1.200
+ ,42.0
+ ,1
+ ,1
+ ,1
+ ,6.6
+ ,4.1
+ ,6.0
+ ,0.785
+ ,3.500
+ ,42.0
+ ,2
+ ,2
+ ,2
+ ,9.5
+ ,1.2
+ ,10.4
+ ,0.200
+ ,5.000
+ ,120.0
+ ,2
+ ,2
+ ,2
+ ,3.3
+ ,0.5
+ ,20.0
+ ,27.66
+ ,115.000
+ ,148.0
+ ,5
+ ,5
+ ,5
+ ,11.0
+ ,3.4
+ ,3.9
+ ,0.120
+ ,1.000
+ ,16.0
+ ,3
+ ,1
+ ,2
+ ,4.7
+ ,1.5
+ ,41.0
+ ,85.000
+ ,325.000
+ ,310.0
+ ,1
+ ,3
+ ,1
+ ,10.4
+ ,3.4
+ ,9.0
+ ,0.101
+ ,4.000
+ ,28.0
+ ,5
+ ,1
+ ,3
+ ,7.4
+ ,0.8
+ ,7.6
+ ,1.040
+ ,5.500
+ ,68.0
+ ,5
+ ,3
+ ,4
+ ,2.1
+ ,0.8
+ ,46.0
+ ,521.000
+ ,655.000
+ ,336.0
+ ,5
+ ,5
+ ,5
+ ,17.9
+ ,2.0
+ ,24.0
+ ,0.010
+ ,0.250
+ ,50.0
+ ,1
+ ,1
+ ,1
+ ,6.1
+ ,1.9
+ ,100.0
+ ,62.000
+ ,1320.000
+ ,267.0
+ ,1
+ ,1
+ ,1
+ ,11.9
+ ,1.3
+ ,3.2
+ ,0.023
+ ,0.400
+ ,19.0
+ ,4
+ ,1
+ ,3
+ ,13.8
+ ,5.6
+ ,5.0
+ ,1.700
+ ,6.300
+ ,12.0
+ ,2
+ ,1
+ ,1
+ ,14.3
+ ,3.1
+ ,6.5
+ ,3.500
+ ,10.800
+ ,120.0
+ ,2
+ ,1
+ ,1
+ ,15.2
+ ,1.8
+ ,12.0
+ ,0.480
+ ,15.500
+ ,140.0
+ ,2
+ ,2
+ ,2
+ ,10.0
+ ,0.9
+ ,20.2
+ ,10.000
+ ,115.000
+ ,170.0
+ ,4
+ ,4
+ ,4
+ ,11.9
+ ,1.8
+ ,13.0
+ ,1.620
+ ,11.400
+ ,17.0
+ ,2
+ ,1
+ ,2
+ ,6.5
+ ,1.9
+ ,27.0
+ ,192.000
+ ,180.000
+ ,115.0
+ ,4
+ ,4
+ ,4
+ ,7.5
+ ,0.9
+ ,18.0
+ ,2.500
+ ,12.300
+ ,31.0
+ ,5
+ ,5
+ ,5
+ ,10.6
+ ,2.6
+ ,4.7
+ ,0.280
+ ,1.900
+ ,21.0
+ ,3
+ ,1
+ ,3
+ ,7.4
+ ,2.4
+ ,9.8
+ ,4.235
+ ,50.400
+ ,52.0
+ ,1
+ ,1
+ ,1
+ ,8.4
+ ,1.2
+ ,29.0
+ ,6.800
+ ,179.000
+ ,164.0
+ ,2
+ ,3
+ ,2
+ ,5.7
+ ,0.9
+ ,7.0
+ ,0.750
+ ,12.300
+ ,225.0
+ ,2
+ ,2
+ ,2
+ ,4.9
+ ,0.5
+ ,6.0
+ ,3.600
+ ,21.000
+ ,225.0
+ ,3
+ ,2
+ ,3
+ ,3.2
+ ,0.6
+ ,20.0
+ ,55.500
+ ,175.000
+ ,151.0
+ ,5
+ ,5
+ ,5
+ ,11.0
+ ,2.3
+ ,4.5
+ ,0.900
+ ,2.600
+ ,60.0
+ ,2
+ ,1
+ ,2
+ ,4.9
+ ,0.5
+ ,7.5
+ ,2.000
+ ,12.300
+ ,200.0
+ ,3
+ ,1
+ ,3
+ ,13.2
+ ,2.6
+ ,2.3
+ ,0.104
+ ,2.500
+ ,46.0
+ ,3
+ ,2
+ ,2
+ ,9.7
+ ,0.6
+ ,24.0
+ ,4.190
+ ,58.000
+ ,210.0
+ ,4
+ ,3
+ ,4
+ ,12.8
+ ,6.6
+ ,3.0
+ ,3.500
+ ,3.900
+ ,14.0
+ ,2
+ ,1
+ ,1)
+ ,dim=c(9
+ ,39)
+ ,dimnames=list(c('SWS'
+ ,'PS'
+ ,'L'
+ ,'Wb'
+ ,'Wbr'
+ ,'Tg'
+ ,'P'
+ ,'S'
+ ,'D')
+ ,1:39))
> y <- array(NA,dim=c(9,39),dimnames=list(c('SWS','PS','L','Wb','Wbr','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 Wb Wbr 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 44.50 624 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 0.425 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 0.010 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 3.1 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 12.30 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 Wb Wbr Tg
3.879814 0.020766 -0.023114 0.002442 0.001835 -0.007289
P S D
0.753428 0.379291 -1.584598
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.254479 -0.502961 0.009168 0.335994 2.308514
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.8798141 0.8054389 4.817 3.90e-05 ***
SWS 0.0207658 0.0592489 0.350 0.728425
L -0.0231143 0.0242532 -0.953 0.348187
Wb 0.0024421 0.0006486 3.765 0.000725 ***
Wbr 0.0018346 0.0016760 1.095 0.282384
Tg -0.0072885 0.0023016 -3.167 0.003528 **
P 0.7534277 0.3532113 2.133 0.041215 *
S 0.3792914 0.1984211 1.912 0.065529 .
