Statistical Inference for the Parameter of Rayleigh Distribution Through Fuzzy Membership Function

S. Mustafa, Shumaila Naheed, Hina Basharat
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Abstract

There are number of inference techniques that can be used for the estimation of the unknown parameters which are based on precise crisp data, but there are many situations where we deal with imprecise and vague data. In this situation the classical mathematical tools cannot help us to estimate the parameters. This impreciseness can be covered by introducing fuzzy concepts. This study deals with the maximum likelihood estimation for the parameters of Rayleigh distribution using Newton Raphson algorithm. A real-life data set analysis is presented by considering set of luminous intensity of light emitting diodes and finding of this study illustrates that proposed inferential technique is useful to deal with fuzziness of data when statistical inference of Rayleigh distribution is carried out for imprecise or fuzzy data.
利用模糊隶属函数对瑞利分布参数进行统计推断
有许多基于精确清晰数据的推理技术可用于未知参数的估计,但我们处理不精确和模糊数据的情况很多。在这种情况下,经典的数学工具不能帮助我们估计参数。这种不精确性可以通过引入模糊概念来弥补。本文研究了用Newton Raphson算法对瑞利分布参数的极大似然估计。本文以一组发光二极管的发光强度为例,对实际数据集进行了分析,研究结果表明,在对不精确或模糊的数据进行瑞利分布的统计推理时,所提出的推理方法可以有效地处理数据的模糊性。
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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