Estimation efficiency for Markov chain models
Christina M.L. Kelton, Marlene A. Smith · Journal of Statistical Computation and Simulation · 1987
In this paper, we evaluate and compare four algorithms for estimating stationary Markov chain models with embedded parameters from aggregate frequency data. By means of factorially designed Monte Carlo simulation experiments, we are able to determine the effects of model characteristics on algorithm accuracy and efficiency. We then present an application, using the best-performing algorithm, for U.S. population migration.