Comparing Some Iterative Methods of Parameter Estimation for Progressively Censored Lomax Data
Keywords:
Lomax distribution, progressive censoring, maximum likelihood, symmetric and asymmetric loss functionsAbstract
Based on Progressively Type-II censored samples, the maximum likelihood estimator, the uniformly minimum variance unbiased estimator (UMV U), and the Bayes estimators for the shape parameter and the hazard function of the Lomax model are derived. The Bayesian estimators are obtained based on symmetric (squared error, absolute difference, and logarithmic loss functions) and
asymmetric (LINEX, General Entropy, and Logarithmic) loss functions. A real data example consists of data from Iowa 65+ Rural Health Study (RHS) is used to illustrate the proposed methods
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