R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
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> x <- array(list(10.9,0,10,0,9.2,0,9.2,0,9.5,0,9.6,0,9.5,0,9.1,0,8.9,0,9,0,10.1,0,10.3,0,10.2,0,9.6,0,9.2,0,9.3,0,9.4,0,9.4,0,9.2,0,9,0,9,0,9,0,9.8,0,10,0,9.8,0,9.3,0,9,0,9,0,9.1,0,9.1,0,9.1,0,9.2,0,8.8,0,8.3,0,8.4,0,8.1,0,7.7,1,7.9,1,7.9,1,8,1,7.9,1,7.6,1,7.1,1,6.8,1,6.5,1,6.9,1,8.2,1,8.7,1,8.3,1,7.9,1,7.5,1,7.8,1,8.3,1,8.4,1,8.2,1,7.7,1,7.2,1,7.3,1,8.1,1,8.5,1),dim=c(2,60),dimnames=list(c('Y','X'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Y','X'),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 = 'Include Monthly 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 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11
1 10.9 0 1 0 0 0 0 0 0 0 0 0 0
2 10.0 0 0 1 0 0 0 0 0 0 0 0 0
3 9.2 0 0 0 1 0 0 0 0 0 0 0 0
4 9.2 0 0 0 0 1 0 0 0 0 0 0 0
5 9.5 0 0 0 0 0 1 0 0 0 0 0 0
6 9.6 0 0 0 0 0 0 1 0 0 0 0 0
7 9.5 0 0 0 0 0 0 0 1 0 0 0 0
8 9.1 0 0 0 0 0 0 0 0 1 0 0 0
9 8.9 0 0 0 0 0 0 0 0 0 1 0 0
10 9.0 0 0 0 0 0 0 0 0 0 0 1 0
11 10.1 0 0 0 0 0 0 0 0 0 0 0 1
12 10.3 0 0 0 0 0 0 0 0 0 0 0 0
13 10.2 0 1 0 0 0 0 0 0 0 0 0 0
14 9.6 0 0 1 0 0 0 0 0 0 0 0 0
15 9.2 0 0 0 1 0 0 0 0 0 0 0 0
16 9.3 0 0 0 0 1 0 0 0 0 0 0 0
17 9.4 0 0 0 0 0 1 0 0 0 0 0 0
18 9.4 0 0 0 0 0 0 1 0 0 0 0 0
19 9.2 0 0 0 0 0 0 0 1 0 0 0 0
20 9.0 0 0 0 0 0 0 0 0 1 0 0 0
21 9.0 0 0 0 0 0 0 0 0 0 1 0 0
22 9.0 0 0 0 0 0 0 0 0 0 0 1 0
23 9.8 0 0 0 0 0 0 0 0 0 0 0 1
24 10.0 0 0 0 0 0 0 0 0 0 0 0 0
25 9.8 0 1 0 0 0 0 0 0 0 0 0 0
26 9.3 0 0 1 0 0 0 0 0 0 0 0 0
27 9.0 0 0 0 1 0 0 0 0 0 0 0 0
28 9.0 0 0 0 0 1 0 0 0 0 0 0 0
29 9.1 0 0 0 0 0 1 0 0 0 0 0 0
30 9.1 0 0 0 0 0 0 1 0 0 0 0 0
31 9.1 0 0 0 0 0 0 0 1 0 0 0 0
32 9.2 0 0 0 0 0 0 0 0 1 0 0 0
33 8.8 0 0 0 0 0 0 0 0 0 1 0 0
34 8.3 0 0 0 0 0 0 0 0 0 0 1 0
35 8.4 0 0 0 0 0 0 0 0 0 0 0 1
36 8.1 0 0 0 0 0 0 0 0 0 0 0 0
37 7.7 1 1 0 0 0 0 0 0 0 0 0 0
38 7.9 1 0 1 0 0 0 0 0 0 0 0 0
39 7.9 1 0 0 1 0 0 0 0 0 0 0 0
40 8.0 1 0 0 0 1 0 0 0 0 0 0 0
41 7.9 1 0 0 0 0 1 0 0 0 0 0 0
42 7.6 1 0 0 0 0 0 1 0 0 0 0 0
43 7.1 1 0 0 0 0 0 0 1 0 0 0 0
44 6.8 1 0 0 0 0 0 0 0 1 0 0 0
45 6.5 1 0 0 0 0 0 0 0 0 1 0 0
46 6.9 1 0 0 0 0 0 0 0 0 0 1 0
47 8.2 1 0 0 0 0 0 0 0 0 0 0 1
48 8.7 1 0 0 0 0 0 0 0 0 0 0 0
49 8.3 1 1 0 0 0 0 0 0 0 0 0 0
50 7.9 1 0 1 0 0 0 0 0 0 0 0 0
51 7.5 1 0 0 1 0 0 0 0 0 0 0 0
52 7.8 1 0 0 0 1 0 0 0 0 0 0 0
53 8.3 1 0 0 0 0 1 0 0 0 0 0 0
54 8.4 1 0 0 0 0 0 1 0 0 0 0 0
55 8.2 1 0 0 0 0 0 0 1 0 0 0 0
56 7.7 1 0 0 0 0 0 0 0 1 0 0 0
57 7.2 1 0 0 0 0 0 0 0 0 1 0 0
58 7.3 1 0 0 0 0 0 0 0 0 0 1 0
59 8.1 1 0 0 0 0 0 0 0 0 0 0 1
60 8.5 1 0 0 0 0 0 0 0 0 0 0 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) X M1 M2 M3 M4
9.742 -1.556 0.260 -0.180 -0.560 -0.460
M5 M6 M7 M8 M9 M10
-0.280 -0.300 -0.500 -0.760 -1.040 -1.020
M11
-0.200
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.64222 -0.15556 0.03778 0.26167 0.89778
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9.7422 0.2141 45.507 < 2e-16 ***
X -1.5556 0.1228 -12.669 < 2e-16 ***
M1 0.2600 0.2947 0.882 0.382105
M2 -0.1800 0.2947 -0.611 0.544259
M3 -0.5600 0.2947 -1.900 0.063532 .
M4 -0.4600 0.2947 -1.561 0.125234
M5 -0.2800 0.2947 -0.950 0.346887
M6 -0.3000 0.2947 -1.018 0.313871
