MsdeParEst
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Software:37158
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Source code repository: https://github.com/cran/MsdeParEst
Related Items (22)
The stochastic system approach for estimating dynamic treatments effect ⋮ On asymptotics related to classical inference in stochastic differential equations with random effects ⋮ A review on asymptotic inference in stochastic differential equations with mixed effects ⋮ Bidimensional random effect estimation in mixed stochastic differential model ⋮ Estimation for stochastic differential equations with mixed effects ⋮ On Bayesian asymptotics in stochastic differential equations with random effects ⋮ Coupling the SAEM algorithm and the extended Kalman filter for maximum likelihood estimation in mixed-effects diffusion models ⋮ Parametric estimation from approximate data: non-Gaussian diffusions ⋮ Nonparametric estimation for stochastic differential equations with random effects ⋮ Non parametric estimation for fractional diffusion processes with random effects ⋮ Nonparametric estimation in a mixed-effect Ornstein-Uhlenbeck model ⋮ Maximum likelihood estimation of stochastic differential equations with random effects driven by fractional Brownian motion ⋮ Nonparametric estimation for i.i.d. paths of fractional SDE ⋮ Nonparametric drift estimation for i.i.d. paths of stochastic differential equations ⋮ Maximum Likelihood Estimation for Stochastic Differential Equations with Random Effects ⋮ Estimation of population parameters in stochastic differential equations with random effects in the diffusion coefficient ⋮ On classical and Bayesian asymptotics in stochastic differential equations with random effects having mixture normal distributions ⋮ Particle methods for stochastic differential equation mixed effects models ⋮ Stability of a class of hybrid neutral stochastic differential equations with unbounded delay ⋮ Parametric inference for small variance and long time horizon McKean-Vlasov diffusion models ⋮ On classical and Bayesian asymptotics in state space stochastic differential equations ⋮ Mixtures of stochastic differential equations with random effects: application to data clustering
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