R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)
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(9700,0,9081,0,9084,0,9743,0,8587,0,9731,0,9563,0,9998,0,9437,0,10038,0,9918,0,9252,0,9737,0,9035,0,9133,0,9487,0,8700,0,9627,0,8947,0,9283,0,8829,0,9947,0,9628,0,9318,0,9605,0,8640,0,9214,0,9567,0,8547,0,9185,0,9470,0,9123,0,9278,0,10170,0,9434,0,9655,0,9429,0,8739,0,9552,0,9687,1,9019,1,9672,1,9206,1,9069,1,9788,1,10312,1,10105,1,9863,1,9656,1,9295,1,9946,1,9701,1,9049,1,10190,1,9706,1,9765,1,9893,1,9994,1,10433,1,10073,1,10112,1,9266,1,9820,1,10097,1,9115,1,10411,1,9678,1,10408,1,10153,1,10368,1,10581,1,10597,1,10680,1,9738,1,9556,1),dim=c(2,75),dimnames=list(c('births','difference'),1:75))
> y <- array(NA,dim=c(2,75),dimnames=list(c('births','difference'),1:75))
> 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
> 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
births difference
1 9700 0
2 9081 0
3 9084 0
4 9743 0
5 8587 0
6 9731 0
7 9563 0
8 9998 0
9 9437 0
10 10038 0
11 9918 0
12 9252 0
13 9737 0
14 9035 0
15 9133 0
16 9487 0
17 8700 0
18 9627 0
19 8947 0
20 9283 0
21 8829 0
22 9947 0
23 9628 0
24 9318 0
25 9605 0
26 8640 0
27 9214 0
28 9567 0
29 8547 0
30 9185 0
31 9470 0
32 9123 0
33 9278 0
34 10170 0
35 9434 0
36 9655 0
37 9429 0
38 8739 0
39 9552 0
40 9687 1
41 9019 1
42 9672 1
43 9206 1
44 9069 1
45 9788 1
46 10312 1
47 10105 1
48 9863 1
49 9656 1
50 9295 1
51 9946 1
52 9701 1
53 9049 1
54 10190 1
55 9706 1
56 9765 1
57 9893 1
58 9994 1
59 10433 1
60 10073 1
61 10112 1
62 9266 1
63 9820 1
64 10097 1
65 9115 1
66 10411 1
67 9678 1
68 10408 1
69 10153 1
70 10368 1
71 10581 1
72 10597 1
73 10680 1
74 9738 1
75 9556 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) difference
9369.5 491.7
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-842.17 -241.51 31.83 288.66 818.83
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9369.51 70.63 132.656 < 2e-16 ***
difference 491.65 101.95 4.823 7.52e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 441.1 on 73 degrees of freedom
Multiple R-squared: 0.2416, Adjusted R-squared: 0.2312
F-statistic: 23.26 on 1 and 73 DF, p-value: 7.523e-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,] 0.80709932 0.3858014 0.1929007
[2,] 0.77793321 0.4441336 0.2220668
[3,] 0.68577410 0.6284518 0.3142259
[4,] 0.74558769 0.5088246 0.2544123
[5,] 0.64280680 0.7143864 0.3571932
[6,] 0.69929704 0.6014059 0.3007030
[7,] 0.68720111 0.6255978 0.3127989
[8,] 0.62232588 0.7553482 0.3776741
[9,] 0.56042390 0.8791522 0.4395761
[10,] 0.55923485 0.8815303 0.4407651
[11,] 0.51609203 0.9678159 0.4839080
[12,] 0.43143061 0.8628612 0.5685694
[13,] 0.56664927 0.8667015 0.4333507
[14,] 0.50494055 0.9901189 0.4950595
[15,] 0.50666803 0.9866639 0.4933320
[16,] 0.43244288 0.8648858 0.5675571
[17,] 0.47185112 0.9437022 0.5281489
[18,] 0.51753294 0.9649341 0.4824671
[19,] 0.46550826 0.9310165 0.5344917
[20,] 0.39464667 0.7892933 0.6053533
[21,] 0.34404584 0.6880917 0.6559542
[22,] 0.46384897 0.9276979 0.5361510
[23,] 0.40186170 0.8037234 0.5981383
[24,] 0.34790640 0.6958128 0.6520936
[25,] 0.50954950 0.9809010 0.4904505
[26,] 0.45305970 0.9061194 0.5469403
[27,] 0.38823701 0.7764740 0.6117630
[28,] 0.34641848 0.6928370 0.6535815
[29,] 0.29079961 0.5815992 0.7092004
[30,] 0.42047168 0.8409434 0.5795283
[31,] 0.35674312 0.7134862 0.6432569
[32,] 0.32524076 0.6504815 0.6747592
[33,] 0.27353676 0.5470735 0.7264632
[34,] 0.32247057 0.6449411 0.6775294
[35,] 0.26911940 0.5382388 0.7308806
[36,] 0.21972251 0.4394450 0.7802775
