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(9.9,8.2,9.8,8,9.3,7.5,8.3,6.8,8,6.5,8.5,6.6,10.4,7.6,11.1,8,10.9,8.1,10,7.7,9.2,7.5,9.2,7.6,9.5,7.8,9.6,7.8,9.5,7.8,9.1,7.5,8.9,7.5,9,7.1,10.1,7.5,10.3,7.5,10.2,7.6,9.6,7.7,9.2,7.7,9.3,7.9,9.4,8.1,9.4,8.2,9.2,8.2,9,8.2,9,7.9,9,7.3,9.8,6.9,10,6.6,9.8,6.7,9.3,6.9,9,7,9,7.1,9.1,7.2,9.1,7.1,9.1,6.9,9.2,7,8.8,6.8,8.3,6.4,8.4,6.7,8.1,6.6,7.7,6.4,7.9,6.3,7.9,6.2,8,6.5,7.9,6.8,7.6,6.8,7.1,6.4,6.8,6.1,6.5,5.8,6.9,6.1,8.2,7.2,8.7,7.3,8.3,6.9,7.9,6.1,7.5,5.8,7.8,6.2),dim=c(2,60),dimnames=list(c('WLVrouw','WLMan'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('WLVrouw','WLMan'),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
WLVrouw WLMan
1 9.9 8.2
2 9.8 8.0
3 9.3 7.5
4 8.3 6.8
5 8.0 6.5
6 8.5 6.6
7 10.4 7.6
8 11.1 8.0
9 10.9 8.1
10 10.0 7.7
11 9.2 7.5
12 9.2 7.6
13 9.5 7.8
14 9.6 7.8
15 9.5 7.8
16 9.1 7.5
17 8.9 7.5
18 9.0 7.1
19 10.1 7.5
20 10.3 7.5
21 10.2 7.6
22 9.6 7.7
23 9.2 7.7
24 9.3 7.9
25 9.4 8.1
26 9.4 8.2
27 9.2 8.2
28 9.0 8.2
29 9.0 7.9
30 9.0 7.3
31 9.8 6.9
32 10.0 6.6
33 9.8 6.7
34 9.3 6.9
35 9.0 7.0
36 9.0 7.1
37 9.1 7.2
38 9.1 7.1
39 9.1 6.9
40 9.2 7.0
41 8.8 6.8
42 8.3 6.4
43 8.4 6.7
44 8.1 6.6
45 7.7 6.4
46 7.9 6.3
47 7.9 6.2
48 8.0 6.5
49 7.9 6.8
50 7.6 6.8
51 7.1 6.4
52 6.8 6.1
53 6.5 5.8
54 6.9 6.1
55 8.2 7.2
56 8.7 7.3
57 8.3 6.9
58 7.9 6.1
59 7.5 5.8
60 7.8 6.2
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) WLMan
0.7573 1.1400
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.10557 -0.36001 -0.06356 0.25197 1.71849
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.7573 0.8772 0.863 0.392
WLMan 1.1400 0.1224 9.315 4.03e-13 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.6296 on 58 degrees of freedom
Multiple R-squared: 0.5993, Adjusted R-squared: 0.5924
F-statistic: 86.76 on 1 and 58 DF, p-value: 4.028e-13
> 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,] 0.004650758 0.009301516 0.99534924
[2,] 0.009340184 0.018680367 0.99065982
[3,] 0.227955058 0.455910115 0.77204494
[4,] 0.451528594 0.903057188 0.54847141
[5,] 0.421348307 0.842696614 0.57865169
[6,] 0.322823652 0.645647304 0.67717635
[7,] 0.265738467 0.531476934 0.73426153
[8,] 0.237202810 0.474405621 0.76279719
[9,] 0.201256647 0.402513295 0.79874335
[10,] 0.153235030 0.306470060 0.84676497
[11,] 0.120542128 0.241084256 0.87945787
[12,] 0.090515524 0.181031048 0.90948448
[13,] 0.080580947 0.161161893 0.91941905
[14,] 0.053623925 0.107247851 0.94637607
[15,] 0.069663541 0.139327082 0.93033646
[16,] 0.122690388 0.245380776 0.87730961
[17,] 0.141688378 0.283376757 0.85831162
[18,] 0.106812980 0.213625961 0.89318702
[19,] 0.096726566 0.193453132 0.90327343
[20,] 0.098757798 0.197515596 0.90124220
[21,] 0.109542621 0.219085241 0.89045738
[22,] 0.123911390 0.247822781 0.87608861
[23,] 0.161854973 0.323709947 0.83814503
[24,] 0.262598968 0.525197935 0.73740103
[25,] 0.318393635 0.636787271 0.68160636
[26,] 0.262921996 0.525843992 0.73707800
[27,] 0.368879306 0.737758612 0.63112069
[28,] 0.754791058 0.490417885 0.24520894
