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.
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Type 'license()' or 'licence()' for distribution details.
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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(94.6,116.1,95.9,107.5,104.7,116.7,102.8,112.5,98.1,113,113.9,126.4,80.9,114.1,95.7,112.5,113.2,112.4,105.9,113.1,108.8,116.3,102.3,111.7,99,118.8,100.7,116.5,115.5,125.1,100.7,113.1,109.9,119.6,114.6,114.4,85.4,114,100.5,117.8,114.8,117,116.5,120.9,112.9,115,102,117.3,106,119.4,105.3,114.9,118.8,125.8,106.1,117.6,109.3,117.6,117.2,114.9,92.5,121.9,104.2,117,112.5,106.4,122.4,110.5,113.3,113.6,100,114.2,110.7,125.4,112.8,124.6,109.8,120.2,117.3,120.8,109.1,111.4,115.9,124.1,96,120.2,99.8,125.5,116.8,116,115.7,117,99.4,105.7,94.3,102,91,106.4,93.2,96.9,103.1,107.6,94.1,98.8,91.8,101.1,102.7,105.7,82.6,104.6,89.1,103.2,104.5,101.6,105.1,106.7,95.1,99.5,88.7,101),dim=c(2,60),dimnames=list(c('T.I.P.','I.P.C.N.'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('T.I.P.','I.P.C.N.'),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 = '2'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
I.P.C.N. T.I.P.
1 116.1 94.6
2 107.5 95.9
3 116.7 104.7
4 112.5 102.8
5 113.0 98.1
6 126.4 113.9
7 114.1 80.9
8 112.5 95.7
9 112.4 113.2
10 113.1 105.9
11 116.3 108.8
12 111.7 102.3
13 118.8 99.0
14 116.5 100.7
15 125.1 115.5
16 113.1 100.7
17 119.6 109.9
18 114.4 114.6
19 114.0 85.4
20 117.8 100.5
21 117.0 114.8
22 120.9 116.5
23 115.0 112.9
24 117.3 102.0
25 119.4 106.0
26 114.9 105.3
27 125.8 118.8
28 117.6 106.1
29 117.6 109.3
30 114.9 117.2
31 121.9 92.5
32 117.0 104.2
33 106.4 112.5
34 110.5 122.4
35 113.6 113.3
36 114.2 100.0
37 125.4 110.7
38 124.6 112.8
39 120.2 109.8
40 120.8 117.3
41 111.4 109.1
42 124.1 115.9
43 120.2 96.0
44 125.5 99.8
45 116.0 116.8
46 117.0 115.7
47 105.7 99.4
48 102.0 94.3
49 106.4 91.0
50 96.9 93.2
51 107.6 103.1
52 98.8 94.1
53 101.1 91.8
54 105.7 102.7
55 104.6 82.6
56 103.2 89.1
57 101.6 104.5
58 106.7 105.1
59 99.5 95.1
60 101.0 88.7
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) T.I.P.
72.8392 0.3931
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-12.5772 -4.4121 0.6703 4.4953 13.4283
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 72.83918 8.99661 8.096 4.22e-11 ***
T.I.P. 0.39311 0.08619 4.561 2.69e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6.479 on 58 degrees of freedom
Multiple R-squared: 0.264, Adjusted R-squared: 0.2513
F-statistic: 20.8 on 1 and 58 DF, p-value: 2.687e-05
> 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,] 0.2107206540 0.4214413080 0.78927935
[2,] 0.1774642616 0.3549285233 0.82253574
[3,] 0.3128030644 0.6256061288 0.68719694
[4,] 0.2063462955 0.4126925909 0.79365370
[5,] 0.2160985236 0.4321970471 0.78390148
[6,] 0.1493843202 0.2987686404 0.85061568
[7,] 0.0907279992 0.1814559984 0.90927200
[8,] 0.0611007153 0.1222014305 0.93889928
[9,] 0.0564593635 0.1129187270 0.94354064
[10,] 0.0357852851 0.0715705702 0.96421471
[11,] 0.0472756129 0.0945512257 0.95272439
[12,] 0.0295378298 0.0590756596 0.97046217