D -1.5845975 0.4268905 -3.712 0.000837 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.8727 on 30 degrees of freedom
Multiple R-squared: 0.6957, Adjusted R-squared: 0.6145
F-statistic: 8.572 on 8 and 30 DF, p-value: 5.313e-06
> 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,] 0.8491300 0.3017400 0.1508700
[2,] 0.7845484 0.4309033 0.2154516
[3,] 0.6939939 0.6120121 0.3060061
[4,] 0.5601247 0.8797506 0.4398753
[5,] 0.4455383 0.8910766 0.5544617
[6,] 0.4936165 0.9872330 0.5063835
[7,] 0.4018405 0.8036810 0.5981595
[8,] 0.3718248 0.7436496 0.6281752
[9,] 0.2634628 0.5269255 0.7365372
[10,] 0.4381427 0.8762854 0.5618573
[11,] 0.5050118 0.9899763 0.4949882
[12,] 0.4396966 0.8793932 0.5603034
[13,] 0.3140357 0.6280715 0.6859643
[14,] 0.2170890 0.4341781 0.7829110
[15,] 0.1720083 0.3440166 0.8279917
[16,] 0.1631114 0.3262228 0.8368886
> postscript(file="/var/www/html/freestat/rcomp/tmp/17asd1292249266.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/2iksg1292249266.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/freestat/rcomp/tmp/3iksg1292249266.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/4iksg1292249266.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/5ab9j1292249266.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 6
0.499160814 -0.100417161 0.019673723 0.837627151 1.299419782 0.617776746
7 8 9 10 11 12
-0.302822854 -0.588817781 -0.156965311 -1.074127347 1.423353558 -0.867983845
13 14 15 16 17 18
0.073509656 0.026017001 -0.380814249 0.316106043 -1.141446289 0.174190874
19 20 21 22 23 24
-0.880958573 0.029771699 -1.254479182 1.319392773 -0.381810815 -0.223542849
25 26 27 28 29 30
0.090597299 -0.644359224 0.355882831 -0.262835509 0.871812929 -0.678886070
31 32 33 34 35 36
-0.809151176 -0.417104239 -0.015356921 0.019388895 0.009167622 0.236261339
37 38 39
-1.019999368 0.674253615 2.308514414
> postscript(file="/var/www/html/freestat/rcomp/tmp/6ab9j1292249266.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 0.499160814 NA
1 -0.100417161 0.499160814
2 0.019673723 -0.100417161
3 0.837627151 0.019673723
4 1.299419782 0.837627151
5 0.617776746 1.299419782
6 -0.302822854 0.617776746
7 -0.588817781 -0.302822854
8 -0.156965311 -0.588817781
9 -1.074127347 -0.156965311
10 1.423353558 -1.074127347
11 -0.867983845 1.423353558
12 0.073509656 -0.867983845
13 0.026017001 0.073509656
14 -0.380814249 0.026017001
15 0.316106043 -0.380814249
16 -1.141446289 0.316106043
17 0.174190874 -1.141446289
18 -0.880958573 0.174190874
19 0.029771699 -0.880958573
20 -1.254479182 0.029771699
21 1.319392773 -1.254479182
22 -0.381810815 1.319392773
23 -0.223542849 -0.381810815
24 0.090597299 -0.223542849
25 -0.644359224 0.090597299
26 0.355882831 -0.644359224
27 -0.262835509 0.355882831
28 0.871812929 -0.262835509
29 -0.678886070 0.871812929
30 -0.809151176 -0.678886070
31 -0.417104239 -0.809151176
32 -0.015356921 -0.417104239
33 0.019388895 -0.015356921
34 0.009167622 0.019388895
35 0.236261339 0.009167622
36 -1.019999368 0.236261339
37 0.674253615 -1.019999368
38 2.308514414 0.674253615
39 NA 2.308514414
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.100417161 0.499160814
[2,] 0.019673723 -0.100417161
[3,] 0.837627151 0.019673723
[4,] 1.299419782 0.837627151
[5,] 0.617776746 1.299419782
[6,] -0.302822854 0.617776746
[7,] -0.588817781 -0.302822854
[8,] -0.156965311 -0.588817781
[9,] -1.074127347 -0.156965311
[10,] 1.423353558 -1.074127347
[11,] -0.867983845 1.423353558
[12,] 0.073509656 -0.867983845
[13,] 0.026017001 0.073509656
[14,] -0.380814249 0.026017001
[15,] 0.316106043 -0.380814249
[16,] -1.141446289 0.316106043
[17,] 0.174190874 -1.141446289
[18,] -0.880958573 0.174190874
[19,] 0.029771699 -0.880958573
[20,] -1.254479182 0.029771699
