Stein estimation of Poisson process intensities

Nicolas Privault; Anthony Réveillac

doi:10.1007/s11203-007-9018-8

Stein estimation of Poisson process intensities

Nicolas Privault
, Anthony Réveillac

Department of Mathematics

Research output: Journal Publications and Reviews › RGC 22 - Publication in policy or professional journal

8 Citations (Scopus)

Abstract

We construct superefficient estimators of Stein type for the intensity parameter λ > 0 of a Poisson process, using integration by parts and superharmonic functionals on the Poisson space. © 2007 Springer Science+Business Media B.V.

Original language	English
Pages (from-to)	37-53
Journal	Statistical Inference for Stochastic Processes
Volume	12
Issue number	1
DOIs	https://doi.org/10.1007/s11203-007-9018-8
Publication status	Published - Feb 2009

Research Keywords

Intensity estimation
Malliavin calculus
Poisson process
Stein estimation

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title = "Stein estimation of Poisson process intensities",

abstract = "We construct superefficient estimators of Stein type for the intensity parameter λ > 0 of a Poisson process, using integration by parts and superharmonic functionals on the Poisson space. {\textcopyright} 2007 Springer Science+Business Media B.V.",

keywords = "Intensity estimation, Malliavin calculus, Poisson process, Stein estimation",

author = "Nicolas Privault and Anthony R{\'e}veillac",

year = "2009",

month = feb,

doi = "10.1007/s11203-007-9018-8",

language = "English",

volume = "12",

pages = "37--53",

journal = "Statistical Inference for Stochastic Processes",

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TY - JOUR

T1 - Stein estimation of Poisson process intensities

AU - Privault, Nicolas

AU - Réveillac, Anthony

PY - 2009/2

Y1 - 2009/2

N2 - We construct superefficient estimators of Stein type for the intensity parameter λ > 0 of a Poisson process, using integration by parts and superharmonic functionals on the Poisson space. © 2007 Springer Science+Business Media B.V.

AB - We construct superefficient estimators of Stein type for the intensity parameter λ > 0 of a Poisson process, using integration by parts and superharmonic functionals on the Poisson space. © 2007 Springer Science+Business Media B.V.

KW - Intensity estimation

KW - Malliavin calculus

KW - Poisson process

KW - Stein estimation

UR - https://www.scopus.com/pages/publications/61849143341

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-61849143341&origin=recordpage

U2 - 10.1007/s11203-007-9018-8

DO - 10.1007/s11203-007-9018-8

M3 - RGC 22 - Publication in policy or professional journal

SN - 1387-0874

VL - 12

SP - 37

EP - 53

JO - Statistical Inference for Stochastic Processes

JF - Statistical Inference for Stochastic Processes

IS - 1

ER -

Stein estimation of Poisson process intensities

Abstract

Research Keywords

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