probs

'probs' computes the state-dependent transition matrix

A system for batch-marking data analysis to estimate survival probabilities, capture probabilities, and enumerate the population abundance for both marked and unmarked individuals. The estimation of only marked individuals can be achieved through the batchMarkOptim() function. Similarly, the combined marked and unmarked can be achieved through the batchMarkUnmarkOptim() function. The algorithm was also implemented for the hidden Markov model encapsulated in batchMarkUnmarkOptim() to estimate the abundance of both marked and unmarked individuals in the population. The package is based on the paper: "Hidden Markov Models for Extended Batch Data" of Cowen et al. (2017) <doi:10.1111/biom.12701>.

Kehinde Olobatuyi

extBatchMarking

Extended Batch Marking Models

Simon Johns

Matthew RP Parker

Steve Hof

Laura LE Cowen

probs function

<dl><dt>r</dt>
<dd>The number of individuals from batch group "g" recaptured at recapture occasion t; g = 1,2,...,G, t = g+1,...,T. This must be an integer.</dd>
<dt>p</dt>
<dd>The probability of capture at occasion t. This must be a number between 0 and 1.</dd>
<dt>R</dt>
<dd>The number of individuals marked and released at sampling occasion g from batch group g; g = 1,2,...,G. This must be an integer.</dd></dl>

Arguments

State-dependent probability function — probs

<dl>

<dt>r</dt>
<dd>The number of individuals from batch group "g" recaptured at recapture occasion t; g = 1,2,...,G, t = g+1,...,T. This must be an integer.</dd>


<dt>p</dt>
<dd>The probability of capture at occasion t. This must be a number between 0 and 1.</dd>


<dt>R</dt>
<dd>The number of individuals marked and released at sampling occasion g from batch group g; g = 1,2,...,G. This must be an integer.</dd>

</dl>

probs: State-dependent probability function

Description

Usage

Value

Arguments