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We study a general setting of neutral evolution in which the population is of finite, constant size and can have spatial structure. Mutation leads to different genetic types ("traits"), which can be discrete or continuous. Under minimal…

Populations and Evolution · Quantitative Biology 2018-11-02 Alex McAvoy , Ben Adlam , Benjamin Allen , Martin A. Nowak

Continuous-time Markov chains describing interacting processes exhibit a state space that grows exponentially in the number of processes. This state-space explosion renders the computation or storage of the time-marginal distribution, which…

Numerical Analysis · Mathematics 2020-06-16 Peter Georg , Lars Grasedyck , Maren Klever , Rudolf Schill , Rainer Spang , Tilo Wettig

The concepts of probability, statistics and stochastic theory are being successfully used in structural engineering. Markov Chain modelling is a simple stochastic process model that has found its application in both describing stochastic…

Applications · Statistics 2007-08-14 K. Balaji Rao

Continuous-time Markov chains on non-negative integers can be used for modeling biological systems, population dynamics, and queueing models. Qualitative behaviors of birth-and-death models, typical examples of such one-dimensional…

Probability · Mathematics 2025-10-24 Minjun Kim , Seokhwan Moon , Jinsu Kim

We describe briefly in this note a procedure for consistently estimating the marginal likelihood of a statistical model through a sample from the posterior distribution of the model parameters.

Statistics Theory · Mathematics 2014-06-12 Paulo C. Marques F

The aim of this paper is to give an explicit formula of the invariant distribution of a quasi-birth-and-death process in terms of the block entries of the transition probability matrix using a matrix-valued orthogonal polynomials approach.…

Probability · Mathematics 2015-05-19 Manuel D. de la Iglesia

Predictive constructions are a powerful way of characterizing the probability law of stochastic processes with certain forms of invariance, such as exchangeability or Markov exchangeability. When de Finetti-like representation theorems are…

Methodology · Statistics 2015-11-16 Sandra Fortini , Sonia Petrone

We consider branching processes describing structured, interacting populations in continuous time. Dynamics of each individuals characteristics and branching properties can be influenced by the entire population. We propose a Girsanov-type…

Probability · Mathematics 2024-05-15 Charles Medous

This paper considers general term structure models like the ones appearing in portfolio credit risk modelling or life insurance. We give a general model starting from families of forward rates driven by infinitely many Brownian motions and…

Pricing of Securities · Quantitative Finance 2013-06-27 Stefan Tappe , Thorsten Schmidt

This paper studies the quasi-stationary distributions for a single death process (or downwardly skip-free process) with killing defined on the non-negative integers, corresponding to a non-conservative transition rate matrix. The set…

Probability · Mathematics 2024-08-13 Zhe-Kang Fang , Yong-Hua Mao

For a Markov chain $\mathbf{X}=\{X_i,i=1,2,...,n\}$ with the state space $\{0,1\}$, the random variable $S:=\sum_{i=1}^nX_i$ is said to follow a Markov binomial distribution. The exact distribution of $S$, denoted $\mathcal{L}S$, is very…

Statistics Theory · Mathematics 2010-01-14 Aihua Xia , Mei Zhang

A discrete-time stochastic process derived from a model of basketball is used to generalize any discrete distribution. The generalized distributions can have one or two more parameters than the parent distribution. Those derived from…

Applications · Statistics 2020-06-25 Rose Baker

Bayesian nonparametric inferential procedures based on Markov chain Monte Carlo marginal methods typically yield point estimates in the form of posterior expectations. Though very useful and easy to implement in a variety of statistical…

Statistics Theory · Mathematics 2016-05-04 Julyan Arbel , Antonio Lijoi , Bernardo Nipoti

Computational procedures for the stationary probability distribution, the group inverse of the Markovian kernel and the mean first passage times of an irreducible Markov chain, are developed using perturbations. The derivation of these…

Probability · Mathematics 2016-10-12 Jeffrey J. Hunter

We construct a family of self-similar Markov martingales with given marginal distributions. This construction uses the self-similarity and Markov property of a reference process to produce a family of Markov processes that possess the same…

Statistics Theory · Mathematics 2015-06-05 Jie Yen Fan , Kais Hamza , Fima Klebaner

We introduce an extension of finite mixture models by incorporating skew-normal distributions within a Hidden Markov Model framework. By assuming a constant transition probability matrix and allowing emission distributions to vary according…

Methodology · Statistics 2025-09-25 Andrea Nigri , Marco Forti , Han Lin Shang

Pendry and MacKinnon meaningful discretization of Maxwell's equations was put forward specifically as part of a finite-element numerical algorithm. By contrast with a numerical approach, in the same spirit evoked by the relationships…

Optics · Physics 2023-03-14 Ovidiu-Zeno Lipan , Aldo De Sabata

Conditions for positive and polynomial recurrence have been proposed for a class of reliability models of two elements with transitions from working state to failure and back. As a consequence, uniqueness of stationary distribution of the…

Probability · Mathematics 2020-05-29 Alexander Veretennikov

Clustered observations are ubiquitous in controlled and observational studies and arise naturally in multi-centre trials or longitudinal surveys. We present a novel model for the analysis of clustered observations where the marginal…

Methodology · Statistics 2022-11-03 Luisa Barbanti , Torsten Hothorn

A birth-death-move process with mutations is a Markov model for a system of marked particles in interaction, that move over time, with births and deaths. In addition the mark of each particle may also change, which constitutes a mutation.…

Statistics Theory · Mathematics 2026-04-08 Lisa Balsollier , Frédéric Lavancier
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