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Related papers: Filtering coupled Wright-Fisher diffusions

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The increasing availability of population-level allele frequency data across one or more related populations necessitates the development of methods that can efficiently estimate population genetics parameters, such as the strength of…

Computation · Statistics 2017-11-09 Jeffrey J. Gory , Radu Herbei , Laura S. Kubatko

We consider a discrete latent variable model for two-way data arrays, which allows one to simultaneously produce clusters along one of the data dimensions (e.g. exchangeable observational units or features) and contiguous groups, or…

We propose a method for inference on moderately high-dimensional, nonlinear, non-Gaussian, partially observed Markov process models for which the transition density is not analytically tractable. Markov processes with intractable transition…

Methodology · Statistics 2020-04-02 Joonha Park , Edward L. Ionides

Probabilistic finite mixture models are widely used for unsupervised clustering. These models can often be improved by adapting them to the topology of the data. For instance, in order to classify spatially adjacent data points similarly,…

Computer Vision and Pattern Recognition · Computer Science 2022-02-09 Jonathan Vacher , Claire Launay , Ruben Coen-Cagli

We study two types of stochastic processes, a mean-field spatial system of interacting Fisher-Wright diffusions with an inferior and an advantageous type with rare mutation (inferior to advantageous) and a (mean-field) spatial system of…

Probability · Mathematics 2010-08-02 Donald A. Dawson , Andreas Greven

The method of potential solutions of Fokker-Planck equations is used to develop a transport equation for the joint probability of N coupled stochastic variables with the Dirichlet distribution as its asymptotic solution. To ensure a bounded…

Mathematical Physics · Physics 2013-03-05 J. Bakosi , J. R. Ristorcelli

We investigate various aspects of the (biallelic) Wright-Fisher diffusion with seed bank in conjunction with and contrast to the two-island model analysed e.g. in Kermany, Zhou and Hickey, 2008, and Nath and Griffiths, 1993, including…

Filtering is concerned with the sequential estimation of the state, and uncertainties, of a Markovian system, given noisy observations. It is particularly difficult to achieve accurate filtering in complex dynamical systems, such as those…

Probability · Mathematics 2015-12-14 Wonjung Lee , Andrew Stuart

In [arXiv:1906.10951 (forthcoming on Advances in Applied Probability),arXiv:2011.05933 (published on PLOS ONE)] the authors introduce, study and apply a new variant of the Eggenberger-Polya urn, called the "Rescaled" Polya urn, which, for a…

Probability · Mathematics 2022-03-30 Giacomo Aletti , Irene Crimaldi

We extend classic characterisations of posterior distributions under Dirichlet process and gamma random measures priors to a dynamic framework. We consider the problem of learning, from indirect observations, two families of time-dependent…

Statistics Theory · Mathematics 2016-11-23 Omiros Papaspiliopoulos , Matteo Ruggiero , Dario Spanò

The recently introduced two-parameter infinitely-many neutral alleles model extends the celebrated one-parameter version, related to Kingman's distribution, to diffusive two-parameter Poisson-Dirichlet frequencies. Here we investigate the…

Probability · Mathematics 2014-04-02 Matteo Ruggiero

The Wright-Fisher family of diffusion processes is a widely used class of evolutionary models. However, simulation is difficult because there is no known closed-form formula for its transition function. In this article we demonstrate that…

Methodology · Statistics 2023-10-02 Paul A. Jenkins , Dario Spano

The two-parameter Poisson-Dirichlet diffusion takes values in the infinite ordered simplex and extends the celebrated infinitely-many-neutral-alleles model, having a two-parameter Poisson-Dirichlet stationary distribution. Here we identify…

Probability · Mathematics 2024-10-16 Robert C. Griffiths , Matteo Ruggiero , Dario Spanò , Youzhou Zhou

We develop an iterative global solution scheme for the backward Kolmogorov equation of the diffusion approximation of the Wright-Fisher model of population genetics. That model describes the random genetic drift of several alleles at the…

Analysis of PDEs · Mathematics 2014-06-20 Julian Hofrichter , Tat Dat Tran , Jürgen Jost

A forward diffusion equation describing the evolution of the allele frequency spectrum is presented. The influx of mutations is accounted for by imposing a suitable boundary condition. For a Wright-Fisher diffusion with or without selection…

Populations and Evolution · Quantitative Biology 2007-05-23 Steven N. Evans , Yelena Shvets , Montgomery Slatkin

We apply a Lindeberg principle under the Markov process setting to approximate the Wright-Fisher model with neutral $r$-alleles using a diffusion process, deriving an error rate based on a function class distance involving fourth-order…

Probability · Mathematics 2024-07-15 Peng Chen , Jie Xiong , Lihu Xu , Jiayu Zheng

Marine species reproduce and compete while being advected by turbulent flows. It is largely unknown, both theoretically and experimentally, how population dynamics and genetics are changed by the presence of fluid flows. Discrete…

Populations and Evolution · Quantitative Biology 2019-12-24 Giorgia Guccione , Roberto Benzi , Abigail Plummer , Federico Toschi

Study sample sizes in human genetics are growing rapidly, and in due course it will become routine to analyze samples with hundreds of thousands if not millions of individuals. In addition to posing computational challenges, such large…

Populations and Evolution · Quantitative Biology 2015-06-24 Anand Bhaskar , Andrew G. Clark , Yun S. Song

The Wright-Fisher (W-F) diffusion model serves as a foundational framework for interpreting population evolution through allele frequency dynamics over time. Despite the known transition probability between consecutive generations, an exact…

Methodology · Statistics 2024-06-24 Tania Roa , María Inés Fariello , Gerardo Martínez , José León

Within Bayesian nonparametrics, dependent Dirichlet process mixture models provide a highly flexible approach for conducting inference about the conditional density function. However, several formulations of this class make either rather…

Methodology · Statistics 2024-05-14 María Xosé Rodríguez-Álvarez , Vanda Inácio , Nadja Klein