create.obs.table

dataframe of observation records with fields object,
Region.Label, and Sample.Label which give links to sample.table,
region.table and the data records used in <code>model</code>

obs.table

dataframe containing the observations

ddf.data

variable name supplied as a character

subset.variable

character value on which to subset the data

subset.value

Subsets the obs.table dataframe supplied to only contain the observations of
interest.

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.obs.table: Creates a subsetted observation table

Description

Usage

Arguments

Value