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## regression.R ---
## Author : Claus Dethlefsen
## Created On : Fri Mar 15 10:39:45 2002
## Last Modified By: Claus Dethlefsen
## Last Modified On: Wed Jan 07 08:57:33 2004
## Update Count : 16
## Status : Unknown, Use with caution!
###############################################################################
##
## Copyright (C) 2002 Susanne Gammelgaard Bottcher, Claus Dethlefsen
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; if not, write to the Free Software
## Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
######################################################################
n <- 1000
set.seed(109)
x <- seq(-2,2,length=n/2)
x2<- x^2
y1 <- rnorm(n/2,-5-x-x^2,.5)
y2 <- rnorm(n/2,+5+x+x^2,.5)
y <- c(y1,y2)
A <- factor(rep(c("A1","A2"),c(n/2,n/2)))
mypoly <- data.frame(x,x2,y,A)
names(mypoly)[2] <- "x^2"
fit <- network(mypoly)
fit.prior <- jointprior(fit)
res <- nwfsort( getnetwork(networkfamily(mypoly,fit,fit.prior)) )
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