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Related papers: Filtering the Wright-Fisher diffusion

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In this paper, a general model of wireless channels is established based on the physics of wave propagation. Then the problems of inverse scattering and channel prediction are formulated as nonlinear filtering problems. The solutions to the…

Data Analysis, Statistics and Probability · Physics 2015-06-26 Haiqing Wei

This paper introduces factored conditional filters, new filtering algorithms for simultaneously tracking states and estimating parameters in high-dimensional state spaces. The conditional nature of the algorithms is used to estimate…

Artificial Intelligence · Computer Science 2024-07-10 Dawei Chen , Samuel Yang-Zhao , John Lloyd , Kee Siong Ng

We prove a computable version of de Finetti's theorem on exchangeable sequences of real random variables. As a consequence, exchangeable stochastic processes expressed in probabilistic functional programming languages can be automatically…

Logic · Mathematics 2012-02-03 Cameron E. Freer , Daniel M. Roy

A phase space formulation of the filtering process upon an incident quantum state is developed. This formulation can explain the results of both quantum interference and delayed-choice experiments without making use of the controversial…

Quantum Physics · Physics 2009-11-10 Daniela Dragoman

The Wright-Fisher model and the Moran model are both widely used in population genetics. They describe the time evolution of the frequency of an allele in a well-mixed population with fixed size. We propose a simple and tractable model…

Populations and Evolution · Quantitative Biology 2024-12-30 Arthur Alexandre , Alia Abbara , Cecilia Fruet , Claude Loverdo , Anne-Florence Bitbol

Motivated by applications to prediction and forecasting, we suggest methods for approximating the conditional distribution function of a random variable Y given a dependent random d-vector X. The idea is to estimate not the distribution of…

Statistics Theory · Mathematics 2007-06-13 Peter Hall , Qiwei Yao

This paper addresses a problem in experimental design: We consider It\^o diffusions specified by some $\theta \in \mathbb{R}$ and assume that we are allowed to observe their sample paths only $n$ times before a terminal time $\tau <…

Methodology · Statistics 2017-09-05 Aurya Javeed , Giles Hooker

For recursive circular filtering based on circular statistics, we introduce a general framework for estimation of a circular state based on different circular distributions, specifically the wrapped normal distribution and the von Mises…

Systems and Control · Computer Science 2018-01-01 Gerhard Kurz , Igor Gilitschenski , Uwe D. Hanebeck

A model for diffusion on a cubic lattice with a random distribution of traps is developed. The traps are redistributed at certain time intervals. Such models are useful for describing systems showing dynamic disorder, such as ion-conducting…

Condensed Matter · Physics 2009-10-31 S. Mandal , R. Dasgupta

We consider the spread of a Susceptible-Infected-Recovered (SIR) disease through finite populations and derive an expression for the final size distribution. Our derivation allows arbitrary distributions of the number of transmissions…

Populations and Evolution · Quantitative Biology 2019-07-12 Joel C Miller

The process of dynamic state estimation (filtering) based on point process observations is in general intractable. Numerical sampling techniques are often practically useful, but lead to limited conceptual insight about optimal…

Machine Learning · Statistics 2015-08-04 Yuval Harel , Ron Meir , Manfred Opper

We present a general framework for Bayesian estimation of incompletely observed multivariate diffusion processes. Observations are assumed to be discrete in time, noisy and incomplete. We assume the drift and diffusion coefficient depend on…

Methodology · Statistics 2019-02-04 Frank van der Meulen , Moritz Schauer

In this paper we use splitting technique to estimate the probability of hitting a rare but critical set by the continuous component of a switching diffusion. Instead of following classical approach we use Wonham filter to achieve multiple…

Probability · Mathematics 2014-12-19 Anindya Goswami , François Le Gland

Fleming-Viot diffusions are widely used stochastic models for population dynamics which extend the celebrated Wright-Fisher diffusions. They describe the temporal evolution of the relative frequencies of the allelic types in an ideally…

Computation · Statistics 2026-01-07 Filippo Ascolani , Stefano Damato , Matteo Ruggiero

To ensure high quality outputs, it is important to quantify the epistemic uncertainty of diffusion models. Existing methods are often unreliable because they mix epistemic and aleatoric uncertainty. We introduce a method based on Fisher…

Machine Learning · Statistics 2026-02-18 Aditi Gupta , Raphael A. Meyer , Yotam Yaniv , Elynn Chen , N. Benjamin Erichson

Consider a distributed detection problem in which the underlying distributions of the observations are unknown; instead of these distributions, noisy versions of empirically observed statistics are available to the fusion center. These…

Information Theory · Computer Science 2020-02-13 Haiyun He , Lin Zhou , Vincent Y. F. Tan

The computation of two Bayesian predictive distributions which are discrete mixtures of incomplete beta functions is considered. The number of iterations can easily become large for these distributions and thus, the accuracy of the result…

Statistics Theory · Mathematics 2007-06-13 Jacques Poitevineau , Bruno Lecoutre

With the help of the methods developed in our previous article [Schmitz, to appear in "Annales de l'I.H.P. Prob. & Stat.], we highlight condition (T) as a source of new examples of 'ballistic' diffusions in a random environment when d>1…

Probability · Mathematics 2007-05-23 Tom Schmitz

We consider the notion of the matrix (tensor) distribution of a measurable function of several variables. On the one hand, it is an invariant of this function with respect to a certain group of transformations of variables; on the other…

Dynamical Systems · Mathematics 2023-11-03 A. Vershik

Counterfactual inference considers a hypothetical intervention in a parallel world that shares some evidence with the factual world. If the evidence specifies a conditional distribution on a manifold, counterfactuals may be analytically…

Machine Learning · Statistics 2024-07-03 Juha Karvanen , Santtu Tikka , Matti Vihola
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