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2022 | 23 | nr 3 | 27--41
Tytuł artykułu

A Comparison of the Method of Moments Estimator and Maximum Likelihood Estimator for the Success Probability in the Fibonacci-Type Probability Distribution

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Języki publikacji
A Fibonacci-type probability distribution provides the probabilistic models for establishing stopping rules associated with the number of consecutive successes. It can be interpreted as a generalized version of a geometric distribution. In this article, after revisiting the Fibonaccitype probability distribution to explore its definition, moments and properties, we proposed numerical methods to obtain two estimators of the success probability: the method of moments estimator (MME) and maximum likelihood estimator (MLE). The ways both of them performed were compared in terms of the mean squared error. A numerical study demonsrated that the MLE tends to outperform the MME for most of the parameter space with various sample sizes. (original abstract)
Opis fizyczny
  • University of Central Arkansas, USA
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