A Note on the Estimation of Parameters in a Bernoulli Model with Dependence

Abstract

A generalization of a Bernoulli process which incorporates a dependence structure was given by Klotz (1972, 1973), in which he considered $X_1, X_2, \cdots, X_n$ as a stationary two-state Markov chain with state space $\{0, 1\}$. The parameters of the process are $p = P(X_i = 1)$ and $\lambda$, which measures the degree of persistence in the chain. Klotz was unable to solve the equations arising from the full likelihood for the M.L.E.'s of $p$ and $\lambda$, so proposed and investigated an ad hoc procedure. Here explicit solutions are obtained for M.L.E.'s based on a modified likelihood function, where the modification consists of neglecting the first term of the full likelihood. In addition it is observed that Klotz's equations can in fact be solved explicitly.