On 2-Parameter Estimation of Lomax Distribution (original) (raw)
2019, Journal of Physics: Conference Series
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Applied Mathematical Sciences, 2018
In this study, we consider the parameter estimation of a three-parameter continuous distribution, namely, power Lomax distribution proposed by , when the lifetime experiments are under Type-II Progressively Hybrid censoring scheme. Expectation-Maximization algorithm was used to compute the Maximum Likelihood Estimators. Simulation was used to evaluate the performance of the maximum likelihood estimates in terms of average biases and root mean square errors.
On the Bias of the Maximum Likelihood Estimator for the Two-Parameter Lomax Distribution
Communications in Statistics - Theory and Methods, 2013
The Lomax (Pareto II) distribution has found wide application in a variety of fields. We analyze the second-order bias of the maximum likelihood estimators of its parameters for finite sample sizes, and show that this bias is positive. We derive an analytic bias correction which reduces the percentage bias of these estimators by one or two orders of magnitude, while simultaneously reducing relative mean squared error. Our simulations show that this analytic bias correction outperforms a correction based on the parametric bootstrap. Three examples with actual data illustrate the application of our methods.
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