create.param.arrays

a list of character vectors of model names 
with the elements named by species code

model.names

a list of all the ddf models named in model.names.

ddf.models

the number of bootstrap iterations to be completed.

the name of the model selection criteria.

criteria

Creates a list of arrays. These are used to store the parameter estimates,
a record of convergence, selection criteria values and which model was
selected in the case of model uncertainty.

utility

Performs distance sampling analyses on a number of species
at once and can account for unidentified sightings, model uncertainty
and covariate uncertainty. Unidentified sightings refer to sightings
which cannot be allocated to a single species but may instead be
allocated to a group of species. The abundance of each unidentified
group is estimated and then prorated to the species estimates. Model
uncertainty should be incorporated when multiple models give equally
good fit to the data but lead to large differences in estimated
density / abundance. Covariate uncertainty should be incorporated
when covariates cannot be measured accurately, for example this is
often the case for group size in marine mammal surveys. Variance
estimation for these methods is via a non parametric bootstrap.
The methods implemented are described in Gerodette T. and Forcada
J. (2005) <doi:10.3354/meps291001> Non-recovery of two spotted and
spinner dolphin populations in the eastern tropical Pacific Ocean.

create.param.arrays: Creates a list of arrays for storing the ddf results

Description

Usage

Arguments

Value