[13,] 0.0185613393 0.0371226786 0.98143866
[14,] 0.0148125967 0.0296251933 0.98518740
[15,] 0.0120800528 0.0241601057 0.98791995
[16,] 0.0087593375 0.0175186750 0.99124066
[17,] 0.0048636803 0.0097273605 0.99513632
[18,] 0.0028576018 0.0057152036 0.99714240
[19,] 0.0017621258 0.0035242515 0.99823787
[20,] 0.0010861253 0.0021722507 0.99891387
[21,] 0.0007671187 0.0015342373 0.99923288
[22,] 0.0003959536 0.0007919071 0.99960405
[23,] 0.0005700698 0.0011401395 0.99942993
[24,] 0.0003138502 0.0006277004 0.99968615
[25,] 0.0001573345 0.0003146690 0.99984267
[26,] 0.0001227915 0.0002455831 0.99987721
[27,] 0.0010380159 0.0020760319 0.99896198
[28,] 0.0006621787 0.0013243574 0.99933782
[29,] 0.0045032641 0.0090065281 0.99549674
[30,] 0.0127959862 0.0255919725 0.98720401
[31,] 0.0096945881 0.0193891761 0.99030541
[32,] 0.0067925514 0.0135851027 0.99320745
[33,] 0.0156558424 0.0313116849 0.98434416
[34,] 0.0237527691 0.0475055382 0.97624723
[35,] 0.0209721526 0.0419443052 0.97902785
[36,] 0.0146720057 0.0293440115 0.98532799
[37,] 0.0115628557 0.0231257114 0.98843714
[38,] 0.0159863892 0.0319727783 0.98401361
[39,] 0.0708195603 0.1416391206 0.92918044
[40,] 0.8215542551 0.3568914899 0.17844574
[41,] 0.8031588929 0.3936822142 0.19684111
[42,] 0.9235527038 0.1528945923 0.07644730
[43,] 0.9226877109 0.1546245782 0.07731229
[44,] 0.9178986683 0.1642026634 0.08210133
[45,] 0.9276309048 0.1447381905 0.07236910
[46,] 0.9718038984 0.0563922031 0.02819610
[47,] 0.9725781300 0.0548437401 0.02742187
[48,] 0.9778629206 0.0442741587 0.02213708
[49,] 0.9580826101 0.0838347797 0.04191739
[50,] 0.9260747805 0.1478504390 0.07392522
[51,] 0.8876043393 0.2247913214 0.11239566
> postscript(file="/var/www/html/rcomp/tmp/18vja1292667414.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2j4iv1292667414.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3j4iv1292667414.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4j4iv1292667414.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5j4iv1292667414.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 = 60
Frequency = 1
1 2 3 4 5 6
6.0724349 -3.0386105 2.7020050 -0.7510825 1.5965434 8.7853757
7 8 9 10 11 12
9.4580677 2.0400119 -4.9394460 -1.3697293 0.6902463 -1.3545265
13 14 15 16 17 18
7.0427427 4.0744525 6.8563967 0.6744525 3.5578232 -3.4898026
19 20 21 22 23 24
7.5890642 5.4530749 -0.9684250 2.2632848 -2.2215124 4.3634070
25 26 27 28 29 30
4.8909595 0.6661378 6.2591275 3.0516483 1.7936903 -4.0118935
31 32 33 34 35 36
12.6979699 3.1985609 -10.6642677 -10.4560753 -3.7787572 2.0496308
37 38 39 40 41 42
9.0433337 7.4177987 4.1971344 1.8487953 -4.3276873 5.6991519
43 44 45 46 47 48
9.6220783 13.4282532 -2.7546488 -1.3222257 -6.2145021 -7.9096315
49 50 51 52 53 54
-2.2123623 -12.5772084 -5.7690160 -11.0310091 -7.8268518 -7.5117713
55 56 57 58 59 60
-0.7102225 -4.6654497 -12.3193727 -7.4552398 -10.7241210 -6.7082050
> postscript(file="/var/www/html/rcomp/tmp/6cvhg1292667414.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 = 60
Frequency = 1
lag(myerror, k = 1) myerror
0 6.0724349 NA
1 -3.0386105 6.0724349
2 2.7020050 -3.0386105
