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(612613,0,611324,0,594167,0,595454,0,590865,0,589379,0,584428,0,573100,0,567456,0,569028,0,620735,0,628884,0,628232,0,612117,0,595404,0,597141,0,593408,0,590072,0,579799,0,574205,0,572775,0,572942,0,619567,0,625809,0,619916,0,587625,0,565742,0,557274,0,560576,1,548854,1,531673,1,525919,1,511038,1,498662,1,555362,1,564591,1,541657,1,527070,1,509846,1,514258,1,516922,1,507561,1,492622,1,490243,1,469357,1,477580,1,528379,1,533590,1,517945,1,506174,1,501866,1,516141,1,528222,1,532638,1,536322,1,536535,1,523597,1,536214,1,586570,1,596594,1),dim=c(2,60),dimnames=list(c('wlh','dummies'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('wlh','dummies'),1:60))
> 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 = '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
wlh dummies
1 612613 0
2 611324 0
3 594167 0
4 595454 0
5 590865 0
6 589379 0
7 584428 0
8 573100 0
9 567456 0
10 569028 0
11 620735 0
12 628884 0
13 628232 0
14 612117 0
15 595404 0
16 597141 0
17 593408 0
18 590072 0
19 579799 0
20 574205 0
21 572775 0
22 572942 0
23 619567 0
24 625809 0
25 619916 0
26 587625 0
27 565742 0
28 557274 0
29 560576 1
30 548854 1
31 531673 1
32 525919 1
33 511038 1
34 498662 1
35 555362 1
36 564591 1
37 541657 1
38 527070 1
39 509846 1
40 514258 1
41 516922 1
42 507561 1
43 492622 1
44 490243 1
45 469357 1
46 477580 1
47 528379 1
48 533590 1
49 517945 1
50 506174 1
51 501866 1
52 516141 1
53 528222 1
54 532638 1
55 536322 1
56 536535 1
57 523597 1
58 536214 1
59 586570 1
60 596594 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) dummies
593909 -68141
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-56411.1 -18553.8 -175.2 16270.4 70825.9
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 593909 4729 125.58 < 2e-16 ***
dummies -68141 6476 -10.52 4.54e-15 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 25020 on 58 degrees of freedom
Multiple R-squared: 0.6562, Adjusted R-squared: 0.6503
F-statistic: 110.7 on 1 and 58 DF, p-value: 4.544e-15
> 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,] 0.11038937 0.22077875 0.8896106
[2,] 0.05967425 0.11934851 0.9403257
[3,] 0.04096991 0.08193981 0.9590301
[4,] 0.05945767 0.11891534 0.9405423
[5,] 0.08619361 0.17238722 0.9138064
[6,] 0.08707604 0.17415208 0.9129240
[7,] 0.13626899 0.27253797 0.8637310
[8,] 0.23182847 0.46365693 0.7681715
[9,] 0.30119676 0.60239352 0.6988032
[10,] 0.25252527 0.50505054 0.7474747
[11,] 0.18329625 0.36659250 0.8167037
[12,] 0.12833047 0.25666095 0.8716695
[13,] 0.08740199 0.17480398 0.9125980
[14,] 0.05892949 0.11785898 0.9410705
[15,] 0.04667785 0.09335570 0.9533221
[16,] 0.04277318 0.08554637 0.9572268
[17,] 0.04003191 0.08006381 0.9599681
[18,] 0.03663405 0.07326811 0.9633659
[19,] 0.03994963 0.07989926 0.9600504
[20,] 0.05833848 0.11667696 0.9416615
[21,] 0.07338811 0.14677622 0.9266119
[22,] 0.05656212 0.11312425 0.9434379
[23,] 0.05972883 0.11945767 0.9402712
