Hidden Markov Models, Markov Chains, Markov Switching, Markov Auto Regression, Maximum Likelihood.
constant mean y_bar of all observations i.e.: y_bar=(y_1+y2+…+y_n)/n, we get a mean model: y_t = y_bar. A more interesting model might rely upon a set of ‘m+1’ number of regression coefficients β_cap=[β_cap_0, β_cap_1, β_cap_2, …, β_cap_m] that ‘link’ the dependent variable y to a matrix of