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Parameter estimation in geometric process with Weibull distribution
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DOI：10.1016/j.amc.2010.08.003.png)
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摘要
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We consider geometric process (GP) when the distribution of the first occurrence time of an event is assumed to be Weibull. Explicit estimators of the parameters in GP are derived by using the method of modified maximum likelihood (MML) proposed by Tiku [24]. Asymptotic distributions and consistency properties of these estimators are obtained. We show that our estimators are more efficient than the widely used modified moment (MM) estimators via Monte Carlo simulation study. Further, two real life examples are given at the end of the paper. (C) 2010 Elsevier Inc. All rights reserved.
Keyword:
Taylor series
Geometric process
Modified likelihood
Asymptotic normality
Consistency
Efficiency
Monte Carlo simulation
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被引数:
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