# No code here, just documentation!
#' A fitted Mixture Model Detection Function Object
#'
#' The fitted mixture model detection function object returned by
#' \code{\link{fitmix}}. Knowledge of most of this is not useful. Use
#' \code{link{summary.ds.mixture}} for result summaries.
#'
#' @name ds.mixture
#' @section Details:
#' A \code{\link{ds.mixture}} object has the following elements:
#' \tabular{ll}{
#' distance \tab Vector of distances used in the analysis.\cr
#' likelihood \tab Value of the log-likelihood at the maxima.\cr
#' pars \tab Parmeter estimates. See \code{\link{mmds.pars}} for more
#' information.\cr
#' mix.terms \tab Number of mixture terms fit.\cr
#' width \tab Truncation distance used.\cr
#' z \tab List containing the matrix of covariates used. Output from
#' \code{\link{model.matrix}}.\cr
#' zdim \tab Number of columns of \code{z}. See \code{\link{mmds.pars}} for
#' more information.\cr
#' hessian \tab Hessian matrix at the maxima.\cr
#' pt \tab Logical indicating whether the data were from a point transect
#' survey.\cr
#' data \tab Data frame after truncation.\cr
#' ftype \tab Type of detection function.\cr
#' ctrl.options \tab Options passed to \code{\link{optim}}.\cr
#' showit \tab Debug level.\cr
#' opt.method \tab Optimisation method used.\cr
#' usegrad \tab Were analytic gradients used?\cr
#' model.formula \tab Model formula.\cr
#' mu \tab Per-observation effective trip width/effective area of
#' detection.\cr
#' pa.vec \tab Vector of per-observation detectabilities.\cr
#' N \tab Estimate of N in the covered area (Horvitz-Thompson).\cr
#' pa \tab Average detectability.\cr
#' pars.se \tab Standard errors of the parameters.\cr
#' N.se \tab Standard error of the Horvitz-Thompson estimate of the
#' abundance.\cr
#' pa.se \tab Standard error of the average detectability.\cr
#' aic \tab AIC of the fitted model.\cr
#' cvm \tab Cramer-von Mises GoF test results. List containing: \code{p},
#' the p-value and \code{W}, the test statistic.\cr
#' ks \tab Kolmogorov-Smirnov test results. List containing: \code{p}, the
#' p-value and \code{Dn}, the test statistic. See
#' \code{\link{mmds.gof}} for more information.\cr}
#'
#' @author David L. Miller
#' @section Note:
#' \code{ds.mixture} objects can be passed to \code{\link{step.ds.mixture}} to
#' select number of mixture components based on AIC score.
NULL
#' Goodness of fit for mixture model detection functions
#'
#' Goodness of fit testing for detection for mixture model detection functions.
#'
#' @name mmds.gof
#' @section Details:
#' Two goodness of fit tests are provided: the Cramer-von Mises and the
#' Kolmogorov-Smirnov. Both are implemented as in Buckland et al. (2004).
#'
#' Print methods are provided, so accessing the \code{ks} and \code{cvm}
#' elements of a \code{\link{ds.mixture}} object will give suitable summaries.
#'
#' David L. Miller
NULL
#' Parameters in \code{mmds}
#'
#' The internal parametrisation used in \code{mmds} is not directly
#' interpretable. This man page aims to explain how to interpret the parameters
#' and transform them into useful information.
#'
#' @name mmds.pars
#' @section Details:
#' Parametrisation works differently for the scale parameters of the
#' half-normals and for the mixture proportions.
#'
#' The scale parameters of the half-normals (or their constituent parameters in
#' the case of a covariate model) are given on the log scale.
#'
#' The mixture proportions are transformed to a parametrisation that allows
#' values to lie over all of the real line (see Miller and Thomas for details).
#'
#' The parameter vector is made up of the scale parameters followed by the
#' mixture parameters. In the non-covariate case the former is the length of
#' the number of mixtures (\code{mix.terms}) and the latter is of length
#' \code{mix.terms}-1. When the model has covariates the scale paramters are
#' given as \code{mix.terms} intercepts followed by the covariate parameters.
#'
#' The function \code{\link{getpars}} transforms the parameters (\code{$pars}
#' element) in a \code{\link{ds.mixture}} object to a named list.
#'
#' Calling \code{\link{summary.ds.mixture}} will show the mixture proportions.
#'
#' The parameter \code{initialvalues} supplied to \code{\link{fitmix}}.
#'
#' @author David L. Miller
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