Forward Backward for MSAR models with non homogeneous transitions

Description

Computes the posterior (or smoothing) probabilities in an homogenenous HMM or MSAR model using the forwards backwards algo. 'filter_only' is an optional argument (default: 0). If 1, we do filtering, if 0, smoothing.

Usage

1
nhforwards_backwards(prior, transition, obslik, filter_only = 0)

Arguments

prior

rior probabilities PRIOR(I) = Pr(X(1) = I)

transition

non homogeneous transitions, one transition matrix for each time

obslik

emission probabilities OBSLIK(I,t) = Pr(Y(t) | X(t)=I)

filter_only

optional argument (default: 0). If TRUE, we do filtering, if FALSE, smoothing (default).

Value

..$gamma

smoothing probabilities P(X(t)|Y(0),...,Y(T))

..$xi

two steps smoothing probabilities P(X(t),X(t+1)|Y(0),...,Y(T))

..$loglik

log likelihood

..$M

Number of regimes

..$alpha

intermediate component in the FB algorithm (forward)

..$beta

intermediate component in the FB algorithm (backward)

Author(s)

Valerie Monbet, valerie.monbet@univ-rennes1.fr

See Also

fit.MSAR, Estep.MSAR

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