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

Summary 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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Publication Details

Journal
Australian & New Zealand Journal of Statistics
Published
2024-08-11
DOI
https://doi.org/10.1111/anzs.12423
Citations
1
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
Field-Weighted Citation Impact
0.71
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article

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

Freddy Hernández Barajas, Olga C. Úsuga-Manco, Fernando Marmolejo‐Ramos, Carmen Elena Patiño Rodríguez
1 citations
Australian & New Zealand Journal of Statistics
Statistical Distribution Estimation and Applications
0.71
article

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

Freddy Hernández Barajas, Olga C. Úsuga-Manco, Fernando Marmolejo‐Ramos, Carmen Elena Patiño Rodríguez
article en
1 citations

Abstract

Summary 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.

Australian & New Zealand Journal of StatisticsVol. 66(3)
University of South Australia (AU), Universidad de Antioquia (CO), Universidad Nacional de Colombia (CO)
Openalex Percentile: Top 27%
Statistical Distribution Estimation and Applications
0.71
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