Estimating the width of a uniform distribution under symmetric measurement errors
In this paper we consider the problem of estimating the support of a uniform distribution under symmetric additive errors. The maximum likelihood (ML) estimator is of our primary interest, but we also analyze the method of moments (MM) estimator, when it exists. Under some regularity conditions, the ML estimator is consistent and asymptotically efficient. Errors with Student’s t-distribution are shown to be a good choice for robustness issues.
KeywordsUniform distribution Additive error Maximum likelihood estimator Robustness
This work was supported by the Croatian Science Foundation through research grants IP-2016-06-6545.
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