[24,] 0.07452849 0.14905698 0.9254715
[25,] 0.06641888 0.13283776 0.9335811
[26,] 0.05326233 0.10652466 0.9467377
[27,] 0.04220201 0.08440403 0.9577980
[28,] 0.03219911 0.06439822 0.9678009
[29,] 0.03041168 0.06082335 0.9695883
[30,] 0.03766538 0.07533075 0.9623346
[31,] 0.03993927 0.07987855 0.9600607
[32,] 0.05827568 0.11655136 0.9417243
[33,] 0.04418242 0.08836485 0.9558176
[34,] 0.03019442 0.06038884 0.9698056
[35,] 0.02534220 0.05068439 0.9746578
[36,] 0.01834386 0.03668773 0.9816561
[37,] 0.01216616 0.02433232 0.9878338
[38,] 0.00949640 0.01899280 0.9905036
[39,] 0.01279122 0.02558244 0.9872088
[40,] 0.01859144 0.03718287 0.9814086
[41,] 0.08827936 0.17655872 0.9117206
[42,] 0.22902904 0.45805807 0.7709710
[43,] 0.16912517 0.33825033 0.8308748
[44,] 0.11925023 0.23850047 0.8807498
[45,] 0.08899551 0.17799102 0.9110045
[46,] 0.09189799 0.18379599 0.9081020
[47,] 0.13035947 0.26071894 0.8696405
[48,] 0.12806740 0.25613480 0.8719326
[49,] 0.09739833 0.19479665 0.9026017
[50,] 0.06743887 0.13487774 0.9325611
[51,] 0.04185931 0.08371862 0.9581407
> postscript(file="/var/www/html/rcomp/tmp/14lie1261840856.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/29f1v1261840856.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3ktgj1261840856.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/45uxw1261840856.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5vyw21261840856.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 = 60
Frequency = 1
1 2 3 4 5 6
18703.6786 17414.6786 257.6786 1544.6786 -3044.3214 -4530.3214
7 8 9 10 11 12
-9481.3214 -20809.3214 -26453.3214 -24881.3214 26825.6786 34974.6786
13 14 15 16 17 18
34322.6786 18207.6786 1494.6786 3231.6786 -501.3214 -3837.3214
19 20 21 22 23 24
-14110.3214 -19704.3214 -21134.3214 -20967.3214 25657.6786 31899.6786
25 26 27 28 29 30
26006.6786 -6284.3214 -28167.3214 -36635.3214 34807.9375 23085.9375
31 32 33 34 35 36
5904.9375 150.9375 -14730.0625 -27106.0625 29593.9375 38822.9375
37 38 39 40 41 42
15888.9375 1301.9375 -15922.0625 -11510.0625 -8846.0625 -18207.0625
43 44 45 46 47 48
-33146.0625 -35525.0625 -56411.0625 -48188.0625 2610.9375 7821.9375
49 50 51 52 53 54
-7823.0625 -19594.0625 -23902.0625 -9627.0625 2453.9375 6869.9375
55 56 57 58 59 60
10553.9375 10766.9375 -2171.0625 10445.9375 60801.9375 70825.9375
> postscript(file="/var/www/html/rcomp/tmp/6d0sr1261840856.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 18703.6786 NA
1 17414.6786 18703.6786
2 257.6786 17414.6786
3 1544.6786 257.6786
4 -3044.3214 1544.6786
5 -4530.3214 -3044.3214
6 -9481.3214 -4530.3214
7 -20809.3214 -9481.3214
8 -26453.3214 -20809.3214
9 -24881.3214 -26453.3214
10 26825.6786 -24881.3214
11 34974.6786 26825.6786
12 34322.6786 34974.6786
13 18207.6786 34322.6786
14 1494.6786 18207.6786
15 3231.6786 1494.6786
16 -501.3214 3231.6786
17 -3837.3214 -501.3214
18 -14110.3214 -3837.3214
19 -19704.3214 -14110.3214
20 -21134.3214 -19704.3214
21 -20967.3214 -21134.3214