[29,] 0.929974517 0.140050965 0.07002548
[30,] 0.939385290 0.121229419 0.06061471
[31,] 0.922490954 0.155018092 0.07750905
[32,] 0.896870424 0.206259152 0.10312958
[33,] 0.863834887 0.272330226 0.13616511
[34,] 0.837165792 0.325668416 0.16283421
[35,] 0.853853972 0.292292057 0.14614603
[36,] 0.886803721 0.226392559 0.11319628
[37,] 0.904885857 0.190228286 0.09511414
[38,] 0.920120382 0.159759236 0.07987962
[39,] 0.916534953 0.166930094 0.08346505
[40,] 0.900934671 0.198130658 0.09906533
[41,] 0.879042386 0.241915229 0.12095761
[42,] 0.860039502 0.279920995 0.13996050
[43,] 0.857546217 0.284907565 0.14245378
[44,] 0.828250930 0.343498139 0.17174907
[45,] 0.775426438 0.449147123 0.22457356
[46,] 0.763966309 0.472067381 0.23603369
[47,] 0.781694144 0.436611712 0.21830586
[48,] 0.805517984 0.388964031 0.19448202
[49,] 0.887291866 0.225416268 0.11270813
[50,] 0.989987916 0.020024169 0.01001208
[51,] 0.995885120 0.008229759 0.00411488
> postscript(file="/var/www/html/rcomp/tmp/1pky31258722934.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/203ye1258722934.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3szi41258722934.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4u5cb1258722934.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5zej91258722934.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
-0.205574592 -0.077566832 -0.007547431 -0.209520270 -0.167508630 0.218487490
7 8 9 10 11 12
0.978448689 1.222433168 0.908429288 0.464444808 -0.107547431 -0.221551311
13 14 15 16 17 18
-0.149559072 -0.049559072 -0.149559072 -0.207547431 -0.407547431 0.148468089
19 20 21 22 23 24
0.792452569 0.992452569 0.778448689 0.064444808 -0.335555192 -0.463562952
25 26 27 28 29 30
-0.591570712 -0.705574592 -0.905574592 -1.105574592 -0.763562952 -0.079539671
31 32 33 34 35 36
1.176475850 1.718487490 1.404483610 0.676475850 0.262471970 0.148468089
37 38 39 40 41 42
0.134464209 0.248468089 0.476475850 0.462471970 0.290479730 0.246495251
43 44 45 46 47 48
0.004483610 -0.181512510 -0.353504749 -0.039500869 0.074503011 -0.167508630
49 50 51 52 53 54
-0.609520270 -0.909520270 -0.953504749 -0.911493109 -0.869481468 -0.811493109
55 56 57 58 59 60
-0.765535791 -0.379539671 -0.323524150 0.188506891 0.130518532 -0.025496989
> postscript(file="/var/www/html/rcomp/tmp/6wfl81258722934.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 -0.205574592 NA
1 -0.077566832 -0.205574592
2 -0.007547431 -0.077566832
3 -0.209520270 -0.007547431
4 -0.167508630 -0.209520270
5 0.218487490 -0.167508630
6 0.978448689 0.218487490
7 1.222433168 0.978448689
8 0.908429288 1.222433168
9 0.464444808 0.908429288
10 -0.107547431 0.464444808
11 -0.221551311 -0.107547431
12 -0.149559072 -0.221551311
13 -0.049559072 -0.149559072
14 -0.149559072 -0.049559072
15 -0.207547431 -0.149559072
16 -0.407547431 -0.207547431
17 0.148468089 -0.407547431
18 0.792452569 0.148468089
19 0.992452569 0.792452569
20 0.778448689 0.992452569
21 0.064444808 0.778448689
22 -0.335555192 0.064444808
23 -0.463562952 -0.335555192