M7 -0.5000 0.2947 -1.697 0.096362 .
M8 -0.7600 0.2947 -2.579 0.013098 *
M9 -1.0400 0.2947 -3.529 0.000944 ***
M10 -1.0200 0.2947 -3.461 0.001155 **
M11 -0.2000 0.2947 -0.679 0.500661
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.4659 on 47 degrees of freedom
Multiple R-squared: 0.8089, Adjusted R-squared: 0.76
F-statistic: 16.57 on 12 and 47 DF, p-value: 5.091e-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,] 0.296795934 0.593591869 0.7032041
[2,] 0.157223715 0.314447429 0.8427763
[3,] 0.083276290 0.166552579 0.9167237
[4,] 0.049305821 0.098611641 0.9506942
[5,] 0.022311384 0.044622768 0.9776886
[6,] 0.010737177 0.021474353 0.9892628
[7,] 0.004929955 0.009859911 0.9950700
[8,] 0.003646656 0.007293311 0.9963533
[9,] 0.002914287 0.005828574 0.9970857
[10,] 0.017136864 0.034273729 0.9828631
[11,] 0.018502363 0.037004726 0.9814976
[12,] 0.010666035 0.021332070 0.9893340
[13,] 0.006177200 0.012354400 0.9938228
[14,] 0.004164711 0.008329422 0.9958353
[15,] 0.003048493 0.006096987 0.9969515
[16,] 0.001889027 0.003778054 0.9981110
[17,] 0.002458895 0.004917791 0.9975411
[18,] 0.009886743 0.019773486 0.9901133
[19,] 0.060519640 0.121039280 0.9394804
[20,] 0.383818706 0.767637412 0.6161813
[21,] 0.726581287 0.546837427 0.2734187
[22,] 0.688176749 0.623646502 0.3118233
[23,] 0.611986587 0.776026826 0.3880134
[24,] 0.569965753 0.860068493 0.4300342
[25,] 0.480333018 0.960666036 0.5196670
[26,] 0.386507786 0.773015572 0.6134922
[27,] 0.378783406 0.757566812 0.6212166
[28,] 0.549775263 0.900449474 0.4502247
[29,] 0.697691864 0.604616271 0.3023081
> postscript(file="/var/www/html/rcomp/tmp/19wpe1258797598.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2ka6d1258797598.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/3xhfv1258797598.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4duir1258797598.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5xa0r1258797598.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
0.897777778 0.437777778 0.017777778 -0.082222222 0.037777778 0.157777778
7 8 9 10 11 12
0.257777778 0.117777778 0.197777778 0.277777778 0.557777778 0.557777778
13 14 15 16 17 18
0.197777778 0.037777778 0.017777778 0.017777778 -0.062222222 -0.042222222
19 20 21 22 23 24
-0.042222222 0.017777778 0.297777778 0.277777778 0.257777778 0.257777778
25 26 27 28 29 30
-0.202222222 -0.262222222 -0.182222222 -0.282222222 -0.362222222 -0.342222222
31 32 33 34 35 36
-0.142222222 0.217777778 0.097777778 -0.422222222 -1.142222222 -1.642222222
37 38 39 40 41 42
-0.746666667 -0.106666667 0.273333333 0.273333333 -0.006666667 -0.286666667
43 44 45 46 47 48
-0.586666667 -0.626666667 -0.646666667 -0.266666667 0.213333333 0.513333333
49 50 51 52 53 54
-0.146666667 -0.106666667 -0.126666667 0.073333333 0.393333333 0.513333333
55 56 57 58 59 60
0.513333333 0.273333333 0.053333333 0.133333333 0.113333333 0.313333333
> postscript(file="/var/www/html/rcomp/tmp/6eax21258797598.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 0.897777778 NA
1 0.437777778 0.897777778
2 0.017777778 0.437777778
3 -0.082222222 0.017777778
4 0.037777778 -0.082222222
5 0.157777778 0.037777778
6 0.257777778 0.157777778
7 0.117777778 0.257777778
8 0.197777778 0.117777778