22 25657.6786 -20967.3214
23 31899.6786 25657.6786
24 26006.6786 31899.6786
25 -6284.3214 26006.6786
26 -28167.3214 -6284.3214
27 -36635.3214 -28167.3214
28 34807.9375 -36635.3214
29 23085.9375 34807.9375
30 5904.9375 23085.9375
31 150.9375 5904.9375
32 -14730.0625 150.9375
33 -27106.0625 -14730.0625
34 29593.9375 -27106.0625
35 38822.9375 29593.9375
36 15888.9375 38822.9375
37 1301.9375 15888.9375
38 -15922.0625 1301.9375
39 -11510.0625 -15922.0625
40 -8846.0625 -11510.0625
41 -18207.0625 -8846.0625
42 -33146.0625 -18207.0625
43 -35525.0625 -33146.0625
44 -56411.0625 -35525.0625
45 -48188.0625 -56411.0625
46 2610.9375 -48188.0625
47 7821.9375 2610.9375
48 -7823.0625 7821.9375
49 -19594.0625 -7823.0625
50 -23902.0625 -19594.0625
51 -9627.0625 -23902.0625
52 2453.9375 -9627.0625
53 6869.9375 2453.9375
54 10553.9375 6869.9375
55 10766.9375 10553.9375
56 -2171.0625 10766.9375
57 10445.9375 -2171.0625
58 60801.9375 10445.9375
59 70825.9375 60801.9375
60 NA 70825.9375
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 17414.6786 18703.6786
[2,] 257.6786 17414.6786
[3,] 1544.6786 257.6786
[4,] -3044.3214 1544.6786
[5,] -4530.3214 -3044.3214
[6,] -9481.3214 -4530.3214
[7,] -20809.3214 -9481.3214
[8,] -26453.3214 -20809.3214
[9,] -24881.3214 -26453.3214
[10,] 26825.6786 -24881.3214
[11,] 34974.6786 26825.6786
[12,] 34322.6786 34974.6786
[13,] 18207.6786 34322.6786
[14,] 1494.6786 18207.6786
[15,] 3231.6786 1494.6786
[16,] -501.3214 3231.6786
[17,] -3837.3214 -501.3214
[18,] -14110.3214 -3837.3214
[19,] -19704.3214 -14110.3214
[20,] -21134.3214 -19704.3214
[21,] -20967.3214 -21134.3214
[22,] 25657.6786 -20967.3214
[23,] 31899.6786 25657.6786
[24,] 26006.6786 31899.6786
[25,] -6284.3214 26006.6786
[26,] -28167.3214 -6284.3214
[27,] -36635.3214 -28167.3214
[28,] 34807.9375 -36635.3214
[29,] 23085.9375 34807.9375
[30,] 5904.9375 23085.9375
[31,] 150.9375 5904.9375
[32,] -14730.0625 150.9375
[33,] -27106.0625 -14730.0625
[34,] 29593.9375 -27106.0625
[35,] 38822.9375 29593.9375
[36,] 15888.9375 38822.9375
[37,] 1301.9375 15888.9375
[38,] -15922.0625 1301.9375
[39,] -11510.0625 -15922.0625
[40,] -8846.0625 -11510.0625
[41,] -18207.0625 -8846.0625
[42,] -33146.0625 -18207.0625
[43,] -35525.0625 -33146.0625
[44,] -56411.0625 -35525.0625
[45,] -48188.0625 -56411.0625
[46,] 2610.9375 -48188.0625
[47,] 7821.9375 2610.9375
[48,] -7823.0625 7821.9375
[49,] -19594.0625 -7823.0625
[50,] -23902.0625 -19594.0625
[51,] -9627.0625 -23902.0625
[52,] 2453.9375 -9627.0625
[53,] 6869.9375 2453.9375
[54,] 10553.9375 6869.9375
[55,] 10766.9375 10553.9375
[56,] -2171.0625 10766.9375
[57,] 10445.9375 -2171.0625
[58,] 60801.9375 10445.9375
[59,] 70825.9375 60801.9375
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 17414.6786 18703.6786
2 257.6786 17414.6786
3 1544.6786 257.6786
4 -3044.3214 1544.6786
5 -4530.3214 -3044.3214
6 -9481.3214 -4530.3214
7 -20809.3214 -9481.3214
8 -26453.3214 -20809.3214
9 -24881.3214 -26453.3214
10 26825.6786 -24881.3214
