R version 2.7.0 (2008-04-22)
Copyright (C) 2008 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.
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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(6.06,0,5.983,0,6.11,0,6.143,0,6.093,0,6.148,0,6.464,0,6.532,0,6.321,0,6.23,0,6.176,0,6.338,0,6.462,0,6.401,0,6.46,0,6.519,0,6.542,0,6.637,0,7.114,0,7.579,0,7.408,0,8.243,0,8.243,0,8.434,0,8.576,0,8.58,0,8.645,0,8.66,0,8.72,0,8.787,0,9.162,0,9.144,0,8.806,0,8.778,0,8.66,0,8.826,0,8.609,1,8.628,1,8.619,1,8.775,1,8.84,1,8.745,1,9.092,1,8.934,1,8.749,1,8.298,1,8.067,1,7.969,1,7.999,0,7.865,0,7.746,0,7.633,0,7.458,0,7.391,0,7.856,0,7.72,0,7.297,0,7.123,0,7.004,0,7.151,0),dim=c(2,60),dimnames=list(c('Textiel','dummy'),1:60))
> y <- array(NA,dim=c(2,60),dimnames=list(c('Textiel','dummy'),1:60))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Textiel dummy
1 6.060 0
2 5.983 0
3 6.110 0
4 6.143 0
5 6.093 0
6 6.148 0
7 6.464 0
8 6.532 0
9 6.321 0
10 6.230 0
11 6.176 0
12 6.338 0
13 6.462 0
14 6.401 0
15 6.460 0
16 6.519 0
17 6.542 0
18 6.637 0
19 7.114 0
20 7.579 0
21 7.408 0
22 8.243 0
23 8.243 0
24 8.434 0
25 8.576 0
26 8.580 0
27 8.645 0
28 8.660 0
29 8.720 0
30 8.787 0
31 9.162 0
32 9.144 0
33 8.806 0
34 8.778 0
35 8.660 0
36 8.826 0
37 8.609 1
38 8.628 1
39 8.619 1
40 8.775 1
41 8.840 1
42 8.745 1
43 9.092 1
44 8.934 1
45 8.749 1
46 8.298 1
47 8.067 1
48 7.969 1
49 7.999 0
50 7.865 0
51 7.746 0
52 7.633 0
53 7.458 0
54 7.391 0
55 7.856 0
56 7.720 0
57 7.297 0
58 7.123 0
59 7.004 0
60 7.151 0
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) dummy
7.421 1.189
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-1.43840 -0.89265 0.01308 0.63860 1.74060
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 7.4214 0.1345 55.158 < 2e-16 ***
dummy 1.1890 0.3009 3.952 0.000213 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.9322 on 58 degrees of freedom
Multiple R-squared: 0.2122, Adjusted R-squared: 0.1986
F-statistic: 15.62 on 1 and 58 DF, p-value: 0.0002128
> 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,] 7.293033e-04 1.458607e-03 9.992707e-01
[2,] 8.532257e-05 1.706451e-04 9.999147e-01
[3,] 8.616457e-04 1.723291e-03 9.991384e-01
[4,] 1.106612e-03 2.213223e-03 9.988934e-01
[5,] 3.483022e-04 6.966045e-04 9.996517e-01
[6,] 9.837756e-05 1.967551e-04 9.999016e-01
[7,] 2.991105e-05 5.982210e-05 9.999701e-01
[8,] 1.152449e-05 2.304898e-05 9.999885e-01
[9,] 8.436672e-06 1.687334e-05 9.999916e-01
[10,] 4.643975e-06 9.287949e-06 9.999954e-01
[11,] 3.654259e-06 7.308517e-06 9.999963e-01
[12,] 4.257350e-06 8.514700e-06 9.999957e-01
[13,] 6.115605e-06 1.223121e-05 9.999939e-01
[14,] 1.612785e-05 3.225570e-05 9.999839e-01
[15,] 7.478727e-04 1.495745e-03 9.992521e-01
[16,] 3.161666e-02 6.323331e-02 9.683833e-01
[17,] 9.520081e-02 1.904016e-01 9.047992e-01
[18,] 4.775585e-01 9.551170e-01 5.224415e-01
[19,] 7.352408e-01 5.295183e-01 2.647592e-01
[20,] 8.852062e-01 2.295875e-01 1.147938e-01
[21,] 9.529449e-01 9.411012e-02 4.705506e-02
[22,] 9.770469e-01 4.590620e-02 2.295310e-02
[23,] 9.881450e-01 2.371000e-02 1.185500e-02
[24,] 9.931470e-01 1.370610e-02 6.853049e-03
