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The maximum likelihood degree of a statistical model refers to the number of solutions, where the derivative of the log-likelihood function is zero, over the complex field. This paper examines the maximum likelihood degree of the parameter…

Statistics Theory · Mathematics 2025-02-10 Pooja Yadav , Tanuja Srivastava

The likelihood function is central to both frequentist and Bayesian formulations of parametric statistical inference, and large-sample approximations to the sampling distributions of estimators and test statistics, and to posterior…

Methodology · Statistics 2022-04-05 Anthony C. Davison , Nancy Reid

This paper considers the issue of modeling fractional data observed in the interval [0,1), (0,1] or [0,1]. Mixed continuous-discrete distributions are proposed. The beta distribution is used to describe the continuous component of the model…

Methodology · Statistics 2008-03-19 Raydonal Ospina , Silvia L. P. Ferrari

We study the distribution of the occurrence of rare patterns in sufficiently mixing Gibbs random fields on the lattice $\mathbb{Z}^d$, $d\geq 2$. A typical example is the high temperature Ising model. This distribution is shown to converge…

Probability · Mathematics 2009-11-10 M. Abadi , J. -R. Chazottes , F. Redig , E. Verbitskiy

Starting with just the assumption of uniformly distributed orbital orientations, we derive expressions for the distributions of the Keplerian orbital elements as functions of arbitrary distributions of eccentricity and semi-major axis. We…

Instrumentation and Methods for Astrophysics · Physics 2011-01-24 Dmitry Savransky , Eric Cady , N. Jeremy Kasdin

In algebraic statistics, the maximum likelihood degree of a statistical model refers to the number of solutions (counted with multiplicity) of the score equations over the complex field. In this paper, the maximum likelihood degree of the…

Statistics Theory · Mathematics 2025-11-14 Pooja Yadav , Tanuja Srivastava

In this paper, we propose a new class of bivariate distributions, called the bivariate discrete inverse Weibull (BDsIW) distribution, whose marginals are discrete inverse Weibull (DsIW) distributions. Some statistical and mathematical…

Statistics Theory · Mathematics 2018-08-24 M. S. Eliwa , M. El-Morshedy

Topp Leone q Exponential Distruibution is a continuous model distribution used for modelling lifetime phenomena. In this study, we introduce different estimation methods for the unknown parameters of Topp Leone Exponential(TLE) distribution…

Statistics Theory · Mathematics 2021-03-08 Nicy Sebastian , V R Rajitha

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

A random variable is equi-dispersed if its mean equals its variance. A Poisson distribution is a classical example of this phenomenon. However, a less well-known fact is that the class of normal densities that are equi-dispersed constitutes…

Statistics Theory · Mathematics 2022-09-07 Barry C. Arnold , B. G. Manjunath

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

The experimentally measured multiplicity distributions exhibit, after closer inspection, peculiarly enhanced void probability and oscillatory behavior of the modified combinants. We show that both these features can be used as additional…

High Energy Physics - Phenomenology · Physics 2019-09-05 M. Rybczynski , Z. Wlodarczyk , G. Wilk

In this study an attempt has been made to propose a way to develop new distribution. For this purpose, we need only idea about distribution function. Some important statistical properties of the new distribution like moments, cumulants,…

Methodology · Statistics 2024-08-30 Brijesh P. Singh , Utpal Dhar Das

The sum of independent, but not necessary identically distributed, exponential random variables follows hypoexponential distribution. We focus on a particular case when all, but one rate parameters of the exponential variables are…

Probability · Mathematics 2023-04-04 George Yanev

The statistical duality of distributions is a powerful tool for statistical inferences. In the paper the statistical duality of Laplace distribution is discussed. As shown the confidence density of the parameter of this distribution is…

Statistics Theory · Mathematics 2007-06-13 E. A. Barkova , S. I. Bityukov , V. A. Taperechkina

Our contribution is to widen the scope of extreme value analysis applied to discrete-valued data. Extreme values of a random variable $X$ are commonly modeled using the generalized Pareto distribution, a method that often gives good results…

Statistics Theory · Mathematics 2017-07-18 Adrien Hitz , Richard Davis , Gennady Samorodnitsky

In this paper we study the distribution of the scaled largest eigenvalue of complexWishart matrices, which has diverse applications both in statistics and wireless communications. Exact expressions, valid for any matrix dimensions, have…

Information Theory · Computer Science 2012-02-06 Lu Wei , Olav Tirkkonen , Prathapasinghe Dharmawansa , Matthew McKay

In numerous instances, the generalized exponential distribution can be used as an alternative to the most widely used non-regular family of distributions: Weibull, gamma, lognormal with three-parameters when analyzing lifetime or any skewed…

Methodology · Statistics 2026-03-03 Kiran Prajapat , Sharmishtha Mitra , Debasis Kundu

The main object of this article is to present an extension of the zero-inflated Poisson-Lindley distribution, called of zero-modified Poisson-Lindley. The additional parameter $\pi$ of the zero-modified Poisson-Lindley has a natural…

Methodology · Statistics 2018-11-28 Danillo Xavier , Manoel Santos-Neto , Marcelo Bourguignon , Vera Tomazella

We extend a recently established asymptotic normality theorem for generalized linear mixed models to include the dispersion parameter. The new results show that the maximum likelihood estimators of all model parameters have asymptotically…

Statistics Theory · Mathematics 2022-08-11 Aishwarya Bhaskaran , Matt P. Wand
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