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We combine Tyler's robust estimator of the dispersion matrix with nonlinear shrinkage. This approach delivers a simple and fast estimator of the dispersion matrix in elliptical models that is robust against both heavy tails and high…

Methodology · Statistics 2023-05-31 Simon Hediger , Jeffrey Näf , Michael Wolf

A new class of distributions, called Generalized One Parameter Polynomial Exponential-G family of distributions is proposed for modelling lifetime data. An account of the structural and reliability properties of the new class is presented.…

Applications · Statistics 2020-06-11 Sudhansu S. Maiti , Sukanta Pramanik

The possibilities of the use of the coefficient of variation over a high threshold in tail modelling are discussed. The paper also considers multiple threshold tests for a generalized Pareto distribution, together with a threshold selection…

Statistics Theory · Mathematics 2015-10-02 J. Castillo , M. Padilla

The statistical parameters of five generalizations of the Lindley distribution, such as the average, variance and moments, are reviewed. A new double truncated Lindley distribution with three parameters is derived. The new distributions are…

Methodology · Statistics 2020-03-31 Lorenzo Zaninetti

We reexamine the classical linear regression model when the model is subject to two types of uncertainty: (i) some of covariates are either missing or completely inaccessible, and (ii) the variance of the measurement error is undetermined…

Statistics Theory · Mathematics 2021-08-05 Shuzhen Yang , Jianfeng Yao

Spread regression is an extension of linear regression that allows for the inclusion of a predictor that contains information about the variance. It can be used to take the information from a weather forecast ensemble and produce a…

Atmospheric and Oceanic Physics · Physics 2007-05-23 Stephen Jewson

Distributional regression aims to estimate the full conditional distribution of a target variable, given covariates. Popular methods include linear and tree-ensemble based quantile regression. We propose a neural network-based…

Methodology · Statistics 2024-07-08 Xinwei Shen , Nicolai Meinshausen

Variance parameter estimation in linear mixed models is a challenge for many classical nonlinear optimization algorithms due to the positive-definiteness constraint of the random effects covariance matrix. We take a completely novel view on…

Machine Learning · Statistics 2022-12-20 Lena Sembach , Jan Pablo Burgard , Volker H. Schulz

This letter proposes a regression model for nonnegative signals. The proposed regression estimates the mean of Rayleigh distributed signals by a structure which includes a set of regressors and a link function. For the proposed model, we…

Methodology · Statistics 2022-07-26 B. G. Palm , F. M. Bayer , R. J. Cintra , M. I. Pettersson , R. Machado

We introduce a new broad and exible class of multivariate elliptically symmetric distributions in- cluding the elliptically symmetric logistic and multivariate normal. Various probabilistic properties of the new distribution are studied,…

Probability · Mathematics 2018-10-26 Chuancun Yin , Xiuyan Sha

Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model…

Computation · Statistics 2014-06-24 Douglas Bates , Martin Mächler , Ben Bolker , Steve Walker

This paper introduces a new two-parameter distribution, referred to as the Shiha distribution, which provides a flexible model for skewed lifetime data with either heavy or light tails. The proposed distribution is applicable to various…

Methodology · Statistics 2026-02-04 F. A. Shiha

This article explores mathematical models for understanding the evolution of contagious diseases. The most widely known set of models are the compartmental ones, which are based on a set of differential equations. But these are not the only…

Populations and Evolution · Quantitative Biology 2021-12-07 C. O. S. Sorzano

Several probability distributions have been proposed in the literature, especially with the aim of obtaining models that are more flexible relative to the behaviors of the density and hazard rate functions. Recently, a new generalization of…

Computation · Statistics 2016-04-26 K. V. P. Barco , J. Mazucheli , V. Janeiro

The restricted maximum likelihood (REML) estimator of the dispersion matrix for random coefficient models is rewritten in terms of the sufficient statistics of the individual regressions.

Methodology · Statistics 2019-11-14 Kurt S. Riedel

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

We develop two novel approaches for constructing skewed and bimodal flexible distributions that can effectively generalize classical symmetric distributions. We illustrate the application of introduced techniques by extending normal,…

Methodology · Statistics 2021-07-01 Jamil Ownuk , Ahmad Nezakati , Hossein Baghishani

This paper deals with the estimation of reliability $R=P(Y<X)$ when $X$ is a random strength of a component subjected to a random stress $Y$ and $(X,Y)$ follows a bivariate Rayleigh distribution. The maximum likelihood estimator of $R$ and…

Statistics Theory · Mathematics 2014-05-20 Abbas Pak , Nayereh Bagheri Khoolenjani , Ali Akbar Jafari

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

Parameter estimation in Coxian phase-type models can be challenging due to their non-unique representation leading to a multi-modal likelihood. Since each representation corresponds to a different underlying data-generating mechanism, it is…

Statistics Theory · Mathematics 2019-07-24 Jean Rizk , Kevin Burke , Cathal Walsh
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