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(184,74,11,31,20,213,72,11,43,18,347,70,18,16,16,565,71,11,25,19,327,72,9,29,24,260,68,8,32,15,325,68,12,24,14,102,62,13,28,11,38,69,7,25,12,226,66,9,58,15,137,60,13,21,9,369,81,4,77,36,109,66,9,37,12,809,67,11,37,16,29,65,12,35,11,245,64,10,42,14,118,64,12,21,10,148,62,7,81,27,387,59,15,31,16,98,56,15,50,15,608,46,22,24,8,218,54,14,27,13,254,54,20,22,11,697,45,26,18,8,827,57,12,23,11,693,57,9,60,18,448,61,19,14,12,942,52,17,31,10,1017,44,21,24,9,216,43,18,23,8,673,48,19,22,10,989,57,14,25,12,630,47,19,25,9,404,50,19,21,9,692,48,16,32,11,1517,49,13,31,14,879,72,13,13,22,631,59,14,21,13,1375,49,9,46,13,1139,54,13,27,12,3545,62,22,18,15,706,47,17,39,11,451,45,34,15,10,433,48,26,23,12,601,69,23,7,12,1024,42,23,23,11,457,49,18,30,12,1441,57,15,35,13,1022,72,22,15,16,1244,67,26,18,16),dim=c(5,50),dimnames=list(c('Crimerate','25+HSgraduate','Dropouts16-19','CollegeStudents18-24','25+CollegeGrads'),1:50))
> y <- array(NA,dim=c(5,50),dimnames=list(c('Crimerate','25+HSgraduate','Dropouts16-19','CollegeStudents18-24','25+CollegeGrads'),1:50))
> 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
Crimerate 25+HSgraduate Dropouts16-19 CollegeStudents18-24 25+CollegeGrads
1 184 74 11 31 20
2 213 72 11 43 18
3 347 70 18 16 16
4 565 71 11 25 19
5 327 72 9 29 24
6 260 68 8 32 15
7 325 68 12 24 14
8 102 62 13 28 11
9 38 69 7 25 12
10 226 66 9 58 15
11 137 60 13 21 9
12 369 81 4 77 36
13 109 66 9 37 12
14 809 67 11 37 16
15 29 65 12 35 11
16 245 64 10 42 14
17 118 64 12 21 10
18 148 62 7 81 27
19 387 59 15 31 16
20 98 56 15 50 15
21 608 46 22 24 8
22 218 54 14 27 13
23 254 54 20 22 11
24 697 45 26 18 8
25 827 57 12 23 11
26 693 57 9 60 18
27 448 61 19 14 12
28 942 52 17 31 10
29 1017 44 21 24 9
30 216 43 18 23 8
31 673 48 19 22 10
32 989 57 14 25 12
33 630 47 19 25 9
34 404 50 19 21 9
35 692 48 16 32 11
36 1517 49 13 31 14
37 879 72 13 13 22
38 631 59 14 21 13
39 1375 49 9 46 13
40 1139 54 13 27 12
41 3545 62 22 18 15
42 706 47 17 39 11
43 451 45 34 15 10
44 433 48 26 23 12
45 601 69 23 7 12
46 1024 42 23 23 11
47 457 49 18 30 12
48 1441 57 15 35 13
49 1022 72 22 15 16
50 1244 67 26 18 16
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) `25+HSgraduate` `Dropouts16-19`
1395.26 -22.02 11.36
`CollegeStudents18-24` `25+CollegeGrads`
-13.00 52.81
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-672.3 -303.4 -108.7 177.8 2707.3
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1395.259 1026.946 1.359 0.1810
`25+HSgraduate` -22.024 14.248 -1.546 0.1292
`Dropouts16-19` 11.356 21.103 0.538 0.5931
`CollegeStudents18-24` -13.002 9.405 -1.382 0.1737
`25+CollegeGrads` 52.807 28.752 1.837 0.0729 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 551.8 on 45 degrees of freedom
Multiple R-squared: 0.1504, Adjusted R-squared: 0.07488
F-statistic: 1.991 on 4 and 45 DF, p-value: 0.112
> 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,] 2.359928e-02 4.719856e-02 0.9764007
[2,] 1.083536e-02 2.167072e-02 0.9891646
[3,] 3.084017e-03 6.168034e-03 0.9969160
[4,] 7.305535e-04 1.461107e-03 0.9992694
[5,] 1.852467e-04 3.704934e-04 0.9998148
[6,] 3.703480e-05 7.406960e-05 0.9999630
[7,] 1.068663e-03 2.137326e-03 0.9989313
[8,] 4.573276e-04 9.146551e-04 0.9995427
[9,] 1.421066e-04 2.842133e-04 0.9998579
[10,] 5.292826e-05 1.058565e-04 0.9999471
[11,] 3.126310e-05 6.252619e-05 0.9999687
[12,] 1.151853e-05 2.303707e-05 0.9999885
[13,] 6.654351e-06 1.330870e-05 0.9999933
[14,] 4.242537e-06 8.485075e-06 0.9999958
[15,] 1.974236e-06 3.948471e-06 0.9999980
[16,] 9.317249e-07 1.863450e-06 0.9999991
[17,] 4.018616e-07 8.037232e-07 0.9999996
[18,] 2.289661e-06 4.579322e-06 0.9999977
[19,] 6.910890e-06 1.382178e-05 0.9999931
[20,] 2.516794e-06 5.033588e-06 0.9999975
[21,] 5.513793e-06 1.102759e-05 0.9999945