[37,] 0.29478232 0.5895646 0.7052177
[38,] 0.25484948 0.5096990 0.7451505
[39,] 0.27933812 0.5586762 0.7206619
[40,] 0.36478246 0.7295649 0.6352175
[41,] 0.33231660 0.6646332 0.6676834
[42,] 0.39467546 0.7893509 0.6053245
[43,] 0.37212422 0.7442484 0.6278758
[44,] 0.31579815 0.6315963 0.6842019
[45,] 0.27020669 0.5404134 0.7297933
[46,] 0.30749290 0.6149858 0.6925071
[47,] 0.25836408 0.5167282 0.7416359
[48,] 0.21668522 0.4333704 0.7833148
[49,] 0.39428034 0.7885607 0.6057197
[50,] 0.36643319 0.7328664 0.6335668
[51,] 0.32366794 0.6473359 0.6763321
[52,] 0.27699603 0.5539921 0.7230040
[53,] 0.22519931 0.4503986 0.7748007
[54,] 0.17775150 0.3555030 0.8222485
[55,] 0.18899890 0.3779978 0.8110011
[56,] 0.14427598 0.2885520 0.8557240
[57,] 0.10766479 0.2153296 0.8923352
[58,] 0.18060690 0.3612138 0.8193931
[59,] 0.14122779 0.2824556 0.8587722
[60,] 0.09913677 0.1982735 0.9008632
[61,] 0.36284927 0.7256985 0.6371507
[62,] 0.30833438 0.6166688 0.6916656
[63,] 0.34386745 0.6877349 0.6561326
[64,] 0.26513004 0.5302601 0.7348700
[65,] 0.17270262 0.3454052 0.8272974
[66,] 0.10325832 0.2065166 0.8967417
> postscript(file="/var/www/rcomp/tmp/1qutm1291914016.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/213a71291914016.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/rcomp/tmp/313a71291914016.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/413a71291914016.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/5uu9s1291914016.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 = 75
Frequency = 1
1 2 3 4 5 6
330.487179 -288.512821 -285.512821 373.487179 -782.512821 361.487179
7 8 9 10 11 12
193.487179 628.487179 67.487179 668.487179 548.487179 -117.512821
13 14 15 16 17 18
367.487179 -334.512821 -236.512821 117.487179 -669.512821 257.487179
19 20 21 22 23 24
-422.512821 -86.512821 -540.512821 577.487179 258.487179 -51.512821
25 26 27 28 29 30
235.487179 -729.512821 -155.512821 197.487179 -822.512821 -184.512821
31 32 33 34 35 36
100.487179 -246.512821 -91.512821 800.487179 64.487179 285.487179
37 38 39 40 41 42
59.487179 -630.512821 182.487179 -174.166667 -842.166667 -189.166667
43 44 45 46 47 48
-655.166667 -792.166667 -73.166667 450.833333 243.833333 1.833333
49 50 51 52 53 54
-205.166667 -566.166667 84.833333 -160.166667 -812.166667 328.833333
55 56 57 58 59 60
-155.166667 -96.166667 31.833333 132.833333 571.833333 211.833333
61 62 63 64 65 66
250.833333 -595.166667 -41.166667 235.833333 -746.166667 549.833333
67 68 69 70 71 72
-183.166667 546.833333 291.833333 506.833333 719.833333 735.833333
73 74 75
818.833333 -123.166667 -305.166667
> postscript(file="/var/www/rcomp/tmp/6uu9s1291914016.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 = 75
Frequency = 1
lag(myerror, k = 1) myerror
0 330.487179 NA
1 -288.512821 330.487179
2 -285.512821 -288.512821
3 373.487179 -285.512821
4 -782.512821 373.487179
5 361.487179 -782.512821
6 193.487179 361.487179
7 628.487179 193.487179
8 67.487179 628.487179
9 668.487179 67.487179
10 548.487179 668.487179
11 -117.512821 548.487179
12 367.487179 -117.512821
13 -334.512821 367.487179
14 -236.512821 -334.512821
15 117.487179 -236.512821
16 -669.512821 117.487179
17 257.487179 -669.512821
18 -422.512821 257.487179
19 -86.512821 -422.512821
20 -540.512821 -86.512821
21 577.487179 -540.512821
22 258.487179 577.487179
23 -51.512821 258.487179
24 235.487179 -51.512821
25 -729.512821 235.487179
26 -155.512821 -729.512821
27 197.487179 -155.512821
28 -822.512821 197.487179
29 -184.512821 -822.512821
30 100.487179 -184.512821
