\name{model.sel}
\alias{mod.sel}
\alias{model.sel}
\alias{model.sel.default}
\alias{model.sel.model.selection}
\alias{model.sel}
\encoding{utf-8}

\title{model selection table}
\description{
Build a model selection table.
}

\usage{

model.sel(object, ...)
%mod.sel(object, ...)

\method{model.sel}{model.selection}(object, rank = NULL, rank.args = NULL, ...)
\method{model.sel}{default}(object, ..., rank = NULL, rank.args = NULL)

}

\arguments{
	\item{object}{A fitted model object, a list of such objects, or a
	\code{"model.selection"} object.}

    \item{\dots}{ More fitted model objects. }

    \item{rank}{Optional, custom rank function (information criterion) to use
        instead of \code{AICc}, e.g. \code{QAIC} or \code{BIC}, may be omitted
        if \code{object} is a model list returned by \code{get.models}. }

    \item{rank.args}{Optional \code{list} of arguments for the \code{rank}
        function. If one is an expression, an \code{x} within it is substituted
        with a current model. }
}

\value{

An object of class \code{"model.selection"} with columns containing useful
information about each model: the coefficients, df, log-likelihood, the value of
the information criterion used, Delta(IC) and \sQuote{Akaike weight}. If any
arguments differ between the modelling function calls, the result will include
additional columns showing them (except for formulas and some other arguments).
}

\author{Kamil Barto\enc{ń}{n}}

\seealso{
\code{\link{dredge}}, \code{\link{AICc}}, \link[=MuMIn-models]{list of supported
models}.

Possible alternatives: \code{\link[bbmle]{ICtab}} (in package \pkg{bbmle}), or
 \code{\link[AICcmodavg]{aictab}} (\pkg{AICcmodavg}).
 
}

\examples{

data(Cement)
Cement$X1 <- cut(Cement$X1, 3)
Cement$X2 <- cut(Cement$X2, 2)

fm1 <- glm(formula = y ~ X1 + X2 * X3, data = Cement)
fm2 <- update(fm1, . ~ . - X1 - X2)
fm3 <- update(fm1, . ~ . - X2 - X3)

## ranked with AICc by default
(msAICc <- model.sel(fm1, fm2, fm3))

## ranked with BIC
model.sel(fm1, fm2, fm3, rank = AIC, rank.args = alist(k = log(nobs(x))))
# or
# model.sel(msAICc, rank = AIC, rank.args = alist(k = log(nobs(x))))
# or
# update(msAICc, rank = AIC, rank.args = alist(k = log(nobs(x))))


}

\keyword{models}