swh:1:snp:dc80812a22a7696ce24055bd58afbf9f13e3e78c
Tip revision: e65e968c8f3853c5ed581ab3833000dc922d7456 authored by Bettina Gruen on 23 February 2011, 00:00:00 UTC
version 2.3-4
version 2.3-4
Tip revision: e65e968
patent.Rd
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% Copyright (C) 2004-2011 Friedrich Leisch and Bettina Gruen
% $Id: patent.Rd 4666 2011-02-23 15:52:35Z gruen $
%
\name{patent}
\alias{patent}
\docType{data}
\title{Patents and R\&D spending}
\description{
Number of patents, R\&D spending and sales in millions of dollar for 70
pharmaceutical and biomedical companies in 1976.
}
\usage{data("patent")}
\format{
A data frame with 70 observations on the following 4 variables.
\describe{
\item{Company}{Name of company.}
\item{Patents}{Number of patents.}
\item{RDS}{R\&D spending per sales.}
\item{lgRD}{Logarithmized R\&D spendings (in millions of dollars).}
}
}
\details{
The data is taken from the National Bureau of Economic Research R\&D Masterfile.
}
\source{
P. Wang, I.M. Cockburn and M.L. Puterman (1998): Analysis of Patent
Data - A Mixed-Poisson-Regression-Model Approach.
Journal of Business \& Economic Statistics 16 (1), pages 27-41.
}
\references{
B.H. Hall, C. Cummins, E. Laderman and J. Mundy (1988): The R\&D Master
File Documentation.
Technical Working Paper 72, National Bureau of Economic
Research. Cambridge, MA.
}
\examples{
data("patent")
patentMix <- stepFlexmix(Patents ~ lgRD, k=3,
model=FLXMRglm(family="poisson"),
concomitant=FLXPmultinom(~RDS),
nrep=5, data=patent)
plot(Patents ~ lgRD, data=patent,
pch=as.character(clusters(patentMix)))
ordering <- order(patent$lgRD)
apply(fitted(patentMix), 2, function(y)
lines(sort(patent$lgRD), y[ordering]))
}
\keyword{datasets}