31 -246.512821 100.487179
32 -91.512821 -246.512821
33 800.487179 -91.512821
34 64.487179 800.487179
35 285.487179 64.487179
36 59.487179 285.487179
37 -630.512821 59.487179
38 182.487179 -630.512821
39 -174.166667 182.487179
40 -842.166667 -174.166667
41 -189.166667 -842.166667
42 -655.166667 -189.166667
43 -792.166667 -655.166667
44 -73.166667 -792.166667
45 450.833333 -73.166667
46 243.833333 450.833333
47 1.833333 243.833333
48 -205.166667 1.833333
49 -566.166667 -205.166667
50 84.833333 -566.166667
51 -160.166667 84.833333
52 -812.166667 -160.166667
53 328.833333 -812.166667
54 -155.166667 328.833333
55 -96.166667 -155.166667
56 31.833333 -96.166667
57 132.833333 31.833333
58 571.833333 132.833333
59 211.833333 571.833333
60 250.833333 211.833333
61 -595.166667 250.833333
62 -41.166667 -595.166667
63 235.833333 -41.166667
64 -746.166667 235.833333
65 549.833333 -746.166667
66 -183.166667 549.833333
67 546.833333 -183.166667
68 291.833333 546.833333
69 506.833333 291.833333
70 719.833333 506.833333
71 735.833333 719.833333
72 818.833333 735.833333
73 -123.166667 818.833333
74 -305.166667 -123.166667
75 NA -305.166667
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -288.512821 330.487179
[2,] -285.512821 -288.512821
[3,] 373.487179 -285.512821
[4,] -782.512821 373.487179
[5,] 361.487179 -782.512821
[6,] 193.487179 361.487179
[7,] 628.487179 193.487179
[8,] 67.487179 628.487179
[9,] 668.487179 67.487179
[10,] 548.487179 668.487179
[11,] -117.512821 548.487179
[12,] 367.487179 -117.512821
[13,] -334.512821 367.487179
[14,] -236.512821 -334.512821
[15,] 117.487179 -236.512821
[16,] -669.512821 117.487179
[17,] 257.487179 -669.512821
[18,] -422.512821 257.487179
[19,] -86.512821 -422.512821
[20,] -540.512821 -86.512821
[21,] 577.487179 -540.512821
[22,] 258.487179 577.487179
[23,] -51.512821 258.487179
[24,] 235.487179 -51.512821
[25,] -729.512821 235.487179
[26,] -155.512821 -729.512821
[27,] 197.487179 -155.512821
[28,] -822.512821 197.487179
[29,] -184.512821 -822.512821
[30,] 100.487179 -184.512821
[31,] -246.512821 100.487179
[32,] -91.512821 -246.512821
[33,] 800.487179 -91.512821
[34,] 64.487179 800.487179
[35,] 285.487179 64.487179
[36,] 59.487179 285.487179
[37,] -630.512821 59.487179
[38,] 182.487179 -630.512821
[39,] -174.166667 182.487179
[40,] -842.166667 -174.166667
[41,] -189.166667 -842.166667
[42,] -655.166667 -189.166667
[43,] -792.166667 -655.166667
[44,] -73.166667 -792.166667
[45,] 450.833333 -73.166667
[46,] 243.833333 450.833333
[47,] 1.833333 243.833333
[48,] -205.166667 1.833333
[49,] -566.166667 -205.166667
[50,] 84.833333 -566.166667
[51,] -160.166667 84.833333
[52,] -812.166667 -160.166667
[53,] 328.833333 -812.166667
[54,] -155.166667 328.833333
[55,] -96.166667 -155.166667
[56,] 31.833333 -96.166667
[57,] 132.833333 31.833333
[58,] 571.833333 132.833333
[59,] 211.833333 571.833333
[60,] 250.833333 211.833333
[61,] -595.166667 250.833333
[62,] -41.166667 -595.166667
[63,] 235.833333 -41.166667
[64,] -746.166667 235.833333
[65,] 549.833333 -746.166667
[66,] -183.166667 549.833333
[67,] 546.833333 -183.166667
[68,] 291.833333 546.833333
[69,] 506.833333 291.833333
[70,] 719.833333 506.833333
[71,] 735.833333 719.833333
[72,] 818.833333 735.833333
[73,] -123.166667 818.833333
[74,] -305.166667 -123.166667
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -288.512821 330.487179
2 -285.512821 -288.512821
3 373.487179 -285.512821
4 -782.512821 373.487179
5 361.487179 -782.512821
6 193.487179 361.487179
7 628.487179 193.487179