24 -0.591570712 -0.463562952
25 -0.705574592 -0.591570712
26 -0.905574592 -0.705574592
27 -1.105574592 -0.905574592
28 -0.763562952 -1.105574592
29 -0.079539671 -0.763562952
30 1.176475850 -0.079539671
31 1.718487490 1.176475850
32 1.404483610 1.718487490
33 0.676475850 1.404483610
34 0.262471970 0.676475850
35 0.148468089 0.262471970
36 0.134464209 0.148468089
37 0.248468089 0.134464209
38 0.476475850 0.248468089
39 0.462471970 0.476475850
40 0.290479730 0.462471970
41 0.246495251 0.290479730
42 0.004483610 0.246495251
43 -0.181512510 0.004483610
44 -0.353504749 -0.181512510
45 -0.039500869 -0.353504749
46 0.074503011 -0.039500869
47 -0.167508630 0.074503011
48 -0.609520270 -0.167508630
49 -0.909520270 -0.609520270
50 -0.953504749 -0.909520270
51 -0.911493109 -0.953504749
52 -0.869481468 -0.911493109
53 -0.811493109 -0.869481468
54 -0.765535791 -0.811493109
55 -0.379539671 -0.765535791
56 -0.323524150 -0.379539671
57 0.188506891 -0.323524150
58 0.130518532 0.188506891
59 -0.025496989 0.130518532
60 NA -0.025496989
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -0.077566832 -0.205574592
[2,] -0.007547431 -0.077566832
[3,] -0.209520270 -0.007547431
[4,] -0.167508630 -0.209520270
[5,] 0.218487490 -0.167508630
[6,] 0.978448689 0.218487490
[7,] 1.222433168 0.978448689
[8,] 0.908429288 1.222433168
[9,] 0.464444808 0.908429288
[10,] -0.107547431 0.464444808
[11,] -0.221551311 -0.107547431
[12,] -0.149559072 -0.221551311
[13,] -0.049559072 -0.149559072
[14,] -0.149559072 -0.049559072
[15,] -0.207547431 -0.149559072
[16,] -0.407547431 -0.207547431
[17,] 0.148468089 -0.407547431
[18,] 0.792452569 0.148468089
[19,] 0.992452569 0.792452569
[20,] 0.778448689 0.992452569
[21,] 0.064444808 0.778448689
[22,] -0.335555192 0.064444808
[23,] -0.463562952 -0.335555192
[24,] -0.591570712 -0.463562952
[25,] -0.705574592 -0.591570712
[26,] -0.905574592 -0.705574592
[27,] -1.105574592 -0.905574592
[28,] -0.763562952 -1.105574592
[29,] -0.079539671 -0.763562952
[30,] 1.176475850 -0.079539671
[31,] 1.718487490 1.176475850
[32,] 1.404483610 1.718487490
[33,] 0.676475850 1.404483610
[34,] 0.262471970 0.676475850
[35,] 0.148468089 0.262471970
[36,] 0.134464209 0.148468089
[37,] 0.248468089 0.134464209
[38,] 0.476475850 0.248468089
[39,] 0.462471970 0.476475850
[40,] 0.290479730 0.462471970
[41,] 0.246495251 0.290479730
[42,] 0.004483610 0.246495251
[43,] -0.181512510 0.004483610
[44,] -0.353504749 -0.181512510
[45,] -0.039500869 -0.353504749
[46,] 0.074503011 -0.039500869
[47,] -0.167508630 0.074503011
[48,] -0.609520270 -0.167508630
[49,] -0.909520270 -0.609520270
[50,] -0.953504749 -0.909520270
[51,] -0.911493109 -0.953504749
[52,] -0.869481468 -0.911493109
[53,] -0.811493109 -0.869481468
[54,] -0.765535791 -0.811493109
[55,] -0.379539671 -0.765535791
[56,] -0.323524150 -0.379539671
[57,] 0.188506891 -0.323524150
[58,] 0.130518532 0.188506891
[59,] -0.025496989 0.130518532
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -0.077566832 -0.205574592
2 -0.007547431 -0.077566832
3 -0.209520270 -0.007547431
