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(22,0,22,0,20,0,21,0,20,0,21,0,21,0,21,0,19,0,21,0,21,0,22,0,19,0,24,0,22,0,22,0,22,0,24,0,22,0,23,0,24,0,21,0,20,0,22,0,23,0,23,0,22,0,20,0,21,1,21,1,20,1,20,1,17,1,18,1,19,1,19,1,20,1,21,1,20,1,21,1,19,1,22,1,20,1,18,1,16,1,17,1,18,1,19,1,18,1,20,1,21,1,18,1,19,1,19,1,19,1,21,1,19,1,19,1,17,1,16,1,16,1,17,1,16,1,15,1,16,1,16,1,16,1,18,1,19,1,16,1,16,1,16,1),dim=c(2,72),dimnames=list(c('Y','X'),1:72))
> y <- array(NA,dim=c(2,72),dimnames=list(c('Y','X'),1:72))
> 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
Y X
1 22 0
2 22 0
3 20 0
4 21 0
5 20 0
6 21 0
7 21 0
8 21 0
9 19 0
10 21 0
11 21 0
12 22 0
13 19 0
14 24 0
15 22 0
16 22 0
17 22 0
18 24 0
19 22 0
20 23 0
21 24 0
22 21 0
23 20 0
24 22 0
25 23 0
26 23 0
27 22 0
28 20 0
29 21 1
30 21 1
31 20 1
32 20 1
33 17 1
34 18 1
35 19 1
36 19 1
37 20 1
38 21 1
39 20 1
40 21 1
41 19 1
42 22 1
43 20 1
44 18 1
45 16 1
46 17 1
47 18 1
48 19 1
49 18 1
50 20 1
51 21 1
52 18 1
53 19 1
54 19 1
55 19 1
56 21 1
57 19 1
58 19 1
59 17 1
60 16 1
61 16 1
62 17 1
63 16 1
64 15 1
65 16 1
66 16 1
67 16 1
68 18 1
69 19 1
70 16 1
71 16 1
72 16 1
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X
21.571 -3.185
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-3.3864 -1.3864 0.4286 1.4286 3.6136
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 21.5714 0.3205 67.31 < 2e-16 ***
X -3.1851 0.4099 -7.77 4.85e-11 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.696 on 70 degrees of freedom
Multiple R-squared: 0.4631, Adjusted R-squared: 0.4554
F-statistic: 60.37 on 1 and 70 DF, p-value: 4.852e-11
> 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,] 0.27747679 0.55495359 0.7225232
[2,] 0.14220136 0.28440273 0.8577986
[3,] 0.06655959 0.13311918 0.9334404
[4,] 0.02879251 0.05758502 0.9712075
[5,] 0.07557868 0.15115737 0.9244213
[6,] 0.04025668 0.08051337 0.9597433
[7,] 0.02041927 0.04083855 0.9795807
[8,] 0.01719982 0.03439963 0.9828002
[9,] 0.03666149 0.07332299 0.9633385
[10,] 0.16989024 0.33978047 0.8301098
[11,] 0.13310159 0.26620318 0.8668984
[12,] 0.10130702 0.20261403 0.8986930
[13,] 0.07494251 0.14988502 0.9250575
[14,] 0.15095679 0.30191358 0.8490432
[15,] 0.11196517 0.22393034 0.8880348
[16,] 0.10800929 0.21601858 0.8919907
[17,] 0.16405677 0.32811353 0.8359432
[18,] 0.12443956 0.24887912 0.8755604
[19,] 0.12204650 0.24409299 0.8779535
[20,] 0.08952890 0.17905779 0.9104711
[21,] 0.08193043 0.16386086 0.9180696
[22,] 0.07662179 0.15324359 0.9233782
[23,] 0.05783259 0.11566518 0.9421674
[24,] 0.05227084 0.10454168 0.9477292
[25,] 0.04640426 0.09280853 0.9535957
[26,] 0.04248779 0.08497558 0.9575122
[27,] 0.03547373 0.07094747 0.9645263
[28,] 0.02868857 0.05737714 0.9713114
[29,] 0.05810757 0.11621514 0.9418924
[30,] 0.05190852 0.10381705 0.9480915
[31,] 0.03761295 0.07522591 0.9623870
[32,] 0.02664472 0.05328943 0.9733553
[33,] 0.02197260 0.04394520 0.9780274
[34,] 0.02927662 0.05855323 0.9707234
[35,] 0.02508519 0.05017038 0.9749148
[36,] 0.03551947 0.07103895 0.9644805
[37,] 0.02738952 0.05477904 0.9726105
[38,] 0.09186170 0.18372339 0.9081383