[22,] 4.685687e-06 9.371373e-06 0.9999953
[23,] 5.432444e-06 1.086489e-05 0.9999946
[24,] 1.871385e-06 3.742770e-06 0.9999981
[25,] 2.961056e-06 5.922112e-06 0.9999970
[26,] 9.497985e-07 1.899597e-06 0.9999991
[27,] 3.343557e-07 6.687114e-07 0.9999997
[28,] 1.096604e-07 2.193208e-07 0.9999999
[29,] 6.653109e-07 1.330622e-06 0.9999993
[30,] 5.254951e-06 1.050990e-05 0.9999947
[31,] 5.563857e-06 1.112771e-05 0.9999944
[32,] 5.663933e-06 1.132787e-05 0.9999943
[33,] 3.035258e-06 6.070516e-06 0.9999970
[34,] 7.556589e-01 4.886823e-01 0.2443411
[35,] 6.135467e-01 7.729067e-01 0.3864533
> postscript(file="/var/www/html/rcomp/tmp/14sk91290525561.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2xjjc1290525561.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3xjjc1290525561.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4xjjc1290525561.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/58bif1290525561.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 = 50
Frequency = 1
1 2 3 4 5 6
-359.494357 -112.905056 -347.884831 -69.770331 -475.061876 -104.530761
7 8 9 10 11 12
-136.164503 -292.235333 -225.742125 144.114301 -286.682094 -187.659516
13 14 15 16 17 18
-87.503995 400.578308 -196.793838 -47.513165 -259.037147 -333.911114
19 20 21 22 23 24
-321.050220 -376.278745 -134.412082 -482.399436 -473.933171 -190.873141
25 26 27 28 29 30
268.991992 280.481217 -271.231635 373.912558 189.089318 -560.060007
31 32 33 34 35 36
-122.913094 381.475728 -96.124138 -308.059956 7.368008 717.037783
37 38 39 40 41 42
-70.903615 -37.291202 868.299185 502.764187 2707.309011 79.000933
43 44 45 46 47 48
-672.344700 -535.020626 -78.479272 10.712325 -307.131923 899.331084
49 50
312.735373 418.195699
> postscript(file="/var/www/html/rcomp/tmp/68bif1290525561.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 = 50
Frequency = 1
lag(myerror, k = 1) myerror
0 -359.494357 NA
1 -112.905056 -359.494357
2 -347.884831 -112.905056
3 -69.770331 -347.884831
4 -475.061876 -69.770331
5 -104.530761 -475.061876
6 -136.164503 -104.530761
7 -292.235333 -136.164503
8 -225.742125 -292.235333
9 144.114301 -225.742125
10 -286.682094 144.114301
11 -187.659516 -286.682094
12 -87.503995 -187.659516
13 400.578308 -87.503995
14 -196.793838 400.578308
15 -47.513165 -196.793838
16 -259.037147 -47.513165
17 -333.911114 -259.037147
18 -321.050220 -333.911114
19 -376.278745 -321.050220
20 -134.412082 -376.278745
21 -482.399436 -134.412082
22 -473.933171 -482.399436
23 -190.873141 -473.933171
24 268.991992 -190.873141
25 280.481217 268.991992
26 -271.231635 280.481217
27 373.912558 -271.231635
28 189.089318 373.912558
29 -560.060007 189.089318
30 -122.913094 -560.060007
31 381.475728 -122.913094
32 -96.124138 381.475728
33 -308.059956 -96.124138
34 7.368008 -308.059956
35 717.037783 7.368008
36 -70.903615 717.037783
37 -37.291202 -70.903615
38 868.299185 -37.291202
39 502.764187 868.299185
40 2707.309011 502.764187
41 79.000933 2707.309011
42 -672.344700 79.000933
43 -535.020626 -672.344700
44 -78.479272 -535.020626
45 10.712325 -78.479272
46 -307.131923 10.712325
47 899.331084 -307.131923
48 312.735373 899.331084
49 418.195699 312.735373
50 NA 418.195699
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -112.905056 -359.494357
[2,] -347.884831 -112.905056
[3,] -69.770331 -347.884831
[4,] -475.061876 -69.770331
[5,] -104.530761 -475.061876
[6,] -136.164503 -104.530761
[7,] -292.235333 -136.164503
[8,] -225.742125 -292.235333
[9,] 144.114301 -225.742125
[10,] -286.682094 144.114301
[11,] -187.659516 -286.682094
[12,] -87.503995 -187.659516
[13,] 400.578308 -87.503995
[14,] -196.793838 400.578308
[15,] -47.513165 -196.793838
[16,] -259.037147 -47.513165
[17,] -333.911114 -259.037147
[18,] -321.050220 -333.911114
[19,] -376.278745 -321.050220
[20,] -134.412082 -376.278745
[21,] -482.399436 -134.412082
