mvms_dmat: HMM Observation Probability matrix functions

In marked: Mark-Recapture Analysis for Survival and Abundance Estimation

HMM Observation Probability matrix functions

Description

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.

Usage

mvms_dmat(pars, m, F, T, sup)

Arguments

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

Value

4-d array of id and occasion-specific observation probability matrices - state-dependent distributions in Zucchini and MacDonald (2009)

Author(s)

Jeff Laake

References

Zucchini, W. and I.L. MacDonald. 2009. Hidden Markov Models for Time Series: An Introduction using R. Chapman and Hall, Boca Raton, FL. 275p.

marked documentation built on Oct. 19, 2023, 5:06 p.m.