mvms_dmat: HMM Observation Probability matrix functions

Description Usage Arguments Value Author(s) References

View source: R/Observation_functions.r

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

1
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 Dec. 9, 2019, 9:06 a.m.