[22,] -473.933171 -482.399436
[23,] -190.873141 -473.933171
[24,] 268.991992 -190.873141
[25,] 280.481217 268.991992
[26,] -271.231635 280.481217
[27,] 373.912558 -271.231635
[28,] 189.089318 373.912558
[29,] -560.060007 189.089318
[30,] -122.913094 -560.060007
[31,] 381.475728 -122.913094
[32,] -96.124138 381.475728
[33,] -308.059956 -96.124138
[34,] 7.368008 -308.059956
[35,] 717.037783 7.368008
[36,] -70.903615 717.037783
[37,] -37.291202 -70.903615
[38,] 868.299185 -37.291202
[39,] 502.764187 868.299185
[40,] 2707.309011 502.764187
[41,] 79.000933 2707.309011
[42,] -672.344700 79.000933
[43,] -535.020626 -672.344700
[44,] -78.479272 -535.020626
[45,] 10.712325 -78.479272
[46,] -307.131923 10.712325
[47,] 899.331084 -307.131923
[48,] 312.735373 899.331084
[49,] 418.195699 312.735373
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -112.905056 -359.494357
2 -347.884831 -112.905056
3 -69.770331 -347.884831
4 -475.061876 -69.770331
5 -104.530761 -475.061876
6 -136.164503 -104.530761
7 -292.235333 -136.164503
8 -225.742125 -292.235333
9 144.114301 -225.742125
10 -286.682094 144.114301
11 -187.659516 -286.682094
12 -87.503995 -187.659516
13 400.578308 -87.503995
14 -196.793838 400.578308
15 -47.513165 -196.793838
16 -259.037147 -47.513165
17 -333.911114 -259.037147
18 -321.050220 -333.911114
19 -376.278745 -321.050220
20 -134.412082 -376.278745
21 -482.399436 -134.412082
22 -473.933171 -482.399436
23 -190.873141 -473.933171
24 268.991992 -190.873141
25 280.481217 268.991992
26 -271.231635 280.481217
27 373.912558 -271.231635
28 189.089318 373.912558
29 -560.060007 189.089318
30 -122.913094 -560.060007
31 381.475728 -122.913094
32 -96.124138 381.475728
33 -308.059956 -96.124138
34 7.368008 -308.059956
35 717.037783 7.368008
36 -70.903615 717.037783
37 -37.291202 -70.903615
38 868.299185 -37.291202
39 502.764187 868.299185
40 2707.309011 502.764187
41 79.000933 2707.309011
42 -672.344700 79.000933
43 -535.020626 -672.344700
44 -78.479272 -535.020626
45 10.712325 -78.479272
46 -307.131923 10.712325
47 899.331084 -307.131923
48 312.735373 899.331084
49 418.195699 312.735373
> 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/7i2hi1290525561.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8i2hi1290525561.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9btgl1290525561.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10btgl1290525561.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11plwb1290525561.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/12smvh1290525561.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/13z5at1290525561.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/14aw9e1290525561.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/15depk1290525561.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/16rons1290525561.tab")
+ }
>
> try(system("convert tmp/14sk91290525561.ps tmp/14sk91290525561.png",intern=TRUE))
character(0)
> try(system("convert tmp/2xjjc1290525561.ps tmp/2xjjc1290525561.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xjjc1290525561.ps tmp/3xjjc1290525561.png",intern=TRUE))
character(0)
> try(system("convert tmp/4xjjc1290525561.ps tmp/4xjjc1290525561.png",intern=TRUE))
character(0)
> try(system("convert tmp/58bif1290525561.ps tmp/58bif1290525561.png",intern=TRUE))
character(0)
> try(system("convert tmp/68bif1290525561.ps tmp/68bif1290525561.png",intern=TRUE))
character(0)
> try(system("convert tmp/7i2hi1290525561.ps tmp/7i2hi1290525561.png",intern=TRUE))
character(0)
> try(system("convert tmp/8i2hi1290525561.ps tmp/8i2hi1290525561.png",intern=TRUE))
character(0)
> try(system("convert tmp/9btgl1290525561.ps tmp/9btgl1290525561.png",intern=TRUE))
character(0)
> try(system("convert tmp/10btgl1290525561.ps tmp/10btgl1290525561.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.396 1.580 5.403