[39,] 0.09591812 0.19183625 0.9040819
[40,] 0.08819714 0.17639428 0.9118029
[41,] 0.16435516 0.32871031 0.8356448
[42,] 0.16985649 0.33971298 0.8301435
[43,] 0.14049067 0.28098133 0.8595093
[44,] 0.11778502 0.23557005 0.8822150
[45,] 0.09376885 0.18753771 0.9062311
[46,] 0.10676877 0.21353755 0.8932312
[47,] 0.22352096 0.44704191 0.7764790
[48,] 0.18836715 0.37673429 0.8116329
[49,] 0.17946010 0.35892020 0.8205399
[50,] 0.17678377 0.35356754 0.8232162
[51,] 0.18210589 0.36421179 0.8178941
[52,] 0.57867855 0.84264291 0.4213215
[53,] 0.69659311 0.60681378 0.3034069
[54,] 0.85358196 0.29283607 0.1464180
[55,] 0.82666087 0.34667827 0.1733391
[56,] 0.80532255 0.38935490 0.1946775
[57,] 0.77234794 0.45530411 0.2276521
[58,] 0.71166188 0.57667623 0.2883381
[59,] 0.64923708 0.70152584 0.3507629
[60,] 0.70289212 0.59421576 0.2971079
[61,] 0.62203754 0.75592492 0.3779625
[62,] 0.52689993 0.94620013 0.4731001
[63,] 0.42174646 0.84349293 0.5782535
> postscript(file="/var/www/html/rcomp/tmp/190ya1258724928.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2qplq1258724928.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3xyjt1258724928.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/40dop1258724928.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/53lsz1258724928.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 = 72
Frequency = 1
1 2 3 4 5 6 7
0.4285714 0.4285714 -1.5714286 -0.5714286 -1.5714286 -0.5714286 -0.5714286
8 9 10 11 12 13 14
-0.5714286 -2.5714286 -0.5714286 -0.5714286 0.4285714 -2.5714286 2.4285714
15 16 17 18 19 20 21
0.4285714 0.4285714 0.4285714 2.4285714 0.4285714 1.4285714 2.4285714
22 23 24 25 26 27 28
-0.5714286 -1.5714286 0.4285714 1.4285714 1.4285714 0.4285714 -1.5714286
29 30 31 32 33 34 35
2.6136364 2.6136364 1.6136364 1.6136364 -1.3863636 -0.3863636 0.6136364
36 37 38 39 40 41 42
0.6136364 1.6136364 2.6136364 1.6136364 2.6136364 0.6136364 3.6136364
43 44 45 46 47 48 49
1.6136364 -0.3863636 -2.3863636 -1.3863636 -0.3863636 0.6136364 -0.3863636
50 51 52 53 54 55 56
1.6136364 2.6136364 -0.3863636 0.6136364 0.6136364 0.6136364 2.6136364
57 58 59 60 61 62 63
0.6136364 0.6136364 -1.3863636 -2.3863636 -2.3863636 -1.3863636 -2.3863636
64 65 66 67 68 69 70
-3.3863636 -2.3863636 -2.3863636 -2.3863636 -0.3863636 0.6136364 -2.3863636
71 72
-2.3863636 -2.3863636
> postscript(file="/var/www/html/rcomp/tmp/6skx01258724928.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 = 72
Frequency = 1
lag(myerror, k = 1) myerror
0 0.4285714 NA
1 0.4285714 0.4285714
2 -1.5714286 0.4285714
3 -0.5714286 -1.5714286
4 -1.5714286 -0.5714286
5 -0.5714286 -1.5714286
6 -0.5714286 -0.5714286
7 -0.5714286 -0.5714286
8 -2.5714286 -0.5714286
9 -0.5714286 -2.5714286
10 -0.5714286 -0.5714286
11 0.4285714 -0.5714286
12 -2.5714286 0.4285714
13 2.4285714 -2.5714286
14 0.4285714 2.4285714
15 0.4285714 0.4285714
16 0.4285714 0.4285714
17 2.4285714 0.4285714
18 0.4285714 2.4285714
19 1.4285714 0.4285714
20 2.4285714 1.4285714
21 -0.5714286 2.4285714
22 -1.5714286 -0.5714286
23 0.4285714 -1.5714286
24 1.4285714 0.4285714
25 1.4285714 1.4285714
26 0.4285714 1.4285714
