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mmds (version 1.1)

ds.mixture: 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.

Arguments

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.