ExpectationM_MSARmdl function

Markov-switching autoregressive log-likelihood function

Markov-switching autoregressive log-likelihood function

This function computes the log-likelihood for a markov-switching autoregressive model and uses the Hamilton smoother to obtain smoothed probabilities of each state. This is also the expectation step in the Expectation Maximization algorithm for a Markov-switching autoregressive model.

ExpectationM_MSARmdl(theta, mdl, k)

Arguments

  • theta: Vector of model parameters.
  • mdl: List with model attributes.
  • k: Integer determining the number of regimes.

Returns

List which includes log-likelihood and smoothed probabilities of each regime.

  • Maintainer: Gabriel Rodriguez Rondon
  • License: GPL (>= 2)
  • Last published: 2025-02-24