A Proof of Strong Consistency of Maximum Likelihood Estimator for Independent Non-Identically Distributed Data
Abstract
We give a general proof of the strong consistency of the Maximum Likelihood Estimator for the case of independent non-identically distributed (i.n.i.d) data, assuming that the density functions of the random variables follow a particular set of assumptions. Our proof is based on the works of Wald~wald1949note, Goel~goel1974note, and Ferguson~ferguson2017course. We use this result to prove the strong consistency of a Maximum Likelihood Estimator for Orbit Determination.
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