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Probability distributions defined on the unit interval are widely used in fields ranging from econometrics to reliability studies. Traditional models such as the beta and Kumaraswamy distributions are well-established due to their…

Methodology · Statistics 2026-03-04 Roberto Vila , Helton Saulo , Poliana Matos , Subhankar Dutta

A decision must often be made between heavy-tailed and Gaussian errors for a regression or a time series model, and the t-distribution is frequently used when it is assumed that the errors are heavy-tailed distributed. The performance of…

Computation · Statistics 2015-05-11 J. Martin van Zyl

We define a four-parameter extended Rayleigh distribution, and obtain several mathematical properties including a stochastic representation. We construct a regression from the new distribution. The estimation is done by maximum likelihood.…

This paper is devoted to study a new three- parameters model called the Exponential Flexible Weibull extension (EFWE) distribution which exhibits bathtub-shaped hazard rate. Some of it's statistical properties are obtained including…

Statistics Theory · Mathematics 2016-05-27 Beih S. El-Desouky , Abdelfattah Mustafa , Shamsan AL-Garash

Finite mixture of skew distributions have emerged as an effective tool in modelling heterogeneous data with asymmetric features. With various proposals appearing rapidly in the recent years, which are similar but not identical, the…

Methodology · Statistics 2013-05-29 Sharon X. Lee , Geoffrey J. McLachlan

Large, non-Gaussian spatial datasets pose a considerable modeling challenge as the dependence structure implied by the model needs to be captured at different scales, while retaining feasible inference. Skew-normal and skew-t distributions…

Methodology · Statistics 2017-12-07 Felipe Tagle , Stefano Castruccio , Marc G. Genton

We develop an unsupervised mixture model for non-negative, skewed and heavy-tailed data, such as losses in actuarial and risk management applications. The mixture has a lognormal component, which is usually appropriate for the body of the…

Methodology · Statistics 2025-05-29 Marco Bee , Flavio Santi

The concepts of probability, statistics and stochastic theory are being successfully used in structural engineering. Markov Chain modelling is a simple stochastic process model that has found its application in both describing stochastic…

Applications · Statistics 2007-08-14 K. Balaji Rao

This work proposes a statistical model for crossover trials with multiple skewed responses measured in each period. A 3 $\times$ 3 crossover trial data where different drug doses were administered to subjects with a history of seasonal…

Methodology · Statistics 2026-04-09 Savita Pareek , Kalyan Das , Siuli Mukhopadhyay

Catastrophic loss data are known to be heavy-tailed. Practitioners then need models that are able to capture both tail and modal parts of claim data. To this purpose, a new parametric family of loss distributions is proposed as a gamma…

Applications · Statistics 2019-12-23 Zhengxiao Li , Jan Beirlant , Shengwang Meng

In the study of heavy tail data, several models have been introduced. If the interest is in the tail of the distribution, block maxima or excess over thresholds are the typical approaches, wasting relevant information in the bulk of the…

Methodology · Statistics 2026-02-10 Luis E. Nieto-Barajas

Traditionally power distribution networks are either not observable or only partially observable. This complicates development and implementation of new smart grid technologies, such as those related to demand response, outage detection and…

Optimization and Control · Mathematics 2015-03-02 Deepjyoti Deka , Scott Backhaus , Michael Chertkov

In this paper, a new two-parameter model called generalized Ramos-Louzada (GRL) distribution is proposed. The new model provides more flexibility in modeling data with increasing, decreasing, j shaped and reversed-J shaped hazard rate…

Applications · Statistics 2019-12-19 Hazem Al-Mofleh , Ahmed Z. Afify

In this paper, a generalization for the Birnbaum Saunders distribution, which has been applied to the modelling of fatigue failure times and reliability studies, is considered. The maximum likelihood estimators and statistical inference for…

Statistics Theory · Mathematics 2021-09-06 Beenu Thomas , Chacko V M

The modeling and analysis of lifetimes is an important aspect of statistical work in a wide variety of scientific and technological fields. For the first time, the called Kumaraswamy Pareto distribution is introduced and studied. The new…

Methodology · Statistics 2012-12-05 Marcelo B. Pereira , Rodrigo B. Silva , Luz M. Zea , Gauss M. Cordeiro

A continuous approximation for the results of [1] is obtained. In this approximation the energy distribution is represented in the form of the product of the Gibbs factor and superstatistics factor. The mutual weights of the factors are…

Chemical Physics · Physics 2007-05-23 V. V. Ryazanov

This paper presents a new methodology for generating continuous statistical distributions, integrating the exponentiated odds ratio within the framework of survival analysis. This new method enhances the flexibility and adaptability of…

Statistics Theory · Mathematics 2024-02-28 Xinyu Chen , Yuanqi Xie , Achraf Cohen , Shusen Pu

The aim of this article is to determine a new six-parameter Beta Weibull distribution and its various associated functions, namely the cumulative distribution, survival, probability density and hazard functions. Next, we determine the…

Statistics Theory · Mathematics 2026-04-07 Didier Alain Njamen Njomen , Fidel Djongreba Ndikwa

The normal distribution and its perturbation has left an immense mark on the statistical literature. Hence, several generalized forms were developed to model different skewness, kurtosis, and body shapes. However, it is not easy to…

Methodology · Statistics 2019-12-10 Matthias Wagener , Mohammad Arashi

In natural phenomena, data distributions often deviate from normality. One can think of cataclysms as a self-explanatory example: events that occur almost never, and at the same time are many standard deviations away from the common…

Machine Learning · Computer Science 2022-12-16 Nuno Costa , Nuno Moniz
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