4 -0.167508630 -0.209520270
5 0.218487490 -0.167508630
6 0.978448689 0.218487490
7 1.222433168 0.978448689
8 0.908429288 1.222433168
9 0.464444808 0.908429288
10 -0.107547431 0.464444808
11 -0.221551311 -0.107547431
12 -0.149559072 -0.221551311
13 -0.049559072 -0.149559072
14 -0.149559072 -0.049559072
15 -0.207547431 -0.149559072
16 -0.407547431 -0.207547431
17 0.148468089 -0.407547431
18 0.792452569 0.148468089
19 0.992452569 0.792452569
20 0.778448689 0.992452569
21 0.064444808 0.778448689
22 -0.335555192 0.064444808
23 -0.463562952 -0.335555192
24 -0.591570712 -0.463562952
25 -0.705574592 -0.591570712
26 -0.905574592 -0.705574592
27 -1.105574592 -0.905574592
28 -0.763562952 -1.105574592
29 -0.079539671 -0.763562952
30 1.176475850 -0.079539671
31 1.718487490 1.176475850
32 1.404483610 1.718487490
33 0.676475850 1.404483610
34 0.262471970 0.676475850
35 0.148468089 0.262471970
36 0.134464209 0.148468089
37 0.248468089 0.134464209
38 0.476475850 0.248468089
39 0.462471970 0.476475850
40 0.290479730 0.462471970
41 0.246495251 0.290479730
42 0.004483610 0.246495251
43 -0.181512510 0.004483610
44 -0.353504749 -0.181512510
45 -0.039500869 -0.353504749
46 0.074503011 -0.039500869
47 -0.167508630 0.074503011
48 -0.609520270 -0.167508630
49 -0.909520270 -0.609520270
50 -0.953504749 -0.909520270
51 -0.911493109 -0.953504749
52 -0.869481468 -0.911493109
53 -0.811493109 -0.869481468
54 -0.765535791 -0.811493109
55 -0.379539671 -0.765535791
56 -0.323524150 -0.379539671
57 0.188506891 -0.323524150
58 0.130518532 0.188506891
59 -0.025496989 0.130518532
> 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/7vdsx1258722934.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8g7141258722934.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9j8k81258722934.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10fcxo1258722934.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11smpe1258722934.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/12j9ub1258722934.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/132puv1258722934.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/1479ll1258722935.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/15654u1258722935.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/162pbl1258722935.tab")
+ }
>
> system("convert tmp/1pky31258722934.ps tmp/1pky31258722934.png")
> system("convert tmp/203ye1258722934.ps tmp/203ye1258722934.png")
> system("convert tmp/3szi41258722934.ps tmp/3szi41258722934.png")
> system("convert tmp/4u5cb1258722934.ps tmp/4u5cb1258722934.png")
> system("convert tmp/5zej91258722934.ps tmp/5zej91258722934.png")
> system("convert tmp/6wfl81258722934.ps tmp/6wfl81258722934.png")
> system("convert tmp/7vdsx1258722934.ps tmp/7vdsx1258722934.png")
> system("convert tmp/8g7141258722934.ps tmp/8g7141258722934.png")
> system("convert tmp/9j8k81258722934.ps tmp/9j8k81258722934.png")
> system("convert tmp/10fcxo1258722934.ps tmp/10fcxo1258722934.png")
>
>
> proc.time()
user system elapsed
2.504 1.576 2.962