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Conference papers
A bayesian lower bound for parameter estimation of Poisson data including multiple changes
Abstract : This paper derives lower bounds for the mean square errors of parameter estimators in the case of Poisson distributed data subjected to multiple abrupt changes. Since both change locations (discrete parameters) and parameters of the Poisson distribution (continuous parameters) are unknown, it is appropriate to consider a mixed Cramér-Rao/Weiss-Weinstein bound for which we derive closed-form expressions and illustrate its tightness by numerical simulations.
Cited literature [27 references]
https://hal-centralesupelec.archives-ouvertes.fr/hal-01525499
Contributor : Alexandre Renaux <>
Submitted on : Sunday, May 21, 2017 - 12:58:06 PM
Last modification on : Wednesday, April 8, 2020 - 4:02:59 PM
Document(s) archivé(s) le : Wednesday, August 23, 2017 - 10:51:46 AM
Contributor : Alexandre Renaux <>
Submitted on : Sunday, May 21, 2017 - 12:58:06 PM
Last modification on : Wednesday, April 8, 2020 - 4:02:59 PM
Document(s) archivé(s) le : Wednesday, August 23, 2017 - 10:51:46 AM
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