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

مجتبی علیزاده, فاضل باقری جمالالدین کلایی, محسن خالقی مقدم
{"title":"Efficient Estimation of the Density and Cumulative Distribution Function of the Generalized Rayleigh Distribution","authors":"مجتبی علیزاده, فاضل باقری جمالالدین کلایی, محسن خالقی مقدم","doi":"10.18869/ACADPUB.JSRI.10.1.1","DOIUrl":null,"url":null,"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.","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Statistical Research of Iran","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18869/ACADPUB.JSRI.10.1.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Goodness of Fit Tests based on Information Criterion for Randomly Censored Data Joint Modeling for Zero-Inflated Beta-Binomial and Normal Responses Best Linear Predictors in a Stationary Second Order Autoregressive process by means of near and far observations A Note on the Identifiability of General Bayesian Gaussian Models Simulated Synthetic Population Projection Using an Extended Model
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1