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Related papers: On partially observed jump diffusions I. The filte…

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We consider the problem of statistical inference for a class of partially-observed diffusion processes, with discretely-observed data and finite-dimensional parameters. We construct unbiased estimators of the score function, i.e. the…

Methodology · Statistics 2021-05-12 Jeremy Heng , Jeremie Houssineau , Ajay Jasra

We derive expressions for the first three moments of the decision time (DT) distribution produced via first threshold crossings by sample paths of a drift-diffusion equation. The "pure" and "extended" diffusion processes are widely used to…

Neurons and Cognition · Quantitative Biology 2016-01-26 Vaibhav Srivastava , Philip Holmes , Patrick Simen

In this paper we consider the filtering of partially observed multi-dimensional diffusion processes that are observed regularly at discrete times. We assume that, for numerical reasons, one has to time-discretize the diffusion process which…

Computation · Statistics 2023-02-21 Ajay Jasra , Mohamed Maama , Hernando Ombao

We investigate the existence of a robust, i.e., continuous, representation of the conditional distribution in a stochastic filtering model for multidimensional correlated jump-diffusions. Even in the absence of jumps, it is known that in…

Probability · Mathematics 2026-05-29 Andrew L. Allan , Jost Pieper , Josef Teichmann

The filtering of a Markov diffusion process on a manifold from counting process observations leads to `large' changes in the conditional distribution upon an observed event, corresponding to a multiplication of the density by the intensity…

Optimization and Control · Mathematics 2019-11-01 Simone Carlo Surace , Anna Kutschireiter , Jean-Pascal Pfister

We study a class of interacting particle systems on $\mathbb{R}$ with two types. Particles evolve by independent jumps sampled from a fixed distribution, with type-dependent jump rates $v_+$, $v_-$ and stochastic type switching driven by…

Probability · Mathematics 2026-05-14 Sayan Banerjee , Andrew Nguyen

The smoothing distribution is the conditional distribution of the diffusion process in the space of trajectories given noisy observations made continuously in time. It is generally difficult to sample from this distribution. We use the…

Probability · Mathematics 2025-03-07 Oskar Eklund , Annika Lang , Moritz Schauer

For a one dimensional diffusion process $X=\{X(t) ; 0\leq t \leq T \}$, we suppose that $X(t)$ is hidden if it is below some fixed and known threshold $\tau$, but otherwise it is visible. This means a partially hidden diffusion process. The…

Statistics Theory · Mathematics 2011-11-09 Stefano Iacus , Masayuki Uchida , Nakahiro Yoshida

In this paper we present stochastic foundations of fractional dynamics driven by fractional material derivative of distributed order-type. Before stating our main result we present the stochastic scenario which underlies the dynamics given…

Probability · Mathematics 2015-10-02 Marcin Magdziarz , Marek Teuerle

Second order recurrence of a $d$-dimensional diffusion with an additive Wiener process, with switching, and with one recurrent and one transient regime and constant switching intensities is established under suitable conditions. The…

Probability · Mathematics 2024-06-25 Alexander Veretennikov

In this paper, we study the estimation of drift and diffusion coefficients in a two dimensional system of N interacting particles modeled by a degenerate stochastic differential equation. We consider both complete and partial observation…

Statistics Theory · Mathematics 2026-03-31 Chiara Amorino , Vytautė Pilipauskaitė

In this paper we focus on the pathwise stability of mild solutions for a class of stochastic partial differential equations which are driven by switching-diffusion processes with jumps. In comparison to the existing literature, we show…

Probability · Mathematics 2015-03-13 Chenggui Yuan , Jianhai Bao

Stochastic evolution equations with compensated Poisson noise are considered in the variational approach with monotone and coercive coefficients. Here the Poisson noise is assumed to be time-homogeneous with $\sigma$-finite intensity…

Probability · Mathematics 2022-04-20 Sima Mehri , Erfan Salavati , Bijan Z. Zangeneh

We study some linear and nonlinear shot noise models where the jumps are drawn from a compound Poisson process with jump sizes following an Erlang-$m$ distribution. We show that the associated Master equation can be written as a spatial…

Mathematical Physics · Physics 2016-06-03 Max-Olivier Hongler , Roger Filliger

This work examines a class of switching jump diffusion processes. The main effort is devoted to proving the maximum principle and obtaining the Harnack inequalities. Compared with the diffusions and switching diffusions, the associated…

Probability · Mathematics 2018-10-02 Xiaoshan Chen , Zhen-Qing Chen , Ky Tran , George Yin

Einstein's explanation of Brownian motion provided one of the cornerstones which underlie the modern approaches to stochastic processes. His approach is based on a random walk picture and is valid for Markovian processes lacking long-term…

Statistical Mechanics · Physics 2009-11-10 I. M. Sokolov , J. Klafter

We consider a fractional counting process with jumps of amplitude $1,2,\ldots,k$, with $k\in \mathbb{N}$, whose probabilities satisfy a suitable system of fractional difference-differential equations. We obtain the moment generating…

Probability · Mathematics 2016-03-10 Antonio Di Crescenzo , Barbara Martinucci , Alessandra Meoli

In this article we address the problem of the nonlinear interaction of subdiffusive particles. We introduce the random walk model in which statistical characteristics of a random walker such as escape rate and jump distribution depend on…

Statistical Mechanics · Physics 2015-06-15 Sergei Fedotov

The connection between forward backward doubly stochastic differential equations and the optimal filtering problem is established without using the Zakai's equation. The solutions of forward backward doubly stochastic differential equations…

Numerical Analysis · Mathematics 2018-05-29 Richard Archibald , Feng Bao , Peter Maksymovych

We consider a Wright-Fisher diffusion (x(t)) whose current state cannot be observed directly. Instead, at times t1 < t2 < . . ., the observations y(ti) are such that, given the process (x(t)), the random variables (y(ti)) are independent…

Probability · Mathematics 2007-07-05 Mireille Chaleyat-Maurel , Valentine Genon-Catalot