大阪大学　数理・データ科学教育研究センター
Center for Mathematical Modeling and Data Science,Osaka University

Statistical estimation for stochastic differential equations from discrete time observations

Michael Sørensen (University of Copenhagen)

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4. Statistical estimation for stochastic differential equations from discrete time observations

大阪大学 数理・データ科学セミナー データ科学セミナーシリーズ 第49回

Statistical estimation for stochastic differential equations from discrete time observations

Michael Sørensen (University of Copenhagen)

Statistical inference for discrete time data from a stochastic differential equation model is considered with focus on estimating function techniques. The likelihood function is only very rarely explicitly known, but estimating functions provide a feasible alternative. We discuss various relations between likelihood inference and estimating function inference and give a brief review of the theory of estimating functions for Markov processes including asymptotic theory and some implementation issues. Three types of asymptotics is presented: ergodic low frequency asymptotics and high frequency asymptotics with bounded as well as infinite time horizon. Also inference for jump diffusions is considered. If time permits, we will discuss the problems caused by variation of different time scales.

本発表はJST CREST JPMJCR14D7によってサポートされています．