R_HMMLikelihood function

Hidden Markov Model Functions

R implementation of HMMs described in processed report except function HMMLikelihood renamed to R_HMMLikelihood and changed to compute values for all capture histories and return lnl, alpha, phi, v, dmat, and gamma values. loglikelihood is called with a fitted hmm model and then computes the gamma,dmat and delta matrices and calls R_HMMLikelihood function. These are not used by the fitting code.

R_HMMLikelihood(x,first,m,T,dmat,gamma,delta)
       loglikelihood(object,ddl=NULL)

Arguments

• x: single observed sequence (capture history)
• first: occasion to initiate likelihood calculation for sequence
• m: number of states
• T: number of occasions; sequence length
• dmat: observation probability matrices
• gamma: transition matrices
• delta: initial distribution
• object: fitted hmm model
• ddl: design data list; will be computed if NULL

Returns

both return log-likelihood, alpha, v and phi arrays

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. See page 45.

Author(s)

Jeff Laake