Hidden Markov model likelihoods and their derivatives behave like i.i.d. ones
How to combine fast heuristic Markov chain Monte Carlo with slow exact sampling.
Hurwicz's estimator of the autoregressive model with non-normal innovations
Using the Bahadur representation of a sample quantile for m-dependent and strong mixing random variables, we establish the asymptotic distribution of the Hurwicz estimator for the coefficient of autoregression in a linear process with innovations belonging to the domain of attraction of an α-stable law (1 < α < 2). The present paper extends Hurwicz's result to the autoregressive model.