9 0.277777778 0.197777778
10 0.557777778 0.277777778
11 0.557777778 0.557777778
12 0.197777778 0.557777778
13 0.037777778 0.197777778
14 0.017777778 0.037777778
15 0.017777778 0.017777778
16 -0.062222222 0.017777778
17 -0.042222222 -0.062222222
18 -0.042222222 -0.042222222
19 0.017777778 -0.042222222
20 0.297777778 0.017777778
21 0.277777778 0.297777778
22 0.257777778 0.277777778
23 0.257777778 0.257777778
24 -0.202222222 0.257777778
25 -0.262222222 -0.202222222
26 -0.182222222 -0.262222222
27 -0.282222222 -0.182222222
28 -0.362222222 -0.282222222
29 -0.342222222 -0.362222222
30 -0.142222222 -0.342222222
31 0.217777778 -0.142222222
32 0.097777778 0.217777778
33 -0.422222222 0.097777778
34 -1.142222222 -0.422222222
35 -1.642222222 -1.142222222
36 -0.746666667 -1.642222222
37 -0.106666667 -0.746666667
38 0.273333333 -0.106666667
39 0.273333333 0.273333333
40 -0.006666667 0.273333333
41 -0.286666667 -0.006666667
42 -0.586666667 -0.286666667
43 -0.626666667 -0.586666667
44 -0.646666667 -0.626666667
45 -0.266666667 -0.646666667
46 0.213333333 -0.266666667
47 0.513333333 0.213333333
48 -0.146666667 0.513333333
49 -0.106666667 -0.146666667
50 -0.126666667 -0.106666667
51 0.073333333 -0.126666667
52 0.393333333 0.073333333
53 0.513333333 0.393333333
54 0.513333333 0.513333333
55 0.273333333 0.513333333
56 0.053333333 0.273333333
57 0.133333333 0.053333333
58 0.113333333 0.133333333
59 0.313333333 0.113333333
60 NA 0.313333333
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] 0.437777778 0.897777778
[2,] 0.017777778 0.437777778
[3,] -0.082222222 0.017777778
[4,] 0.037777778 -0.082222222
[5,] 0.157777778 0.037777778
[6,] 0.257777778 0.157777778
[7,] 0.117777778 0.257777778
[8,] 0.197777778 0.117777778
[9,] 0.277777778 0.197777778
[10,] 0.557777778 0.277777778
[11,] 0.557777778 0.557777778
[12,] 0.197777778 0.557777778
[13,] 0.037777778 0.197777778
[14,] 0.017777778 0.037777778
[15,] 0.017777778 0.017777778
[16,] -0.062222222 0.017777778
[17,] -0.042222222 -0.062222222
[18,] -0.042222222 -0.042222222
[19,] 0.017777778 -0.042222222
[20,] 0.297777778 0.017777778
[21,] 0.277777778 0.297777778
[22,] 0.257777778 0.277777778
[23,] 0.257777778 0.257777778
[24,] -0.202222222 0.257777778
[25,] -0.262222222 -0.202222222
[26,] -0.182222222 -0.262222222
[27,] -0.282222222 -0.182222222
[28,] -0.362222222 -0.282222222
[29,] -0.342222222 -0.362222222
[30,] -0.142222222 -0.342222222
[31,] 0.217777778 -0.142222222
[32,] 0.097777778 0.217777778
[33,] -0.422222222 0.097777778
[34,] -1.142222222 -0.422222222
[35,] -1.642222222 -1.142222222
[36,] -0.746666667 -1.642222222
[37,] -0.106666667 -0.746666667
[38,] 0.273333333 -0.106666667
[39,] 0.273333333 0.273333333
[40,] -0.006666667 0.273333333
[41,] -0.286666667 -0.006666667
[42,] -0.586666667 -0.286666667
[43,] -0.626666667 -0.586666667
[44,] -0.646666667 -0.626666667
[45,] -0.266666667 -0.646666667
[46,] 0.213333333 -0.266666667
[47,] 0.513333333 0.213333333
[48,] -0.146666667 0.513333333
[49,] -0.106666667 -0.146666667
[50,] -0.126666667 -0.106666667
[51,] 0.073333333 -0.126666667
[52,] 0.393333333 0.073333333
[53,] 0.513333333 0.393333333
[54,] 0.513333333 0.513333333
[55,] 0.273333333 0.513333333
[56,] 0.053333333 0.273333333
