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\name{slice}
\alias{slice}
\alias{slice.clm}
\alias{plot.slice.clm}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Slice the likelihood of a clm
}
\description{
Slice likelihood and plot the slice. This is usefull for illustrating
the likelihood surface around the MLE (maximum likelihood estimate)
and provides graphics to substantiate (non-)convergence of a model
fit. Also, the closeness of a quadratic approximation to the
log-likelihood function can be inspected for relevant parameters. A
slice is considerably less computationally demanding than a profile.
}
\usage{
slice(object, ...)
\method{slice}{clm}(object, parm = seq_along(par), lambda = 3,
grid = 100, quad.approx = TRUE, ...)
\method{plot}{slice.clm}(x, parm = seq_along(x),
type = c("quadratic", "linear"), plot.mle = TRUE,
ask = prod(par("mfcol")) < length(parm) && dev.interactive(), ...)
}
%- maybe also 'usage' for other objects documented here.
\arguments{
\item{object}{for the \code{clm} method an object of class
\code{"clm"}, i.e., the result of a call to \code{clm}.
}
\item{x}{
a \code{slice.clm} object, i.e., the result of
\code{slice(clm.object)}.
}
\item{parm}{
for \code{slice.clm} a numeric or character vector indexing
parameters, for \code{plot.slice.clm} only a numeric vector is
accepted. By default all parameters are selected.
}
\item{lambda}{
the number of curvature units on each side of the MLE the slice
should cover.
}
\item{grid}{
the number of values at which to compute the log-likelihood for each
parameter.
}
\item{quad.approx}{
compute and include the quadratic approximation to the
log-likelihood function?
}
\item{type}{
\code{"quadratic"} plots the log-likelihood function which is
approximately quadratic, and \code{"linear"} plots the
signed square root of the log-likelihood function which is
approximately linear.
}
\item{plot.mle}{
include a vertical line at the MLE (maximum likelihood estimate)
when \code{type = "quadratic"}? Ignored for \code{type = "linear"}.
}
\item{ask}{
logical; if \code{TRUE}, the user is asked before each plot, see
\code{\link{par}}\code{(ask=.)}.
}
\item{\dots}{
further arguments to \code{plot.default} for the plot method. Not
used in the slice method.
}
}
%% \details{ bla
%% %% ~~ If necessary, more details than the description above ~~
%% }
\value{
The \code{slice} method returns a list of \code{data.frame}s with one
\code{data.frame} for each parameter slice. Each \code{data.frame}
contains in the first column the values of the parameter and in the
second column the values of the (positive) log-likelihood
\code{"logLik"}. A third column is present if \code{quad.approx = TRUE}
and contains the corresponding quadratic approximation to the
log-likelihood. The original model fit is included as the attribute
\code{"original.fit"}.
The \code{plot} method produces a plot of the likelihood slice for
each parameter.
}
\author{
Rune Haubo B Christensen
}
\examples{
## fit model:
fm1 <- clm(rating ~ contact + temp, data = wine)
## slice the likelihood:
sl1 <- slice(fm1)
## three different ways to plot the slices:
par(mfrow = c(2,3))
plot(sl1)
plot(sl1, type = "quadratic", plot.mle = FALSE)
plot(sl1, type = "linear")
## Verify convergence to the optimum:
sl2 <- slice(fm1, lambda = 1e-5, quad.approx = FALSE)
plot(sl2)
}
% Add one or more standard keywords, see file 'KEYWORDS' in the
% R documentation directory.
\keyword{models}
|
