\name{bild-class} \Rdversion{1.1} \docType{class} \alias{bild-class} \title{Class "bild" for results of a maximum likelihood estimation} \description{This class encapsulates results of a maximum likelihood procedure.} \section{Objects from the Class}{Objects can be created by calls of the form \code{new("bild", ...)}, but most often as the result of a call to \code{\link{bild}}.} \section{Slots}{ \describe{ \item{\code{coefficients}:}{Object of class \code{"matrix"}. Estimated parameters.} \item{\code{se}:}{Object of class \code{"matrix"}. Standard errors of estimated parameters.} \item{\code{covariance}:}{Object of class \code{"matrix"}. Covariance of estimated parameters.} \item{\code{correlation}:}{Object of class \code{"matrix"}. Correlation of estimated parameters.} \item{\code{log.likelihood}:}{Object of class \code{"numeric"}. The value of the log likelihood.} \item{\code{message}:}{Object of class \code{"integer"}. A character string giving any additional information returned by the optimizer, or NULL. See \code{\link[stats]{optim}} for details.} \item{\code{n.cases}:}{Object of class \code{"numeric"}. Number of individual profiles used in the optimization procedure.} \item{\code{ni.cases}:}{Object of class \code{"numeric"}. Number of individual profiles in the dataset.} \item{\code{aic}:}{Object of class \code{"numeric"}. The Akaike information criterion for a fitted model object.} \item{\code{residuals}:}{Object of class \code{"numeric"}. The residuals of estimated parameters.} \item{\code{s.residuals}:}{Object of class \code{"numeric"}. The residuals of estimated parameters summed over the individual profile.} \item{\code{ind.probability}:}{Object of class \code{"numeric"}. The transitions probabilities.} \item{\code{prob.matrix}:}{Object of class \code{"matrix"}. The matrix of transitions probabilities.} \item{\code{Fitted}:}{Object of class \code{"numeric"}. The fitted values for the estimated parameters.} \item{\code{Fitted.av}:}{Object of class \code{"numeric"}. } \item{\code{Time}:}{Object of class \code{"numeric"}. Vector of time points.} \item{\code{model.matrix}:}{Object of class \code{"matrix"}. The model matrix.} \item{\code{y.matrix}:}{Object of class \code{"matrix"}. The matrix of response values.} \item{\code{subset.data}:}{Object of class \code{"data.frame"}. The data subset if considered.} \item{\code{y.av}:}{Object of class \code{"numeric"}. The average of the response value over an individual profile.} \item{\code{f.value}:}{Object of class \code{"factor"}. Indicates the \code{aggregation} factor if present.} \item{\code{call}:}{Object of class \code{"language"}. The call to \code{"bild"}.} } } \section{Methods}{ \describe{ \item{plot}{\code{signature(x="bild", y="missing")}: Plots six type of plots.} \item{show}{\code{signature(object="bild")}: Display object briefly.} \item{summary}{\code{signature(object="bild")}: Generate object summary.} \item{getAIC}{\code{signature(object="bild")}: Returns a numeric value corresponding to the AIC of the fitted model.} \item{getLogLik}{\code{signature(object="bild")}: Returns a numeric value corresponding to the log-Likelihood of the fitted model.} } } \keyword{class}