Efficient Estimation of the Density and Cumulative Distribution Function of the Generalized Rayleigh Distribution

مجتبی علیزاده, فاضل باقری جمالالدین کلایی, محسن خالقی مقدم
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引用次数: 10

Abstract

The uniformly minimum variance unbiased (UMVU), maximum likelihood, percentile (PC), least squares (LS) and weighted least squares (WLS) estimators of the probability density function (pdf) and cumulative distribution function are derived for the generalized Rayleigh distribution. This model can be used quite effectively in modelling strength data and also modelling general lifetime data. It has been shown that MLE is better than UMVUE and UMVUE is better than the others. An application to waiting times (min) of 100 bank customers.
广义瑞利分布的密度和累积分布函数的有效估计
对广义瑞利分布导出了概率密度函数(pdf)和累积分布函数的均匀最小方差无偏估计(UMVU)、最大似然估计、百分位数估计(PC)、最小二乘估计(LS)和加权最小二乘估计(WLS)。该模型可有效地用于强度数据的建模,也可用于一般寿命数据的建模。结果表明,MLE算法优于UMVUE算法,UMVUE算法优于其他算法。一个应用程序的等待时间(分钟)为100个银行客户。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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