Inference : a note on estimation in the four-parameter beta distribution

Julian Z. Wang

    Research output: Contribution to journalArticle

    Abstract

    The four-parameter beta distribution is non regular at both lower and upper endpoints in maximum likelihood estimation (MLE). The use of MLE is restricted only in a range of values of the shape parameters. The object of this article is to explore a way of estimating the parameters by placing priors to counteract the shortfalls inherent in the conventional likelihood. The priors are in a general form and therefore the proposed method is generally applicable. The estimators based on the modified likelihood are consistent with optimal rates of convergence.
    Original languageEnglish
    Number of pages7
    JournalCommunication in Statistics : Simulation and Computation
    Publication statusPublished - 2005

    Keywords

    • distribution (probability theory)
    • probabilities
    • parameter estimation
    • estimation theory
    • mathematical statistics
    • Bayesian statistical decision theory

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