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<p>In this article, we propose a new length-biased weighted form of Inverse Rayleigh distribution named as New Length-Biased Weighted Inverse Rayleigh distribution (NLBWIR). Statistical properties of the proposed distribution, like behaviour of the distribution, Reliability function, Hazard function, Reversed Hazard function etc. are discussed. The parameters of the proposed model are estimated by maximum likelihood estimation method and maximum product of spacing method. A Simulation study is carried out to investigate the performance of the estimators obtained by two different methods of estimation. A stochastic comparison is also discussed and fitted the distribution to real data sets to justify the use of new length-biased weighted inverse Rayleigh distribution.</p>

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New length-biased weighted inverse Rayleigh distribution, its properties, applications and stochastic comparison

  • 期刊论文

  • 发表日期：

    2025年8月27日

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  • Surinder Kumar,
  • Shivendra Pratap Singh,
  • Naresh Chandra Kabdwal

摘要

In this article, we propose a new length-biased weighted form of Inverse Rayleigh distribution named as New Length-Biased Weighted Inverse Rayleigh distribution (NLBWIR). Statistical properties of the proposed distribution, like behaviour of the distribution, Reliability function, Hazard function, Reversed Hazard function etc. are discussed. The parameters of the proposed model are estimated by maximum likelihood estimation method and maximum product of spacing method. A Simulation study is carried out to investigate the performance of the estimators obtained by two different methods of estimation. A stochastic comparison is also discussed and fitted the distribution to real data sets to justify the use of new length-biased weighted inverse Rayleigh distribution.