[21,] 1.319392773 -1.254479182
[22,] -0.381810815 1.319392773
[23,] -0.223542849 -0.381810815
[24,] 0.090597299 -0.223542849
[25,] -0.644359224 0.090597299
[26,] 0.355882831 -0.644359224
[27,] -0.262835509 0.355882831
[28,] 0.871812929 -0.262835509
[29,] -0.678886070 0.871812929
[30,] -0.809151176 -0.678886070
[31,] -0.417104239 -0.809151176
[32,] -0.015356921 -0.417104239
[33,] 0.019388895 -0.015356921
[34,] 0.009167622 0.019388895
[35,] 0.236261339 0.009167622
[36,] -1.019999368 0.236261339
[37,] 0.674253615 -1.019999368
[38,] 2.308514414 0.674253615
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.100417161 0.499160814
2 0.019673723 -0.100417161
3 0.837627151 0.019673723
4 1.299419782 0.837627151
5 0.617776746 1.299419782
6 -0.302822854 0.617776746
7 -0.588817781 -0.302822854
8 -0.156965311 -0.588817781
9 -1.074127347 -0.156965311
10 1.423353558 -1.074127347
11 -0.867983845 1.423353558
12 0.073509656 -0.867983845
13 0.026017001 0.073509656
14 -0.380814249 0.026017001
15 0.316106043 -0.380814249
16 -1.141446289 0.316106043
17 0.174190874 -1.141446289
18 -0.880958573 0.174190874
19 0.029771699 -0.880958573
20 -1.254479182 0.029771699
21 1.319392773 -1.254479182
22 -0.381810815 1.319392773
23 -0.223542849 -0.381810815
24 0.090597299 -0.223542849
25 -0.644359224 0.090597299
26 0.355882831 -0.644359224
27 -0.262835509 0.355882831
28 0.871812929 -0.262835509
29 -0.678886070 0.871812929
30 -0.809151176 -0.678886070
31 -0.417104239 -0.809151176
32 -0.015356921 -0.417104239
33 0.019388895 -0.015356921
34 0.009167622 0.019388895
35 0.236261339 0.009167622
36 -1.019999368 0.236261339
37 0.674253615 -1.019999368
38 2.308514414 0.674253615
> 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/freestat/rcomp/tmp/7l2841292249266.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/8l2841292249266.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/freestat/rcomp/tmp/9eb871292249266.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
Warning messages:
1: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced
2: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/freestat/rcomp/tmp/10eb871292249266.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/freestat/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/freestat/rcomp/tmp/11hc6d1292249266.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/freestat/rcomp/tmp/122c4j1292249266.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/freestat/rcomp/tmp/139dju1292249266.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/freestat/rcomp/tmp/14cwi01292249266.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/freestat/rcomp/tmp/15n5hl1292249266.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/freestat/rcomp/tmp/161ffu1292249266.tab")
+ }
>
> try(system("convert tmp/17asd1292249266.ps tmp/17asd1292249266.png",intern=TRUE))
character(0)
> try(system("convert tmp/2iksg1292249266.ps tmp/2iksg1292249266.png",intern=TRUE))
character(0)
> try(system("convert tmp/3iksg1292249266.ps tmp/3iksg1292249266.png",intern=TRUE))
character(0)
> try(system("convert tmp/4iksg1292249266.ps tmp/4iksg1292249266.png",intern=TRUE))
character(0)
> try(system("convert tmp/5ab9j1292249266.ps tmp/5ab9j1292249266.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ab9j1292249266.ps tmp/6ab9j1292249266.png",intern=TRUE))
character(0)
> try(system("convert tmp/7l2841292249266.ps tmp/7l2841292249266.png",intern=TRUE))
character(0)
> try(system("convert tmp/8l2841292249266.ps tmp/8l2841292249266.png",intern=TRUE))
character(0)
> try(system("convert tmp/9eb871292249266.ps tmp/9eb871292249266.png",intern=TRUE))
character(0)
> try(system("convert tmp/10eb871292249266.ps tmp/10eb871292249266.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.654 2.478 3.993