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Related papers: Nonlinearly Perturbed Birth-Death-Type Models

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In this paper some general theory is presented for locally stationary processes based on the stationary approximation and the stationary derivative. Laws of large numbers, central limit theorems as well as deterministic and stochastic bias…

Statistics Theory · Mathematics 2017-11-21 Rainer Dahlhaus , Stefan Richter , Wei Biao Wu

Non-standard distributional approximations have received considerable attention in recent years. They often provide more accurate approximations in small samples, and theoretical improvements in some cases. This paper shows that the…

Statistics Theory · Mathematics 2017-12-12 Matias D. Cattaneo , Michael Jansson , Whitney K. Newey

We consider a nonlinear structured population model with a distributed recruitment term. The question of the existence of non-trivial steady states can be treated (at least!) in three different ways. One approach is to study spectral…

Populations and Evolution · Quantitative Biology 2019-03-06 Azmy S. Ackleh , Jozsef Z. Farkas

We study the statistical properties of the stationary firing-rate states of a neural network model with quenched disorder. The model has arbitrary size, discrete-time evolution equations and binary firing rates, while the topology and the…

Neurons and Cognition · Quantitative Biology 2019-07-24 Diego Fasoli , Stefano Panzeri

In this article, we provide different representations for a time-fractional birth and death process $N_{\alpha}(t)$, whose transition probabilities are governed by a time-fractional system of differential equations. More specifically, we…

Probability · Mathematics 2020-04-30 Jorge Littin

A model describing the dynamics related to the spreading of non-lethal infectious diseases in a fixed-size population is proposed. The model consists of a non-linear delay-differential equation describing the time evolution of the increment…

Populations and Evolution · Quantitative Biology 2010-10-05 A. Noviello , F. Romeo , R. De Luca

This paper reviews recent advances in Bayesian nonparametric techniques for constructing and performing inference in infinite hidden Markov models. We focus on variants of Bayesian nonparametric hidden Markov models that enhance a…

Methodology · Statistics 2014-07-02 Jonathan H. Huggins , Frank Wood

Spatial birth-and-death processes with a finite number of particles are obtained as unique solutions to certain stochastic equations. Conditions are given for existence and uniqueness of such solutions, as well as for continuous dependence…

Probability · Mathematics 2015-02-25 Viktor Bezborodov

In this paper we consider a physiologically structured population model with distributed states at birth, formulated on the space of non-negative Radon measures. Using a characterisation of the pre-dual space of bounded Lipschitz functions,…

Analysis of PDEs · Mathematics 2022-05-17 József Z. Farkas , Piotr Gwiazda , Anna Marciniak-Czochra

We propose a new semiparametric approach for modelling nonlinear univariate diffusions, where the observed process is a nonparametric transformation of an underlying parametric diffusion (UPD). This modelling strategy yields a general class…

Econometrics · Economics 2020-05-08 Ruijun Bu , Kaddour Hadri , Dennis Kristensen

A nonhomogeneous hidden semi-Markov model is proposed to segment toroidal time series according to a finite number of latent regimes and, simultaneously, estimate the influence of time-varying covariates on the process' survival under each…

Applications · Statistics 2023-12-25 Francesco Lagona , Marco Mingione

In this paper, we propose a semi-parametric model for autonomous nonlinear dynamical systems and devise an estimation procedure for model fitting. This model incorporates subject-specific effects and can be viewed as a nonlinear…

Methodology · Statistics 2009-06-19 Debashis Paul , Jie Peng , Prabir Burman

In this note we highlight the role of fractional linear birth and linear death processes recently studied in \citet{sakhno} and \citet{pol}, in relation to epidemic models with empirical power law distribution of the events. Taking…

Probability · Mathematics 2013-03-28 Roberto Garra , Federico Polito

We study the long time behaviour of a Markov process evolving in $\mathbb{N}$ and conditioned not to hit 0. Assuming that the process comes back quickly from infinity, we prove that the process admits a unique quasi-stationary distribution…

Probability · Mathematics 2013-04-04 Servet Martinez , Jaime San Martin , Denis Villemonais

We study quasi-stationary distributions and quasi-limiting behavior of Markov chains in general reducible state spaces with absorption. We propose a set of assumptions dealing with particular situations where the state space can be…

Probability · Mathematics 2026-01-14 Nicolas Champagnat , Denis Villemonais

This paper considers the subexponential asymptotics of the stationary distributions of GI/G/1-type Markov chains in two cases: (i) the phase transition matrix in non-boundary levels is stochastic; and (ii) it is strictly substochastic. For…

Probability · Mathematics 2016-06-22 Tatsuaki Kimura , Hiroyuki Masuyama , Yutaka Takahashi

A method of expansion of solutions of singularly perturbed nonlinear systems in power series of small parameters is applied to the popular Lorenz model in synergetics.Simple asymptotic expressions for the solution to the model in…

chao-dyn · Physics 2007-05-23 E. M. Shahverdiev

In this paper we find asymptotic distribution for some unreliable networks. Using Markov Additive Structure and Adan, Foley, McDonald method, we find the exact asymptotic for the stationary distribution. With the help of MA structure and…

Probability · Mathematics 2011-02-24 Pawel Lorek

A parameter estimation problem for a class of semilinear stochastic evolution equations is considered. Conditions for consistency and asymptotic normality are given in terms of growth and continuity properties of the nonlinear part.…

Statistics Theory · Mathematics 2020-02-26 Gregor Pasemann , Wilhelm Stannat

The well-established methodology for the estimation of hidden semi-Markov models (HSMMs) as hidden Markov models (HMMs) with extended state spaces is further developed to incorporate covariate influences across all aspects of the state…

Methodology · Statistics 2024-05-24 Jan-Ole Koslik