Power logit regression for modeling bounded data

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2022-02-03 DOI:10.1177/1471082x221140157

Francisco F. Queiroz, S. Ferrari

引用次数: 0

Abstract

The main purpose of this article is to introduce a new class of regression models for bounded continuous data, commonly encountered in applied research. The models, named the power logit regression models, assume that the response variable follows a distribution in a wide, flexible class of distributions with three parameters, namely, the median, a dispersion parameter and a skewness parameter. The article offers a comprehensive set of tools for likelihood inference and diagnostic analysis, and introduces the new R package PLreg. Applications with real and simulated data show the merits of the proposed models, the statistical tools, and the computational package.

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建模有界数据的幂logit回归

本文的主要目的是介绍一类应用研究中常见的有界连续数据的新回归模型。这些模型被称为幂logit回归模型，假设响应变量遵循一类广泛、灵活的分布，具有三个参数，即中位数、离散度参数和偏度参数。本文提供了一套用于似然推理和诊断分析的全面工具，并介绍了新的R包PLreg。实际和模拟数据的应用表明了所提出的模型、统计工具和计算包的优点。

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

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.