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Stochastic analysis on Gaussian space ap...

Privault, Nicolas...

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Stochastic analysis on Gaussian space applied to drift estimation by Privault, Nicolas ( Author )

Content Provider	Lemonjar Open Access
Publisher	Australian National University
Publication Date	31-07-2023
Summary	In this paper we consider the nonparametric functional estimation of the drift of Gaussian processes using Paley-Wiener and Karhunen-Lo\`eve expansions. We construct efficient estimators for the drift of such processes, and prove their minimaxity using Bayes estimators. We also construct superefficient estimators of Stein type for such drifts using the Malliavin integration by parts formula and stochastic analysis on Gaussian space, in which superharmonic functionals of the process paths play a particular role. Our results are illustrated by numerical simulations and extend the construction of James-Stein type estimators for Gaussian processes by Berger and Wolper.
ISBN	-
Item Type	Article
File Type	pdf
File Size	37.08 KB
Language	English
Subjects	-
Unlimited	MYR 0.01
Total read	-
URL	http://arxiv.org/abs/0805.2002

Citation

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AMA 11th EditionReferences

Privault, Nicolas. Stochastic analysis on Gaussian space applied to drift estimation. Australian National University. July 31, 2023. Accessed September 19, 2024. https://online.provdatabase.com/cite/3056

APA 7th EditionReferences

Privault, Nicolas. (2023). Stochastic analysis on Gaussian space applied to drift estimation. Australian National University. https://online.provdatabase.com/cite/3056

Chicago 17th EditionReferences

Privault, Nicolas. Stochastic analysis on Gaussian space applied to drift estimation. Australian National University. 2023. https://online.provdatabase.com/cite/3056

HarvardReferences

Privault, Nicolas. (2023). Stochastic analysis on Gaussian space applied to drift estimation. [Online]. Australian National University. Available from: https://online.provdatabase.com/cite/3056. (Accessed 19 September 2024).

Harvard AustraliaReferences

Privault, Nicolas, 2023, Stochastic analysis on Gaussian space applied to drift estimation, Australian National University, viewed 19 September 2024, <https://online.provdatabase.com/cite/3056>

MLA 9th EditionWorks Cited

Privault, Nicolas. Stochastic analysis on Gaussian space applied to drift estimation. Australian National University, 2023. PROV Database, https://online.provdatabase.com/cite/3056.

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