27 -1.5714286 0.4285714
28 2.6136364 -1.5714286
29 2.6136364 2.6136364
30 1.6136364 2.6136364
31 1.6136364 1.6136364
32 -1.3863636 1.6136364
33 -0.3863636 -1.3863636
34 0.6136364 -0.3863636
35 0.6136364 0.6136364
36 1.6136364 0.6136364
37 2.6136364 1.6136364
38 1.6136364 2.6136364
39 2.6136364 1.6136364
40 0.6136364 2.6136364
41 3.6136364 0.6136364
42 1.6136364 3.6136364
43 -0.3863636 1.6136364
44 -2.3863636 -0.3863636
45 -1.3863636 -2.3863636
46 -0.3863636 -1.3863636
47 0.6136364 -0.3863636
48 -0.3863636 0.6136364
49 1.6136364 -0.3863636
50 2.6136364 1.6136364
51 -0.3863636 2.6136364
52 0.6136364 -0.3863636
53 0.6136364 0.6136364
54 0.6136364 0.6136364
55 2.6136364 0.6136364
56 0.6136364 2.6136364
57 0.6136364 0.6136364
58 -1.3863636 0.6136364
59 -2.3863636 -1.3863636
60 -2.3863636 -2.3863636
61 -1.3863636 -2.3863636
62 -2.3863636 -1.3863636
63 -3.3863636 -2.3863636
64 -2.3863636 -3.3863636
65 -2.3863636 -2.3863636
66 -2.3863636 -2.3863636
67 -0.3863636 -2.3863636
68 0.6136364 -0.3863636
69 -2.3863636 0.6136364
70 -2.3863636 -2.3863636
71 -2.3863636 -2.3863636
72 NA -2.3863636
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.4285714 0.4285714
[2,] -1.5714286 0.4285714
[3,] -0.5714286 -1.5714286
[4,] -1.5714286 -0.5714286
[5,] -0.5714286 -1.5714286
[6,] -0.5714286 -0.5714286
[7,] -0.5714286 -0.5714286
[8,] -2.5714286 -0.5714286
[9,] -0.5714286 -2.5714286
[10,] -0.5714286 -0.5714286
[11,] 0.4285714 -0.5714286
[12,] -2.5714286 0.4285714
[13,] 2.4285714 -2.5714286
[14,] 0.4285714 2.4285714
[15,] 0.4285714 0.4285714
[16,] 0.4285714 0.4285714
[17,] 2.4285714 0.4285714
[18,] 0.4285714 2.4285714
[19,] 1.4285714 0.4285714
[20,] 2.4285714 1.4285714
[21,] -0.5714286 2.4285714
[22,] -1.5714286 -0.5714286
[23,] 0.4285714 -1.5714286
[24,] 1.4285714 0.4285714
[25,] 1.4285714 1.4285714
[26,] 0.4285714 1.4285714
[27,] -1.5714286 0.4285714
[28,] 2.6136364 -1.5714286
[29,] 2.6136364 2.6136364
[30,] 1.6136364 2.6136364
[31,] 1.6136364 1.6136364
[32,] -1.3863636 1.6136364
[33,] -0.3863636 -1.3863636
[34,] 0.6136364 -0.3863636
[35,] 0.6136364 0.6136364
[36,] 1.6136364 0.6136364
[37,] 2.6136364 1.6136364
[38,] 1.6136364 2.6136364
[39,] 2.6136364 1.6136364
[40,] 0.6136364 2.6136364
[41,] 3.6136364 0.6136364
[42,] 1.6136364 3.6136364
[43,] -0.3863636 1.6136364
[44,] -2.3863636 -0.3863636
[45,] -1.3863636 -2.3863636
[46,] -0.3863636 -1.3863636
[47,] 0.6136364 -0.3863636
[48,] -0.3863636 0.6136364
[49,] 1.6136364 -0.3863636
[50,] 2.6136364 1.6136364
[51,] -0.3863636 2.6136364
[52,] 0.6136364 -0.3863636
[53,] 0.6136364 0.6136364
[54,] 0.6136364 0.6136364
[55,] 2.6136364 0.6136364
[56,] 0.6136364 2.6136364
[57,] 0.6136364 0.6136364
[58,] -1.3863636 0.6136364
[59,] -2.3863636 -1.3863636
[60,] -2.3863636 -2.3863636
[61,] -1.3863636 -2.3863636
[62,] -2.3863636 -1.3863636
[63,] -3.3863636 -2.3863636
[64,] -2.3863636 -3.3863636
[65,] -2.3863636 -2.3863636
[66,] -2.3863636 -2.3863636
[67,] -0.3863636 -2.3863636
[68,] 0.6136364 -0.3863636
[69,] -2.3863636 0.6136364
[70,] -2.3863636 -2.3863636
[71,] -2.3863636 -2.3863636
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.4285714 0.4285714