3 -0.7510825 2.7020050
4 1.5965434 -0.7510825
5 8.7853757 1.5965434
6 9.4580677 8.7853757
7 2.0400119 9.4580677
8 -4.9394460 2.0400119
9 -1.3697293 -4.9394460
10 0.6902463 -1.3697293
11 -1.3545265 0.6902463
12 7.0427427 -1.3545265
13 4.0744525 7.0427427
14 6.8563967 4.0744525
15 0.6744525 6.8563967
16 3.5578232 0.6744525
17 -3.4898026 3.5578232
18 7.5890642 -3.4898026
19 5.4530749 7.5890642
20 -0.9684250 5.4530749
21 2.2632848 -0.9684250
22 -2.2215124 2.2632848
23 4.3634070 -2.2215124
24 4.8909595 4.3634070
25 0.6661378 4.8909595
26 6.2591275 0.6661378
27 3.0516483 6.2591275
28 1.7936903 3.0516483
29 -4.0118935 1.7936903
30 12.6979699 -4.0118935
31 3.1985609 12.6979699
32 -10.6642677 3.1985609
33 -10.4560753 -10.6642677
34 -3.7787572 -10.4560753
35 2.0496308 -3.7787572
36 9.0433337 2.0496308
37 7.4177987 9.0433337
38 4.1971344 7.4177987
39 1.8487953 4.1971344
40 -4.3276873 1.8487953
41 5.6991519 -4.3276873
42 9.6220783 5.6991519
43 13.4282532 9.6220783
44 -2.7546488 13.4282532
45 -1.3222257 -2.7546488
46 -6.2145021 -1.3222257
47 -7.9096315 -6.2145021
48 -2.2123623 -7.9096315
49 -12.5772084 -2.2123623
50 -5.7690160 -12.5772084
51 -11.0310091 -5.7690160
52 -7.8268518 -11.0310091
53 -7.5117713 -7.8268518
54 -0.7102225 -7.5117713
55 -4.6654497 -0.7102225
56 -12.3193727 -4.6654497
57 -7.4552398 -12.3193727
58 -10.7241210 -7.4552398
59 -6.7082050 -10.7241210
60 NA -6.7082050
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -3.0386105 6.0724349
[2,] 2.7020050 -3.0386105
[3,] -0.7510825 2.7020050
[4,] 1.5965434 -0.7510825
[5,] 8.7853757 1.5965434
[6,] 9.4580677 8.7853757
[7,] 2.0400119 9.4580677
[8,] -4.9394460 2.0400119
[9,] -1.3697293 -4.9394460
[10,] 0.6902463 -1.3697293
[11,] -1.3545265 0.6902463
[12,] 7.0427427 -1.3545265
[13,] 4.0744525 7.0427427
[14,] 6.8563967 4.0744525
[15,] 0.6744525 6.8563967
[16,] 3.5578232 0.6744525
[17,] -3.4898026 3.5578232
[18,] 7.5890642 -3.4898026
[19,] 5.4530749 7.5890642
[20,] -0.9684250 5.4530749
[21,] 2.2632848 -0.9684250
[22,] -2.2215124 2.2632848
[23,] 4.3634070 -2.2215124
[24,] 4.8909595 4.3634070
[25,] 0.6661378 4.8909595
[26,] 6.2591275 0.6661378
[27,] 3.0516483 6.2591275
[28,] 1.7936903 3.0516483
[29,] -4.0118935 1.7936903
[30,] 12.6979699 -4.0118935
[31,] 3.1985609 12.6979699
[32,] -10.6642677 3.1985609
[33,] -10.4560753 -10.6642677
[34,] -3.7787572 -10.4560753
[35,] 2.0496308 -3.7787572
[36,] 9.0433337 2.0496308
[37,] 7.4177987 9.0433337
[38,] 4.1971344 7.4177987
[39,] 1.8487953 4.1971344
[40,] -4.3276873 1.8487953
[41,] 5.6991519 -4.3276873
[42,] 9.6220783 5.6991519
[43,] 13.4282532 9.6220783
[44,] -2.7546488 13.4282532
[45,] -1.3222257 -2.7546488
[46,] -6.2145021 -1.3222257
[47,] -7.9096315 -6.2145021
[48,] -2.2123623 -7.9096315
[49,] -12.5772084 -2.2123623
[50,] -5.7690160 -12.5772084
[51,] -11.0310091 -5.7690160
[52,] -7.8268518 -11.0310091
[53,] -7.5117713 -7.8268518
[54,] -0.7102225 -7.5117713
[55,] -4.6654497 -0.7102225
[56,] -12.3193727 -4.6654497
[57,] -7.4552398 -12.3193727
[58,] -10.7241210 -7.4552398
[59,] -6.7082050 -10.7241210
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -3.0386105 6.0724349
2 2.7020050 -3.0386105