[25,] 9.960322e-01 7.935692e-03 3.967846e-03
[26,] 9.978306e-01 4.338783e-03 2.169391e-03
[27,] 9.995636e-01 8.727413e-04 4.363707e-04
[28,] 9.999358e-01 1.283302e-04 6.416510e-05
[29,] 9.999784e-01 4.329590e-05 2.164795e-05
[30,] 9.999945e-01 1.097054e-05 5.485269e-06
[31,] 9.999987e-01 2.618170e-06 1.309085e-06
[32,] 1.000000e+00 4.734962e-08 2.367481e-08
[33,] 9.999999e-01 1.721993e-07 8.609964e-08
[34,] 9.999997e-01 6.028207e-07 3.014104e-07
[35,] 9.999990e-01 2.034505e-06 1.017252e-06
[36,] 9.999970e-01 5.960996e-06 2.980498e-06
[37,] 9.999925e-01 1.491404e-05 7.457022e-06
[38,] 9.999799e-01 4.018424e-05 2.009212e-05
[39,] 9.999826e-01 3.473975e-05 1.736988e-05
[40,] 9.999846e-01 3.089377e-05 1.544688e-05
[41,] 9.999856e-01 2.875525e-05 1.437763e-05
[42,] 9.999608e-01 7.842957e-05 3.921478e-05
[43,] 9.998735e-01 2.529307e-04 1.264654e-04
[44,] 9.996027e-01 7.946419e-04 3.973210e-04
[45,] 9.995328e-01 9.344583e-04 4.672292e-04
[46,] 9.992441e-01 1.511785e-03 7.558926e-04
[47,] 9.983891e-01 3.221884e-03 1.610942e-03
[48,] 9.957274e-01 8.545223e-03 4.272612e-03
[49,] 9.862795e-01 2.744098e-02 1.372049e-02
[50,] 9.583408e-01 8.331846e-02 4.165923e-02
[51,] 9.542681e-01 9.146375e-02 4.573188e-02
> postscript(file="/var/www/html/rcomp/tmp/1ajzd1227351524.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$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2t87q1227351524.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$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/35xsi1227351524.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4lbja1227351524.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5q82g1227351524.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
-1.361395833 -1.438395833 -1.311395833 -1.278395833 -1.328395833 -1.273395833
7 8 9 10 11 12
-0.957395833 -0.889395833 -1.100395833 -1.191395833 -1.245395833 -1.083395833
13 14 15 16 17 18
-0.959395833 -1.020395833 -0.961395833 -0.902395833 -0.879395833 -0.784395833
19 20 21 22 23 24
-0.307395833 0.157604167 -0.013395833 0.821604167 0.821604167 1.012604167
25 26 27 28 29 30
1.154604167 1.158604167 1.223604167 1.238604167 1.298604167 1.365604167
31 32 33 34 35 36
1.740604167 1.722604167 1.384604167 1.356604167 1.238604167 1.404604167
37 38 39 40 41 42
-0.001416667 0.017583333 0.008583333 0.164583333 0.229583333 0.134583333
43 44 45 46 47 48
0.481583333 0.323583333 0.138583333 -0.312416667 -0.543416667 -0.641416667
49 50 51 52 53 54
0.577604167 0.443604167 0.324604167 0.211604167 0.036604167 -0.030395833
55 56 57 58 59 60
0.434604167 0.298604167 -0.124395833 -0.298395833 -0.417395833 -0.270395833
> postscript(file="/var/www/html/rcomp/tmp/6r7p71227351524.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 -1.361395833 NA
1 -1.438395833 -1.361395833
2 -1.311395833 -1.438395833
3 -1.278395833 -1.311395833
4 -1.328395833 -1.278395833
5 -1.273395833 -1.328395833
6 -0.957395833 -1.273395833
7 -0.889395833 -0.957395833
8 -1.100395833 -0.889395833
9 -1.191395833 -1.100395833
10 -1.245395833 -1.191395833
11 -1.083395833 -1.245395833
12 -0.959395833 -1.083395833
13 -1.020395833 -0.959395833
14 -0.961395833 -1.020395833
15 -0.902395833 -0.961395833
