mvms_dmat

cjs_dmat

ms_dmat

ums_dmat

ums2_dmat

Functions that compute the probability matrix of the observations given the state for various models. 
Currently only CJS, MS models and MS models with state uncertainty are included.

Functions for fitting various models to capture-recapture data
including mixed-effects Cormack-Jolly-Seber(CJS) and multistate models and
the multi-variate state model structure for survival
estimation and POPAN structured Jolly-Seber models for abundance estimation.
There are also Hidden Markov model (HMM) implementations of CJS and multistate
models with and without state uncertainty and a simulation capability for HMM
models.

Jeff Laake

marked

Mark-Recapture Analysis for Survival and Abundance Estimation

mvms_dmat function

<dl><dt>pars</dt>
<dd>list of real parameter matrices (id by occasion) for each type of parameter</dd>
<dt>m</dt>
<dd>number of states</dd>
<dt>F</dt>
<dd>initial occasion vector</dd>
<dt>T</dt>
<dd>number of occasions</dd>
<dt>sup</dt>
<dd>list of supplemental information that may be needed by the function but only needs to be computed once</dd></dl>

Arguments

Author

HMM Observation Probability matrix functions — mvms_dmat

<dl>

<dt>pars</dt>
<dd>list of real parameter matrices (id by occasion) for each type of parameter</dd>


<dt>m</dt>
<dd>number of states</dd>


<dt>F</dt>
<dd>initial occasion vector</dd>


<dt>T</dt>
<dd>number of occasions</dd>


<dt>sup</dt>
<dd>list of supplemental information that may be needed by the function but only needs to be computed once</dd>

</dl>

mvms_dmat: HMM Observation Probability matrix functions

Description

Usage

Value

Arguments

Author

References