https://github.com/cran/RecordLinkage
Tip revision: 2b541c58b0e09eecd3e8c7c35fdadf24c4b468c4 authored by Andreas Borg on 23 March 2010, 00:00:00 UTC
version 0.2-0
version 0.2-0
Tip revision: 2b541c5
getParetoThreshold.Rd
\encoding{latin1}
\name{getParetoThreshold}
\Rdversion{1.1}
\alias{getParetoThreshold}
\title{
Estimate Threshold from Pareto Distribution
}
\description{
Calculates a classification threshold based on a generalized Pareto
distribution (GPD) fitted to the weights of the given data pairs.
}
\usage{
getParetoThreshold(rpairs, quantil = 0.95, interval = NA)
}
%- maybe also 'usage' for other objects documented here.
\arguments{
\item{rpairs}{
A \code{\link{RecLinkData}} object with weights. The data for which to
compute a threshold.
}
\item{quantil}{
A real number between 0 and 1. The quantil which to compute.
}
\item{interval}{
A numeric vector denoting the interval on which to fit
a GPD.
}
}
\details{
This threshold calculation is based on the assumption that weights in
the `middle' range (the region of 'possible links' in classical Record
Linkage) form a `fat tail' and can be fitted to a generalized Pareto
distribution (GPD). The limits of the interval which is subject to
fitting are usually determined by reviewing a mean residual life plot of
the data. If not supplied, a MRL plot is displayed from which the endpoints
can be selected by mouse input. If only one endpoint is selected or supplied,
the greater endpoint is set to the maximum weight.
A suitable interval is characterized by a relatively long, approximately
linear segment of the plot. For weights computed by \code{\link{emWeights}},
it is usally located around 0, for weights computed by
\code{\link{epiWeights}} between \eqn{0.5} and \eqn{1}.
}
\value{
The resulting threshold.
}
\references{
Sariyar et al.: Bestimmung der False Match-Rate im Fellegi-Sunter-Modell
mittels verallgemeinerte Paretoverteilung, Presentation for
54. Jahrestagung der Deutschen Gesellschaft für Medizinische
Informatik, Biometrie und Epidemiologie e.V. (GMDS).
}
\author{
Andreas Borg
}
\note{
The quality of matching varies, poor results can occur in some cases.
Evaluate carefully before applying to a real case.
}
\seealso{
\code{\link{emWeights}} and \code{\link{epiWeights}} for calculating weights,
\code{\link{emClassify}} and \code{\link{epiClassify}} for classifying with
the returned threshold.
}
\examples{
data(RLdata500)
rpairs=compare.dedup(RLdata500, identity=identity.RLdata500, strcmp=TRUE,
blockfld=list(1,3,5,6,7))
rpairs=epiWeights(rpairs)
# leave out argument interval to choose from plot
threshold=getParetoThreshold(rpairs,interval=c(0.68, 0.79))
summary(epiClassify(rpairs,threshold))
}
\keyword{models}
\keyword{classif}