3 -0.7510825 2.7020050
4 1.5965434 -0.7510825
5 8.7853757 1.5965434
6 9.4580677 8.7853757
7 2.0400119 9.4580677
8 -4.9394460 2.0400119
9 -1.3697293 -4.9394460
10 0.6902463 -1.3697293
11 -1.3545265 0.6902463
12 7.0427427 -1.3545265
13 4.0744525 7.0427427
14 6.8563967 4.0744525
15 0.6744525 6.8563967
16 3.5578232 0.6744525
17 -3.4898026 3.5578232
18 7.5890642 -3.4898026
19 5.4530749 7.5890642
20 -0.9684250 5.4530749
21 2.2632848 -0.9684250
22 -2.2215124 2.2632848
23 4.3634070 -2.2215124
24 4.8909595 4.3634070
25 0.6661378 4.8909595
26 6.2591275 0.6661378
27 3.0516483 6.2591275
28 1.7936903 3.0516483
29 -4.0118935 1.7936903
30 12.6979699 -4.0118935
31 3.1985609 12.6979699
32 -10.6642677 3.1985609
33 -10.4560753 -10.6642677
34 -3.7787572 -10.4560753
35 2.0496308 -3.7787572
36 9.0433337 2.0496308
37 7.4177987 9.0433337
38 4.1971344 7.4177987
39 1.8487953 4.1971344
40 -4.3276873 1.8487953
41 5.6991519 -4.3276873
42 9.6220783 5.6991519
43 13.4282532 9.6220783
44 -2.7546488 13.4282532
45 -1.3222257 -2.7546488
46 -6.2145021 -1.3222257
47 -7.9096315 -6.2145021
48 -2.2123623 -7.9096315
49 -12.5772084 -2.2123623
50 -5.7690160 -12.5772084
51 -11.0310091 -5.7690160
52 -7.8268518 -11.0310091
53 -7.5117713 -7.8268518
54 -0.7102225 -7.5117713
55 -4.6654497 -0.7102225
56 -12.3193727 -4.6654497
57 -7.4552398 -12.3193727
58 -10.7241210 -7.4552398
59 -6.7082050 -10.7241210
> 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/7m5hj1292667414.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8m5hj1292667414.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9feg41292667414.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10feg41292667414.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11iwwr1292667414.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/12mfvx1292667414.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/13ipbo1292667414.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/143pru1292667414.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/157q8i1292667414.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/16a8661292667414.tab")
+ }
>
> try(system("convert tmp/18vja1292667414.ps tmp/18vja1292667414.png",intern=TRUE))
character(0)
> try(system("convert tmp/2j4iv1292667414.ps tmp/2j4iv1292667414.png",intern=TRUE))
character(0)
> try(system("convert tmp/3j4iv1292667414.ps tmp/3j4iv1292667414.png",intern=TRUE))
character(0)
> try(system("convert tmp/4j4iv1292667414.ps tmp/4j4iv1292667414.png",intern=TRUE))
character(0)
> try(system("convert tmp/5j4iv1292667414.ps tmp/5j4iv1292667414.png",intern=TRUE))
character(0)
> try(system("convert tmp/6cvhg1292667414.ps tmp/6cvhg1292667414.png",intern=TRUE))
character(0)
> try(system("convert tmp/7m5hj1292667414.ps tmp/7m5hj1292667414.png",intern=TRUE))
character(0)
> try(system("convert tmp/8m5hj1292667414.ps tmp/8m5hj1292667414.png",intern=TRUE))
character(0)
> try(system("convert tmp/9feg41292667414.ps tmp/9feg41292667414.png",intern=TRUE))
character(0)
> try(system("convert tmp/10feg41292667414.ps tmp/10feg41292667414.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
2.552 1.648 24.714