Parametric inference for stochastic differential equations driven by a mixed fractional Brownian motion with random effects based on discrete observations

DOI10.1080/07362994.2021.1902352zbMath1493.62511OpenAlexW3148420303WikidataQ115297184 ScholiaQ115297184MaRDI QIDQ5074266

B. L. S. Prakasa Rao

Publication date: 9 May 2022

Published in: Stochastic Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/07362994.2021.1902352

zbMATH Keywords

stochastic differential equationrandom effectsdiscrete observationsparametric inferencemixed fractional Brownian motion

Mathematics Subject Classification ID

Gaussian processes (60G15) Non-Markovian processes: estimation (62M09)

Related Items (1)

Maximum likelihood estimation for stochastic differential equations driven by a mixed fractional Brownian motion with random effects

Cites Work

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• Mixed Gaussian processes: a filtering approach
• Large deviations for drift parameter estimator of mixed fractional Ornstein-Uhlenbeck process
• Mixed stochastic differential equations with long-range dependence: existence, uniqueness and convergence of solutions
• Nonparametric estimation of trend for stochastic differential equations driven by sub-fractional Brownian motion
• Practical estimation of high dimensional stochastic differential mixed-effects models
• Comparison of nonparametric methods in nonlinear mixed effects models
• Mixed fractional Brownian motion
• Pricing geometric Asian power options under mixed fractional Brownian motion environment
• Mixed stochastic differential equations: existence and uniqueness result
• Parameter estimation for stochastic differential equations driven by mixed fractional Brownian motion
• Convergence rate of MLE in generalized linear and nonlinear mixed-effects models: Theory and applications
• Minimum \(L_1\)-norm estimation for mixed fractional Ornstein-Uhlenbeck type process
• Stochastic calculus for fractional Brownian motion and related processes.
• Strong consistency of the maximum likelihood estimator in generalized linear and nonlinear mixed-effects models
• Mixed stochastic delay differential equations
• Stochastic Differential Mixed-Effects Models
• Stochastic Differential Equations Driven by Fractional Brownian Motion and Standard Brownian Motion
• Statistical Inference for Fractional Diffusion Processes
• Instrumental variable estimation for a linear stochastic differential equation driven by a mixed fractional Brownian motion
• Statistical Analysis of the Mixed Fractional Ornstein--Uhlenbeck Process
• Parametric estimation for linear stochastic differential equations driven by mixed fractional Brownian motion
• Maximum Likelihood Estimation for Stochastic Differential Equations with Random Effects
• LARGE DEVIATION PROBABILITIES FOR MAXIMUM LIKELIHOOD ESTIMATOR AND BAYES ESTIMATOR OF A PARAMETER FOR MIXED FRACTIONAL ORNSTEIN-UHLENBECK TYPE PROCESS
• OPTION PRICING FOR PROCESSES DRIVEN BY MIXED FRACTIONAL BROWNIAN MOTION WITH SUPERIMPOSED JUMPS
• Non parametric estimation for fractional diffusion processes with random effects

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