New results and regression model for the exponentiated odd log-logistic family with applications

Q4 Mathematics

Model Assisted Statistics and Applications Pub Date : 2024-03-14 DOI:10.3233/mas-231450

Gabriela M. Rodrigues, Roberto Vila, E. M. Ortega, G. Cordeiro, Victor Serra

引用次数: 0

Abstract

We obtain new mathematical properties of the exponentiated odd log-logistic family of distributions, and of its special case named the exponentiated odd log-logistic Weibull, and its log transformed. A new location and scale regression model is constructed, and some simulations are carried out to verify the behavior of the maximum likelihood estimators, and of the modified deviance-based residuals. The methodology is applied to the Japanese-Brazilian emigration data.

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指数奇数对数逻辑族的新结果和回归模型及其应用

我们获得了指数化奇数对数-对数分布族的新数学特性，以及其特殊情况（名为指数化奇数对数-对数 Weibull）及其对数变换的新数学特性。构建了一个新的位置和规模回归模型，并进行了一些模拟，以验证最大似然估计值和修正的基于偏差的残差的行为。该方法适用于日本-巴西移民数据。

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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来源期刊

Model Assisted Statistics and Applications Mathematics-Applied Mathematics

CiteScore

1.00

自引率

0.00%

发文量

期刊介绍： Model Assisted Statistics and Applications is a peer reviewed international journal. Model Assisted Statistics means an improvement of inference and analysis by use of correlated information, or an underlying theoretical or design model. This might be the design, adjustment, estimation, or analytical phase of statistical project. This information may be survey generated or coming from an independent source. Original papers in the field of sampling theory, econometrics, time-series, design of experiments, and multivariate analysis will be preferred. Papers of both applied and theoretical topics are acceptable.