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

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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Abstract

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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通过灵活的威布尔扩展分布建立正倾斜数据的分布模型
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。
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