mvms_dmat function

HMM Observation Probability matrix functions

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.

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

Returns

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

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.

Author(s)

Jeff Laake