文章基本信息

标题：Kumaraswamy regression modeling for Bounded Outcome Scores
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作者：Soudabeh Hamedi-Shahraki ; Aliakbar Rasekhi ; Mir Saeed Yekaninejad 等
期刊名称：Pakistan Journal of Statistics and Operation Research
印刷版ISSN：2220-5810
出版年度：2021
卷号：17
期号：1
页码：79-88
DOI：10.18187/pjsor.v17i1.3411
语种：English
出版社：College of Statistical and Actuarial Sciences
摘要：In this paper, we use a regression model for modeling bounded outcome scores (BOS), where the outcome is Kumaraswamy distributed. Similar to the Beta distribution, this distribution can take a variety of shapes while being computationally easier to use. Thus, it is deemed as a suitable alternative distribution to the Beta in modeling bounded random processes. In the proposed model, the median of a bounded response is modeled by the linear predictors which is defined through regression parameters and explanatory variables. We obtained the maximum likelihood estimates (MLE) of the parameters, provided closed-form expressions for the score functions and Fisher information matrix, and presented some diagnostic measures. We conducted Monte Carlo simulations to investigate the finite-sample performance of the MLEs of the parameters. Finally, two practical applications of this model to the real data sets are presented and discussed.
关键词：Bounded outcome score; Kumaraswamy distribution; Beta regression; maximum likelihood estimation; diagnostic analysis