A fitted Mixture Model Detection Function Object

Description

The fitted mixture model detection function object returned by fitmix. Knowledge of most of this is not useful. Use link{summary.ds.mixture} for result summaries.

Details

A ds.mixture object has the following elements:

distance Vector of distances used in the analysis.
likelihood Value of the log-likelihood at the maxima.
pars Parmeter estimates. See mmds.pars for more information.
mix.terms Number of mixture terms fit.
width Truncation distance used.
z List containing the matrix of covariates used. Output from model.matrix.
zdim Number of columns of z. See mmds.pars for more information.
hessian Hessian matrix at the maxima.
pt Logical indicating whether the data were from a point transect survey.
data Data frame after truncation.
ftype Type of detection function.
ctrl.options Options passed to optim.
showit Debug level.
opt.method Optimisation method used.
usegrad Were analytic gradients used?
model.formula Model formula.
mu Per-observation effective trip width/effective area of detection.
pa.vec Vector of per-observation detectabilities.
N Estimate of N in the covered area (Horvitz-Thompson).
pa Average detectability.
pars.se Standard errors of the parameters.
N.se Standard error of the Horvitz-Thompson estimate of the abundance.
pa.se Standard error of the average detectability.
aic AIC of the fitted model.
cvm Cramer-von Mises GoF test results. List containing: p, the p-value and W, the test statistic.
ks Kolmogorov-Smirnov test results. List containing: p, the p-value and Dn, the test statistic. See mmds.gof for more information.

Note

ds.mixture objects can be passed to step.ds.mixture to select number of mixture components based on AIC score.

Author(s)

David L. Miller