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

Language: English

Published by Springer, Berlin, Springer Nature Switzerland, Springer, 2025

3031956370 / 9783031956379

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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.

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This item is printed on demand - it takes 3-4 days longer - Neuware -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 observation of the ergodic stationary solution, here the estimation framework which is part of functional data analysis involves multiple copies of the (non-stationary) solution observed over a short-time interval. Two kinds of nonparametric estimators are investigated for SDE models, first presented in the regression framework: the projection least squares estimator and the Nadaraya-Watson estimator. Adaptive procedures are provided for possible applications in statistical learning. Primarily intended for researchers in statistical inference for stochastic processes who are interested in the copies-based observation scheme, the book will also be useful for graduate and PhD students in probability and statistics, thanks to its multiple reminders of the requisite theory, especially the chapter on nonparametric regression. 184 pp. Englisch.…

Seller Inventory # 9783031956379

Title
From Nonparametric Regression to Statistical Inference for Non-Ergodic Diffusion Processes
Author
Nicolas Marie
Publisher
Springer, Berlin, Springer Nature Switzerland, Springer
Publication year
2025
Condition
Neu
Binding
Buch
Language
English
ISBN 10
3031956370
ISBN 13
9783031956379
Dimensions
235x155x35 mm

BuchWeltWeit Ludwig Meier e.K.

Bergisch Gladbach, Germany

5-star seller

AbeBooks seller since January 11, 2012

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BuchWeltWeit Ludwig Meier e.K.

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