边际和条件双极值分布:一个随机回归模型的例子

IF 1.1 Q3 STATISTICS & PROBABILITY Pakistan Journal of Statistics and Operation Research Pub Date : 2023-09-03 DOI:10.18187/pjsor.v19i3.4143
S. Bharali, Jiten Hazarika, Kuldeep Goswami
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引用次数: 0

摘要

数学模型是一种描述现实生活场景的数学联系。为了安全有效地处理现实世界中的问题,需要进行模拟建模。在本文中,作者研究了随机回归模型场景,其中线性回归模型中的因变量和自变量服从分布。我们假设因变量和自变量都表现出I型极值分布。然后使用改进的最大似然(MML)估计方法导出估计量。据此,提出了一种假设检验技术。
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Marginal and Conditional both Extreme Value Distributions: A Case of Stochastic Regression Model
A mathematical model is a mathematical connection that describes some real-life scenario. To handle real-world problems securely and effectively, simulation modelling is required. In this article, the author investigates the stochastic regression model scenario in which the dependent and independent variables in a linear regression model follow a distribution. We assume that the dependent and independent variables both exhibit Type I Extreme Value Distribution. The estimators are then derived using the Modified Maximum Likelihood (MML) estimation method. In accordance with this, a hypothesis testing technique is developed.
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来源期刊
CiteScore
3.30
自引率
26.70%
发文量
53
期刊介绍: Pakistan Journal of Statistics and Operation Research. PJSOR is a peer-reviewed journal, published four times a year. PJSOR publishes refereed research articles and studies that describe the latest research and developments in the area of statistics, operation research and actuarial statistics.
期刊最新文献
An Improved Class of Estimators Of Population Mean of Sensitive Variable Using Optional Randomized Response Technique Modeling Tri-Model Data With a New Skew Logistic Distribution Marginal and Conditional both Extreme Value Distributions: A Case of Stochastic Regression Model Assessing the Effect of Non-response in Stratified Random Sampling using Enhanced Ratio Type Estimators under Double Sampling Strategy. A Novel Version of the Exponentiated Weibull Distribution: Copulas, Mathematical Properties and Statistical Modeling
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