16 -0.879395833 -0.902395833
17 -0.784395833 -0.879395833
18 -0.307395833 -0.784395833
19 0.157604167 -0.307395833
20 -0.013395833 0.157604167
21 0.821604167 -0.013395833
22 0.821604167 0.821604167
23 1.012604167 0.821604167
24 1.154604167 1.012604167
25 1.158604167 1.154604167
26 1.223604167 1.158604167
27 1.238604167 1.223604167
28 1.298604167 1.238604167
29 1.365604167 1.298604167
30 1.740604167 1.365604167
31 1.722604167 1.740604167
32 1.384604167 1.722604167
33 1.356604167 1.384604167
34 1.238604167 1.356604167
35 1.404604167 1.238604167
36 -0.001416667 1.404604167
37 0.017583333 -0.001416667
38 0.008583333 0.017583333
39 0.164583333 0.008583333
40 0.229583333 0.164583333
41 0.134583333 0.229583333
42 0.481583333 0.134583333
43 0.323583333 0.481583333
44 0.138583333 0.323583333
45 -0.312416667 0.138583333
46 -0.543416667 -0.312416667
47 -0.641416667 -0.543416667
48 0.577604167 -0.641416667
49 0.443604167 0.577604167
50 0.324604167 0.443604167
51 0.211604167 0.324604167
52 0.036604167 0.211604167
53 -0.030395833 0.036604167
54 0.434604167 -0.030395833
55 0.298604167 0.434604167
56 -0.124395833 0.298604167
57 -0.298395833 -0.124395833
58 -0.417395833 -0.298395833
59 -0.270395833 -0.417395833
60 NA -0.270395833
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -1.438395833 -1.361395833
[2,] -1.311395833 -1.438395833
[3,] -1.278395833 -1.311395833
[4,] -1.328395833 -1.278395833
[5,] -1.273395833 -1.328395833
[6,] -0.957395833 -1.273395833
[7,] -0.889395833 -0.957395833
[8,] -1.100395833 -0.889395833
[9,] -1.191395833 -1.100395833
[10,] -1.245395833 -1.191395833
[11,] -1.083395833 -1.245395833
[12,] -0.959395833 -1.083395833
[13,] -1.020395833 -0.959395833
[14,] -0.961395833 -1.020395833
[15,] -0.902395833 -0.961395833
[16,] -0.879395833 -0.902395833
[17,] -0.784395833 -0.879395833
[18,] -0.307395833 -0.784395833
[19,] 0.157604167 -0.307395833
[20,] -0.013395833 0.157604167
[21,] 0.821604167 -0.013395833
[22,] 0.821604167 0.821604167
[23,] 1.012604167 0.821604167
[24,] 1.154604167 1.012604167
[25,] 1.158604167 1.154604167
[26,] 1.223604167 1.158604167
[27,] 1.238604167 1.223604167
[28,] 1.298604167 1.238604167
[29,] 1.365604167 1.298604167
[30,] 1.740604167 1.365604167
[31,] 1.722604167 1.740604167
[32,] 1.384604167 1.722604167
[33,] 1.356604167 1.384604167
[34,] 1.238604167 1.356604167
[35,] 1.404604167 1.238604167
[36,] -0.001416667 1.404604167
[37,] 0.017583333 -0.001416667
[38,] 0.008583333 0.017583333
[39,] 0.164583333 0.008583333
[40,] 0.229583333 0.164583333
[41,] 0.134583333 0.229583333
[42,] 0.481583333 0.134583333
[43,] 0.323583333 0.481583333
[44,] 0.138583333 0.323583333
[45,] -0.312416667 0.138583333
[46,] -0.543416667 -0.312416667
[47,] -0.641416667 -0.543416667
[48,] 0.577604167 -0.641416667
[49,] 0.443604167 0.577604167
[50,] 0.324604167 0.443604167
[51,] 0.211604167 0.324604167
[52,] 0.036604167 0.211604167
[53,] -0.030395833 0.036604167
[54,] 0.434604167 -0.030395833
[55,] 0.298604167 0.434604167
[56,] -0.124395833 0.298604167
[57,] -0.298395833 -0.124395833
[58,] -0.417395833 -0.298395833
[59,] -0.270395833 -0.417395833
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -1.438395833 -1.361395833
