logisticbyx

treats logistic as a function of covariates; for a given covariate
combination it computes function at with those covariate values at a
range of distances

Animal abundance estimation via conventional, multiple covariate
and mark-recapture distance sampling (CDS/MCDS/MRDS). Detection function
fitting is performed via maximum likelihood. Also included are diagnostics
and plotting for fitted detection functions. Abundance estimation is via a
Horvitz-Thompson-like estimator.

Laura Marshall

mrds

Mark-Recapture Distance Sampling

logisticbyx function

<dl><dt>distance</dt>
<dd>vector of distance values</dd>
<dt>x</dt>
<dd>covariate data</dd>
<dt>models</dt>
<dd>model list</dd>
<dt>beta</dt>
<dd>logistic parameters</dd>
<dt>point</dt>
<dd><code>TRUE</code> if a point transect model</dd></dl>

Arguments

Author

Logistic as a function of covariates — logisticbyx

<dl>

<dt>distance</dt>
<dd>vector of distance values</dd>


<dt>x</dt>
<dd>covariate data</dd>


<dt>models</dt>
<dd>model list</dd>


<dt>beta</dt>
<dd>logistic parameters</dd>


<dt>point</dt>
<dd><code>TRUE</code> if a point transect model</dd>

</dl>

logisticbyx: Logistic as a function of covariates

Description

Usage

Value

Arguments

Author