Using maximum cross section method for filtering jump-diffusion random processes

DOI10.1515/rnam-2020-0005OpenAlexW3031353693MaRDI QIDQ2187855

Konstantin A. Rybakov, Tatiana A. Averina

Publication date: 3 June 2020

Published in: Russian Journal of Numerical Analysis and Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/rnam-2020-0005

zbMATH Keywords

estimationfilteringparticle methodstatistical modellingparticle filterstochastic differential equation with jumpsmaximum cross Section method

Mathematics Subject Classification ID

Numerical analysis (65-XX)

Related Items

On one method for modeling an nonhomogeneous Poisson point process ⋮ Unnamed Item ⋮ Unnamed Item ⋮ Unnamed Item ⋮ Maximum cross section method in the filtering problem for continuous systems with Markovian switching ⋮ Unnamed Item ⋮ Statistical filtering algorithms for systems withrandom structure

Cites Work

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• Exact simulation of jump-diffusion processes with Monte Carlo applications
• Fundamentals of stochastic filtering
• Numerical solution of stochastic differential equations with jumps in finance
• The maximal section algorithm in the Monte Carlo method
• Statistical analysis of diffusion systems with invariants
• Optimal continuous-discrete nonlinear finite memory filter with discrete predictions
• Theory of stochastic differential equations with jumps and applications.
• Pugachev's filters for complex information processing
• Continuous finite-dimensional locally optimal filtering of jump diffusions
• The Zakai equation of nonlinear filtering for jump-diffusion observations: existence and uniqueness
• Conditionally minimax nonlinear filter and unscented Kalman filter: empirical analysis and comparison
• Nonlinear filtering for jump-diffusions
• Exact simulation problems for jump-diffusions
• Stochastic processes and filtering theory
• Algorithms for exact and approximate statistical simulation of Poisson ensembles
• Nonlinear Filtering for Jump Diffusion Observations
• Ornstein–Uhlenbeck Processes and Extensions
• Parallel realization of statistical simulation and random number generators
• On lie algebras and finite dimensional filtering
• Solving approximately a prediction problem for stochastic jump-diffusion systems