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We study the problem of modeling univariate distributions via their quantile functions. We introduce a flexible family of distributions whose quantile function is a linear combination of basis quantiles. Because the model is linear in its…

Methodology · Statistics 2026-02-05 Cheng Peng , Yizhou Li , Stan Uryasev

Parametric quantile regression is illustrated for the one parameter new unit Rayleigh distribution called Median Based Unit Rayleigh distribution (MBUR) distribution. The estimation process using re-parameterized maximum likelihood function…

Methodology · Statistics 2025-10-14 Iman Mohamed Attia

In this paper, we consider survival analysis with right-censored data which is a common situation in predictive maintenance and health field. We propose a model based on the estimation of two-parameter Weibull distribution conditionally to…

Methodology · Statistics 2020-02-24 Achraf Bennis , Sandrine Mouysset , Mathieu Serrurier

In this paper, we introduce a new three-parameter distribution based on the combination of re-parametrization of the so-called EGNB2 and transmuted exponential distributions. This combination aims to modify the transmuted exponential…

Statistics Theory · Mathematics 2020-02-11 Christophe Chesneau , Hassan S. Bakouch , Muhammad Nauman Khan

In this paper, we proposed a new lifetime distribution namely generalized weighted Lindley (GLW) distribution. The GLW distribution is a useful generalization of the weighted Lindley distribution, which accommodates increasing, decreasing,…

Statistics Theory · Mathematics 2016-07-20 P. L. Ramos , F. Louzada

In the regression problem, L1 and L2 are the most commonly used loss functions, which produce mean predictions with different biases. However, the predictions are neither robust nor adequate enough since they only capture a few conditional…

Machine Learning · Computer Science 2019-11-14 Faen Zhang , Xinyu Fan , Hui Xu , Pengcheng Zhou , Yujian He , Junlong Liu

A discrete version of the Gumbel (Type I) extreme value distribution has been derived by using the general approach of discretization of a continuous distribution. Important distributional and reliability properties have been explored. It…

Statistics Theory · Mathematics 2014-10-29 Subrata Chakraborty , Dhrubajyoti Chakravarty

In this article, bootstrap and Shewhart type process control monitoring schemes are proposed for the quantiles of generalized Weibull distribution under hybrid censoring. Monitoring schemes for the quantiles of Weibull, generalized…

Methodology · Statistics 2023-09-22 Amarjit Kundu , Shovan Chowdhury , Bidhan Modok

We demonstrate that certain astrophysical distributions can be modelled with the truncated Weibull distribution, which can lead to some insights: in particular, we report the average value, the $r$th moment, the variance, the median, the…

Instrumentation and Methods for Astrophysics · Physics 2021-03-31 Lorenzo Zaninetti

The Sustainable Development Goals (SDGs) of the United Nations provide a blueprint of a better future by 'leaving no one behind', and, to achieve the SDGs by 2030, poor countries require immense volumes of development aid. In this paper, we…

Machine Learning · Statistics 2024-06-18 Milan Kuzmanovic , Dennis Frauen , Tobias Hatt , Stefan Feuerriegel

Characterizing the wind speed distribution properly is essential for the satisfactory production of potential energy in wind farms, being the mixture models usually employed in the description of such data. However, some mixture models…

In regression tasks, aleatoric uncertainty is commonly addressed by considering a parametric distribution of the output variable, which is based on strong assumptions such as symmetry, unimodality or by supposing a restricted shape. These…

Machine Learning · Computer Science 2019-10-30 Axel Brando , Jose A. Rodríguez-Serrano , Jordi Vitrià , Alberto Rubio

The prediction of crop yields internationally is a crucial objective in agricultural research. Thus, this study implements 6 regression models (Linear, Tree, Gradient Descent, Gradient Boosting, K Nearest Neighbors, and Random Forest) to…

The post-2020 global biodiversity framework needs ambitious, research-based targets. Estimating the accelerated extinction risk due to climate change is critical. The International Union for Conservation of Nature (IUCN) measures the…

Populations and Evolution · Quantitative Biology 2024-01-12 Joaquim Estopinan , Pierre Bonnet , Maximilien Servajean , François Munoz , Alexis Joly

This paper presents a unified and novel estimation framework for the Weibull, Gamma, and Log-normal distributions based on arbitrary-order moment pairs. Traditional estimation techniques, such as Maximum Likelihood Estimation (MLE) and the…

Methodology · Statistics 2025-05-06 Kang Liu

Accurate prediction models for individual-level endpoints and time-to-endpoints are crucial in clinical practice. In this study, we propose a novel approach, GRU-D-Weibull, which combines gated recurrent units with decay (GRU-D) to model…

Machine Learning · Computer Science 2023-08-16 Xiaoyang Ruan , Liwei Wang , Charat Thongprayoon , Wisit Cheungpasitporn , Hongfang Liu

The Weibull distribution is a very applicable model for the lifetime data. In this paper, we have investigated inference on the parameters of Weibull distribution based on record values. We first propose a simple and exact test and a…

Statistics Theory · Mathematics 2015-01-12 Ali Akbar Jafari , Hojatollah Zakerzadeh

This paper introduces a new four-parameter lifetime model called the Weibull Birnbaum-Saunders distribution. This new distribution represents a more flexible model for the lifetime data. Its failure rate function can be increasing,…

Applications · Statistics 2016-04-19 Lazhar Benkhelifa

In transportation, Weigh-in motion (WIM) stations, Electronic Toll Collection (ETC) systems, Closed-circuit Television (CCTV) are widely deployed to collect data at different locations. Vehicle re-identification, by matching the same…

Applications · Statistics 2024-11-06 Diyi Liu , Yangsong Gu , Lee D. Han

One of the key challenges in predictive maintenance is to predict the impending downtime of an equipment with a reasonable prediction horizon so that countermeasures can be put in place. Classically, this problem has been posed in two…

Machine Learning · Computer Science 2018-12-19 Karan Aggarwal , Onur Atan , Ahmed Farahat , Chi Zhang , Kosta Ristovski , Chetan Gupta