Parametric estimation of stochastic differential equations via online gradient descent

Author:

Nakakita ShogoORCID

Abstract

AbstractWe propose an online parametric estimation method of stochastic differential equations with discrete observations and misspecified modelling based on online gradient descent. Our study provides uniform upper bounds for the risks of the estimators over a family of stochastic differential equations. Theoretical guarantees for the estimation of stochastic differential equations with discrete observations by online gradient descent are novel to our best knowledge.

Funder

Japan Society for the Promotion of Science

Japan Science and Technology Corporation

The University of Tokyo

Publisher

Springer Science and Business Media LLC

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