Simulated Maximum Likelihood, Pseudo‐Maximum Likelihood, and Nonlinear Least Squares Methods
Simulated Maximum Likelihood, Pseudo‐Maximum Likelihood, and Nonlinear Least Squares Methods
The simulated analogues to Maximum Likelihood, Pseudo‐Maximum Likelihood, and Non‐Linear Least Squares Methods are presented. Their asymptotic properties and bias corrections are given under various assumptions. Several kinds of simulators are explored and, among them, simulations based on conditioning, on EM algorithm, or on importance sampling. The Metropolis Hastings algorithm is also considered.
Keywords: conditioning, EM algorithm, importance sampling, least squares, likelihood, pseudo‐likelihood
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