通过灵活的威布尔扩展分布建立正倾斜数据的分布模型

IF 0.8 4区数学 Q3 STATISTICS & PROBABILITY Australian & New Zealand Journal of Statistics Pub Date : 2024-08-11 DOI:10.1111/anzs.12423

Freddy Hernández-Barajas, Olga Usuga-Manco, Carmen Patino-Rodríguez, Fernando Marmolejo-Ramos

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引用次数: 0

摘要

摘要众所周知，事件发生前的时间通常呈倾斜分布。为了模拟这种情况，有人提出了一种称为双参数灵活威布尔扩展（FWE）的统计分布。本文通过使用位置、规模和形状的广义加性模型（GAMLSS）分布回归，将 FWE 分布用于数据集建模。GAMLSS 是唯一一种可以检查分类和数字预测因子对用于拟合因变量的分布的所有参数的影响的回归技术。为了更方便地通过 GAMLSS 使用 FWE 分布，我们提出了 RelDists R 软件包。模拟研究表明，即使存在影响分布的因素，通过 GAMLSS 建立 FWE 模型也能提供可靠的参数估计。

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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Distributional modelling of positively skewed data via the flexible Weibull extension distribution

The time until an event occurs is often known to have a skewed distribution. To model this, a statistical distribution called the two-parameter flexible Weibull extension (FWE) has been proposed. In this paper, the FWE distribution is used to model datasets through the use of generalised additive models for location, scale and shape (GAMLSS) distributional regression. GAMLSS is the only regression technique that can examine the effects of both categorical and numeric predictors on all the parameters of the distribution used to fit the dependent variable. To make it easier to use the FWE distribution through GAMLSS, the RelDists R package is proposed. A simulation study shows that FWE modelling through GAMLSS provides reliable parameter estimates even in the presence of factors that affect the distribution.

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来源期刊

Australian & New Zealand Journal of Statistics 数学-统计学与概率论

CiteScore

1.30

自引率

9.10%

发文量

审稿时长

>12 weeks

期刊介绍： The Australian & New Zealand Journal of Statistics is an international journal managed jointly by the Statistical Society of Australia and the New Zealand Statistical Association. Its purpose is to report significant and novel contributions in statistics, ranging across articles on statistical theory, methodology, applications and computing. The journal has a particular focus on statistical techniques that can be readily applied to real-world problems, and on application papers with an Australasian emphasis. Outstanding articles submitted to the journal may be selected as Discussion Papers, to be read at a meeting of either the Statistical Society of Australia or the New Zealand Statistical Association. The main body of the journal is divided into three sections. The Theory and Methods Section publishes papers containing original contributions to the theory and methodology of statistics, econometrics and probability, and seeks papers motivated by a real problem and which demonstrate the proposed theory or methodology in that situation. There is a strong preference for papers motivated by, and illustrated with, real data. The Applications Section publishes papers demonstrating applications of statistical techniques to problems faced by users of statistics in the sciences, government and industry. A particular focus is the application of newly developed statistical methodology to real data and the demonstration of better use of established statistical methodology in an area of application. It seeks to aid teachers of statistics by placing statistical methods in context. The Statistical Computing Section publishes papers containing new algorithms, code snippets, or software descriptions (for open source software only) which enhance the field through the application of computing. Preference is given to papers featuring publically available code and/or data, and to those motivated by statistical methods for practical problems.