logisticdupbyx

Treats logistic for duplicates as a function of covariate z; for a given z
it computes the 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

logisticdupbyx function

<dl><dt>distance</dt>
<dd>vector of distance values</dd>
<dt>x1</dt>
<dd>covariate data for fct 1</dd>
<dt>x2</dt>
<dd>covariate data for fct 2</dd>
<dt>models</dt>
<dd>model list</dd>
<dt>beta</dt>
<dd>logistic parameters</dd>
<dt>point</dt>
<dd><code>TRUE</code> for point transect data</dd></dl>

Arguments

Author

Logistic for duplicates as a function of covariates — logisticdupbyx

<dl>

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


<dt>x1</dt>
<dd>covariate data for fct 1</dd>


<dt>x2</dt>
<dd>covariate data for fct 2</dd>


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


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


<dt>point</dt>
<dd><code>TRUE</code> for point transect data</dd>

</dl>

logisticdupbyx: Logistic for duplicates as a function of covariates

Description

Usage

Value

Arguments

Author