2 -1.5714286 0.4285714
3 -0.5714286 -1.5714286
4 -1.5714286 -0.5714286
5 -0.5714286 -1.5714286
6 -0.5714286 -0.5714286
7 -0.5714286 -0.5714286
8 -2.5714286 -0.5714286
9 -0.5714286 -2.5714286
10 -0.5714286 -0.5714286
11 0.4285714 -0.5714286
12 -2.5714286 0.4285714
13 2.4285714 -2.5714286
14 0.4285714 2.4285714
15 0.4285714 0.4285714
16 0.4285714 0.4285714
17 2.4285714 0.4285714
18 0.4285714 2.4285714
19 1.4285714 0.4285714
20 2.4285714 1.4285714
21 -0.5714286 2.4285714
22 -1.5714286 -0.5714286
23 0.4285714 -1.5714286
24 1.4285714 0.4285714
25 1.4285714 1.4285714
26 0.4285714 1.4285714
27 -1.5714286 0.4285714
28 2.6136364 -1.5714286
29 2.6136364 2.6136364
30 1.6136364 2.6136364
31 1.6136364 1.6136364
32 -1.3863636 1.6136364
33 -0.3863636 -1.3863636
34 0.6136364 -0.3863636
35 0.6136364 0.6136364
36 1.6136364 0.6136364
37 2.6136364 1.6136364
38 1.6136364 2.6136364
39 2.6136364 1.6136364
40 0.6136364 2.6136364
41 3.6136364 0.6136364
42 1.6136364 3.6136364
43 -0.3863636 1.6136364
44 -2.3863636 -0.3863636
45 -1.3863636 -2.3863636
46 -0.3863636 -1.3863636
47 0.6136364 -0.3863636
48 -0.3863636 0.6136364
49 1.6136364 -0.3863636
50 2.6136364 1.6136364
51 -0.3863636 2.6136364
52 0.6136364 -0.3863636
53 0.6136364 0.6136364
54 0.6136364 0.6136364
55 2.6136364 0.6136364
56 0.6136364 2.6136364
57 0.6136364 0.6136364
58 -1.3863636 0.6136364
59 -2.3863636 -1.3863636
60 -2.3863636 -2.3863636
61 -1.3863636 -2.3863636
62 -2.3863636 -1.3863636
63 -3.3863636 -2.3863636
64 -2.3863636 -3.3863636
65 -2.3863636 -2.3863636
66 -2.3863636 -2.3863636
67 -0.3863636 -2.3863636
68 0.6136364 -0.3863636
69 -2.3863636 0.6136364
70 -2.3863636 -2.3863636
71 -2.3863636 -2.3863636
> 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/7n0h01258724928.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8mrho1258724928.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9zmlt1258724928.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10sanr1258724928.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/118zir1258724928.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/12ozej1258724928.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/13ft821258724928.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/14si9t1258724929.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/157qbv1258724929.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/16san61258724929.tab")
+ }
>
> system("convert tmp/190ya1258724928.ps tmp/190ya1258724928.png")
> system("convert tmp/2qplq1258724928.ps tmp/2qplq1258724928.png")
> system("convert tmp/3xyjt1258724928.ps tmp/3xyjt1258724928.png")
> system("convert tmp/40dop1258724928.ps tmp/40dop1258724928.png")
> system("convert tmp/53lsz1258724928.ps tmp/53lsz1258724928.png")
> system("convert tmp/6skx01258724928.ps tmp/6skx01258724928.png")
> system("convert tmp/7n0h01258724928.ps tmp/7n0h01258724928.png")
> system("convert tmp/8mrho1258724928.ps tmp/8mrho1258724928.png")
> system("convert tmp/9zmlt1258724928.ps tmp/9zmlt1258724928.png")
> system("convert tmp/10sanr1258724928.ps tmp/10sanr1258724928.png")
>
>
> proc.time()
user system elapsed
2.682 1.603 5.230