8 67.487179 628.487179
9 668.487179 67.487179
10 548.487179 668.487179
11 -117.512821 548.487179
12 367.487179 -117.512821
13 -334.512821 367.487179
14 -236.512821 -334.512821
15 117.487179 -236.512821
16 -669.512821 117.487179
17 257.487179 -669.512821
18 -422.512821 257.487179
19 -86.512821 -422.512821
20 -540.512821 -86.512821
21 577.487179 -540.512821
22 258.487179 577.487179
23 -51.512821 258.487179
24 235.487179 -51.512821
25 -729.512821 235.487179
26 -155.512821 -729.512821
27 197.487179 -155.512821
28 -822.512821 197.487179
29 -184.512821 -822.512821
30 100.487179 -184.512821
31 -246.512821 100.487179
32 -91.512821 -246.512821
33 800.487179 -91.512821
34 64.487179 800.487179
35 285.487179 64.487179
36 59.487179 285.487179
37 -630.512821 59.487179
38 182.487179 -630.512821
39 -174.166667 182.487179
40 -842.166667 -174.166667
41 -189.166667 -842.166667
42 -655.166667 -189.166667
43 -792.166667 -655.166667
44 -73.166667 -792.166667
45 450.833333 -73.166667
46 243.833333 450.833333
47 1.833333 243.833333
48 -205.166667 1.833333
49 -566.166667 -205.166667
50 84.833333 -566.166667
51 -160.166667 84.833333
52 -812.166667 -160.166667
53 328.833333 -812.166667
54 -155.166667 328.833333
55 -96.166667 -155.166667
56 31.833333 -96.166667
57 132.833333 31.833333
58 571.833333 132.833333
59 211.833333 571.833333
60 250.833333 211.833333
61 -595.166667 250.833333
62 -41.166667 -595.166667
63 235.833333 -41.166667
64 -746.166667 235.833333
65 549.833333 -746.166667
66 -183.166667 549.833333
67 546.833333 -183.166667
68 291.833333 546.833333
69 506.833333 291.833333
70 719.833333 506.833333
71 735.833333 719.833333
72 818.833333 735.833333
73 -123.166667 818.833333
74 -305.166667 -123.166667
> 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/rcomp/tmp/74lqv1291914016.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/84lqv1291914016.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/rcomp/tmp/9xuqg1291914016.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/rcomp/tmp/10xuqg1291914016.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/rcomp/tmp/11jvom1291914016.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/rcomp/tmp/12mvnr1291914016.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/rcomp/tmp/13bx2l1291914016.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/rcomp/tmp/1436jo1291914016.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/rcomp/tmp/15hyhx1291914016.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/rcomp/tmp/163gf31291914016.tab")
+ }
>
> try(system("convert tmp/1qutm1291914016.ps tmp/1qutm1291914016.png",intern=TRUE))
character(0)
> try(system("convert tmp/213a71291914016.ps tmp/213a71291914016.png",intern=TRUE))
character(0)
> try(system("convert tmp/313a71291914016.ps tmp/313a71291914016.png",intern=TRUE))
character(0)
> try(system("convert tmp/413a71291914016.ps tmp/413a71291914016.png",intern=TRUE))
character(0)
> try(system("convert tmp/5uu9s1291914016.ps tmp/5uu9s1291914016.png",intern=TRUE))
character(0)
> try(system("convert tmp/6uu9s1291914016.ps tmp/6uu9s1291914016.png",intern=TRUE))
character(0)
> try(system("convert tmp/74lqv1291914016.ps tmp/74lqv1291914016.png",intern=TRUE))
character(0)
> try(system("convert tmp/84lqv1291914016.ps tmp/84lqv1291914016.png",intern=TRUE))
character(0)
> try(system("convert tmp/9xuqg1291914016.ps tmp/9xuqg1291914016.png",intern=TRUE))
character(0)
> try(system("convert tmp/10xuqg1291914016.ps tmp/10xuqg1291914016.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.110 1.740 4.915