11 34974.6786 26825.6786
12 34322.6786 34974.6786
13 18207.6786 34322.6786
14 1494.6786 18207.6786
15 3231.6786 1494.6786
16 -501.3214 3231.6786
17 -3837.3214 -501.3214
18 -14110.3214 -3837.3214
19 -19704.3214 -14110.3214
20 -21134.3214 -19704.3214
21 -20967.3214 -21134.3214
22 25657.6786 -20967.3214
23 31899.6786 25657.6786
24 26006.6786 31899.6786
25 -6284.3214 26006.6786
26 -28167.3214 -6284.3214
27 -36635.3214 -28167.3214
28 34807.9375 -36635.3214
29 23085.9375 34807.9375
30 5904.9375 23085.9375
31 150.9375 5904.9375
32 -14730.0625 150.9375
33 -27106.0625 -14730.0625
34 29593.9375 -27106.0625
35 38822.9375 29593.9375
36 15888.9375 38822.9375
37 1301.9375 15888.9375
38 -15922.0625 1301.9375
39 -11510.0625 -15922.0625
40 -8846.0625 -11510.0625
41 -18207.0625 -8846.0625
42 -33146.0625 -18207.0625
43 -35525.0625 -33146.0625
44 -56411.0625 -35525.0625
45 -48188.0625 -56411.0625
46 2610.9375 -48188.0625
47 7821.9375 2610.9375
48 -7823.0625 7821.9375
49 -19594.0625 -7823.0625
50 -23902.0625 -19594.0625
51 -9627.0625 -23902.0625
52 2453.9375 -9627.0625
53 6869.9375 2453.9375
54 10553.9375 6869.9375
55 10766.9375 10553.9375
56 -2171.0625 10766.9375
57 10445.9375 -2171.0625
58 60801.9375 10445.9375
59 70825.9375 60801.9375
> 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/71y8o1261840856.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8qmpv1261840856.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9llua1261840856.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/107kkf1261840856.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11rhyd1261840856.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/12qkdu1261840856.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/13n9me1261840856.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/14ht6g1261840856.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/15pxpi1261840856.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/160mdq1261840856.tab")
+ }
>
> try(system("convert tmp/14lie1261840856.ps tmp/14lie1261840856.png",intern=TRUE))
character(0)
> try(system("convert tmp/29f1v1261840856.ps tmp/29f1v1261840856.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ktgj1261840856.ps tmp/3ktgj1261840856.png",intern=TRUE))
character(0)
> try(system("convert tmp/45uxw1261840856.ps tmp/45uxw1261840856.png",intern=TRUE))
character(0)
> try(system("convert tmp/5vyw21261840856.ps tmp/5vyw21261840856.png",intern=TRUE))
character(0)
> try(system("convert tmp/6d0sr1261840856.ps tmp/6d0sr1261840856.png",intern=TRUE))
character(0)
> try(system("convert tmp/71y8o1261840856.ps tmp/71y8o1261840856.png",intern=TRUE))
character(0)
> try(system("convert tmp/8qmpv1261840856.ps tmp/8qmpv1261840856.png",intern=TRUE))
character(0)
> try(system("convert tmp/9llua1261840856.ps tmp/9llua1261840856.png",intern=TRUE))
character(0)
> try(system("convert tmp/107kkf1261840856.ps tmp/107kkf1261840856.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.502 1.612 11.160