Length-biased with-replacement sampling from an exponential finite population
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Puza, Borek
O'Neill, Terence
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Taylor & Francis Group
Abstract
In this article, we study a statistical model which features a finite population of exponentially distributed values and a length-biased, with-replacement sampling mechanism. This mechanism is such that units compete with one another for selection at each draw. It is shown how inference on a number of quantities can be performed using both frequentist and Bayesian strategies. A Monte Carlo study is used to assess the performance of the proposed point and interval estimators.
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Journal of Statistical Computation and Simulation
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2037-12-31
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