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From Nonparametric Regression to Statistical Inference for Non-Ergodic Diffusion Processes

This book is about copies-based nonparametric estimation of the drift function in stochastic differential equations (SDEs) driven by Brownian motion, a jump process, or fractional Brownian motion. While the estimators of the drift function in SDEs are classically computed from one long-time observat...

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Bibliográfalaš dieđut
Váldodahkki: Marie, Nicolas (Dahkki)
Searvvušdahkki: SpringerLink (Online service)
Materiálatiipa: Elektrovnnalaš E-girji
Giella:eaŋgalasgiella
Almmustuhtton: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Preanttus:1st ed. 2025.
Ráidu:Frontiers in Probability and the Statistical Sciences,
Fáttát:
Stochastic models.
Nonparametric statistics.
Stochastic processes.
Stochastic Modelling in Statistics.
Non-parametric Inference.
Stochastic Processes.
Liŋkkat:https://doi.org/10.1007/978-3-031-95638-6
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Sisdoallologahallan:
  • Introduction
  • Nonparametric regression: a detailed reminder
  • The projection least squares estimator of the drift function
  • Going further with the projection least squares method: diffusions with jumps and fractional diffusions
  • The Nadaraya-Watson estimator of the drift function.

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