2 -1.311395833 -1.438395833
3 -1.278395833 -1.311395833
4 -1.328395833 -1.278395833
5 -1.273395833 -1.328395833
6 -0.957395833 -1.273395833
7 -0.889395833 -0.957395833
8 -1.100395833 -0.889395833
9 -1.191395833 -1.100395833
10 -1.245395833 -1.191395833
11 -1.083395833 -1.245395833
12 -0.959395833 -1.083395833
13 -1.020395833 -0.959395833
14 -0.961395833 -1.020395833
15 -0.902395833 -0.961395833
16 -0.879395833 -0.902395833
17 -0.784395833 -0.879395833
18 -0.307395833 -0.784395833
19 0.157604167 -0.307395833
20 -0.013395833 0.157604167
21 0.821604167 -0.013395833
22 0.821604167 0.821604167
23 1.012604167 0.821604167
24 1.154604167 1.012604167
25 1.158604167 1.154604167
26 1.223604167 1.158604167
27 1.238604167 1.223604167
28 1.298604167 1.238604167
29 1.365604167 1.298604167
30 1.740604167 1.365604167
31 1.722604167 1.740604167
32 1.384604167 1.722604167
33 1.356604167 1.384604167
34 1.238604167 1.356604167
35 1.404604167 1.238604167
36 -0.001416667 1.404604167
37 0.017583333 -0.001416667
38 0.008583333 0.017583333
39 0.164583333 0.008583333
40 0.229583333 0.164583333
41 0.134583333 0.229583333
42 0.481583333 0.134583333
43 0.323583333 0.481583333
44 0.138583333 0.323583333
45 -0.312416667 0.138583333
46 -0.543416667 -0.312416667
47 -0.641416667 -0.543416667
48 0.577604167 -0.641416667
49 0.443604167 0.577604167
50 0.324604167 0.443604167
51 0.211604167 0.324604167
52 0.036604167 0.211604167
53 -0.030395833 0.036604167
54 0.434604167 -0.030395833
55 0.298604167 0.434604167
56 -0.124395833 0.298604167
57 -0.298395833 -0.124395833
58 -0.417395833 -0.298395833
59 -0.270395833 -0.417395833
> 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/7tayq1227351524.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8otqj1227351525.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9yoj91227351525.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10g5vx1227351525.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$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/11ggq11227351525.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/1248go1227351525.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/13yf4k1227351525.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/14mq3y1227351525.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/150ats1227351525.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/16abyj1227351525.tab")
+ }
>
> system("convert tmp/1ajzd1227351524.ps tmp/1ajzd1227351524.png")
> system("convert tmp/2t87q1227351524.ps tmp/2t87q1227351524.png")
> system("convert tmp/35xsi1227351524.ps tmp/35xsi1227351524.png")
> system("convert tmp/4lbja1227351524.ps tmp/4lbja1227351524.png")
> system("convert tmp/5q82g1227351524.ps tmp/5q82g1227351524.png")
> system("convert tmp/6r7p71227351524.ps tmp/6r7p71227351524.png")
> system("convert tmp/7tayq1227351524.ps tmp/7tayq1227351524.png")
> system("convert tmp/8otqj1227351525.ps tmp/8otqj1227351525.png")
> system("convert tmp/9yoj91227351525.ps tmp/9yoj91227351525.png")
> system("convert tmp/10g5vx1227351525.ps tmp/10g5vx1227351525.png")
>
>
> proc.time()
user system elapsed
5.018 2.744 5.402