[57,] 0.133333333 0.053333333
[58,] 0.113333333 0.133333333
[59,] 0.313333333 0.113333333
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 0.437777778 0.897777778
2 0.017777778 0.437777778
3 -0.082222222 0.017777778
4 0.037777778 -0.082222222
5 0.157777778 0.037777778
6 0.257777778 0.157777778
7 0.117777778 0.257777778
8 0.197777778 0.117777778
9 0.277777778 0.197777778
10 0.557777778 0.277777778
11 0.557777778 0.557777778
12 0.197777778 0.557777778
13 0.037777778 0.197777778
14 0.017777778 0.037777778
15 0.017777778 0.017777778
16 -0.062222222 0.017777778
17 -0.042222222 -0.062222222
18 -0.042222222 -0.042222222
19 0.017777778 -0.042222222
20 0.297777778 0.017777778
21 0.277777778 0.297777778
22 0.257777778 0.277777778
23 0.257777778 0.257777778
24 -0.202222222 0.257777778
25 -0.262222222 -0.202222222
26 -0.182222222 -0.262222222
27 -0.282222222 -0.182222222
28 -0.362222222 -0.282222222
29 -0.342222222 -0.362222222
30 -0.142222222 -0.342222222
31 0.217777778 -0.142222222
32 0.097777778 0.217777778
33 -0.422222222 0.097777778
34 -1.142222222 -0.422222222
35 -1.642222222 -1.142222222
36 -0.746666667 -1.642222222
37 -0.106666667 -0.746666667
38 0.273333333 -0.106666667
39 0.273333333 0.273333333
40 -0.006666667 0.273333333
41 -0.286666667 -0.006666667
42 -0.586666667 -0.286666667
43 -0.626666667 -0.586666667
44 -0.646666667 -0.626666667
45 -0.266666667 -0.646666667
46 0.213333333 -0.266666667
47 0.513333333 0.213333333
48 -0.146666667 0.513333333
49 -0.106666667 -0.146666667
50 -0.126666667 -0.106666667
51 0.073333333 -0.126666667
52 0.393333333 0.073333333
53 0.513333333 0.393333333
54 0.513333333 0.513333333
55 0.273333333 0.513333333
56 0.053333333 0.273333333
57 0.133333333 0.053333333
58 0.113333333 0.133333333
59 0.313333333 0.113333333
> 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/7abfx1258797598.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8521x1258797598.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9lqbf1258797598.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10ifmq1258797598.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11s8ex1258797598.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/12r46h1258797598.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/1375uc1258797598.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/14rn0e1258797598.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/15z4dt1258797598.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/160ksk1258797598.tab")
+ }
>
> system("convert tmp/19wpe1258797598.ps tmp/19wpe1258797598.png")
> system("convert tmp/2ka6d1258797598.ps tmp/2ka6d1258797598.png")
> system("convert tmp/3xhfv1258797598.ps tmp/3xhfv1258797598.png")
> system("convert tmp/4duir1258797598.ps tmp/4duir1258797598.png")
> system("convert tmp/5xa0r1258797598.ps tmp/5xa0r1258797598.png")
> system("convert tmp/6eax21258797598.ps tmp/6eax21258797598.png")
> system("convert tmp/7abfx1258797598.ps tmp/7abfx1258797598.png")
> system("convert tmp/8521x1258797598.ps tmp/8521x1258797598.png")
> system("convert tmp/9lqbf1258797598.ps tmp/9lqbf1258797598.png")
> system("convert tmp/10ifmq1258797598.ps tmp/10ifmq1258797598.png")
>
>
> proc.time()
user system elapsed
2.445 1.541 3.888