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In this paper, a new mixed Poisson distribution is introduced. This new distribution is obtained by utilizing mixing process, with Poisson distribution as mixed distribution and Transmuted Exponential distribution as mixing distribution.…

Methodology · Statistics 2016-10-05 Deepesh Bhati , Pooja Kumawat , E. Gómez Déniz

While generic competitive systems exhibit mixtures of hierarchy and cycles, real-world systems are predominantly hierarchical. We demonstrate and extend a mechanism for hierarchy; systems with similar agents approach perfect hierarchy in…

Populations and Evolution · Quantitative Biology 2024-02-12 Christopher Cebra , Alexander Strang

In this contribution, we present new algorithms to source separation for the case of noisy instantaneous linear mixture, within the Bayesian statistical framework. The source distribution prior is modeled by a mixture of Gaussians…

Data Analysis, Statistics and Probability · Physics 2009-11-07 Hichem Snoussi , Ali Mohammad-Djafari

Estimating the impact of environmental processes on vertical reef development in geological time is a very challenging task. pyReef-Core is a deterministic carbonate stratigraphic forward model designed to simulate the key biological and…

Increasing pressures on the environment are generating an ever-increasing need to manage animal and plant populations sustainably, and to protect and rebuild endangered populations. Effective management requires reliable mathematical…

Methodology · Statistics 2009-09-29 Stephen T. Buckland , Ken B. Newman , Carmen Fernández , Len Thomas , John Harwood

Network models provide a powerful framework for analysing single-cell count data, facilitating the characterisation of cellular identities, disease mechanisms, and developmental trajectories. However, uncertainty modeling in unsupervised…

Genomics · Quantitative Biology 2026-04-27 Shanshan Ren , Thomas E. Bartlett , Lina Gerontogianni , Swati Chandna

A Bayesian approach is used to estimate the covariance matrix of Gaussian data. Ideas from Gaussian graphical models and model selection are used to construct a prior for the covariance matrix that is a mixture over all decomposable graphs.…

Methodology · Statistics 2007-06-12 Helen Armstrong , Christopher K. Carter , Kevin F. Wong , Robert Kohn

In population genetics, extant samples are usually used for inference of past population genetic forces. With the Kingman coalescent and the backward diffusion equation, inference of the marginal likelihood proceeds from an extant sample…

Populations and Evolution · Quantitative Biology 2020-04-03 Claus Vogl , Sandra Peer

Surveys often ask respondents to report nonnegative counts, but respondents may misremember or round to a nearby multiple of 5 or 10. This phenomenon is called heaping, and the error inherent in heaped self-reported numbers can bias…

Applications · Statistics 2015-09-15 Forrest W. Crawford , Robert E. Weiss , Marc A. Suchard

A central part of population genomics consists of finding genomic regions implicated in local adaptation. Population genomic analyses are based on genotyping numerous molecular markers and looking for outlier loci in terms of patterns of…

Populations and Evolution · Quantitative Biology 2014-07-30 N. Duforet-Frebourg , E. Bazin , M. G. B. Blum

Admixed populations are formed by the merging of two or more ancestral populations, and the ancestry of each locus in an admixed genome derives from either source. Consider a simple "pulse" admixture model, where populations A and B merged…

Populations and Evolution · Quantitative Biology 2015-09-22 Shai Carmi , James Xue , Itsik Pe'er

We propose a method for estimating the posterior distribution of a standard geostatistical model. After choosing the model formulation and specifying a prior, we use normal mixture densities to approximate the posterior distribution. The…

Methodology · Statistics 2014-09-10 Zepu Zhang

The paper tackles the problem of clustering multiple networks, directed or not, that do not share the same set of vertices, into groups of networks with similar topology. A statistical model-based approach based on a finite mixture of…

Statistics Theory · Mathematics 2023-11-07 Tabea Rebafka

Bayesian hierarchical models are a methodology for aggregation and synthesis of data from heterogeneous settings, used widely in statistics and other disciplines. I apply this framework to the evidence from 7 randomized experiments of…

Economics · Quantitative Finance 2016-07-14 Rachael Meager

Mixture models are widely used in Bayesian statistics and machine learning, in particular in computational biology, natural language processing and many other fields. Variational inference, a technique for approximating intractable…

Statistics Theory · Mathematics 2020-08-03 Badr-Eddine Chérief-Abdellatif , Pierre Alquier

Non-Gaussian mixture models are gaining increasing attention for mixture model-based clustering particularly when dealing with data that exhibit features such as skewness and heavy tails. Here, such a mixture distribution is presented,…

Computation · Statistics 2020-05-07 Yuan Fang , Dimitris Karlis , Sanjeena Subedi

Gene-gene interactions are often regarded as playing significant roles in influencing variabilities of complex traits. Although much research has been devoted to this area, to date a comprehensive statistical model that addresses the…

Applications · Statistics 2018-04-18 Durba Bhattacharya , Sourabh Bhattacharya

We introduce and study a stochastic model for the dynamics of colonial species, which reproduce through fission or fragmentation. The fission rate depends on the relative sizes of colonies in the population, and the growth rate of colonies…

Probability · Mathematics 2025-01-30 Sylvain Billiard , Charles Medous , Charline Smadi

We consider the Moran model of population genetics with two types, mutation, and selection, and investigate the line of descent of a randomly-sampled individual from a contemporary population. We trace this ancestral line back into the…

Probability · Mathematics 2024-05-22 Ellen Baake , Enrico Di Gaspero , Fernando Cordero

Reproductive phenology, growth and mortality rates are key ecological parameters that determine population dynamics and are therefore of vital importance to stock assessment models for fisheries management. In many fish species, the…

Other Quantitative Biology · Quantitative Biology 2020-06-23 Vicenç Moltó , Andres Ospina-Alvarez , Mark Gatt , Miquel Palmer , Ignacio A. Catalán