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WCE
2007

Recursive Linear Estimation for Doubly Stochastic Poisson Processes

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Recursive Linear Estimation for Doubly Stochastic Poisson Processes
Abstract— The problem of estimating the intensity process of a doubly stochastic Poisson process is analyzed. Using covariance information, a recursive linear minimum mean-square error estimate is designed. Moreover, an efficient procedure for the computation of its associated error covariance is shown. The proposed solution becomes an alternative approach to the Kalman filter which is applicable under the only structural assumption that the intensity process to be estimated has a finite-dimensional covariance function.
Rosa M. Fernández-Alcalá, Jesú
Added 07 Nov 2010
Updated 07 Nov 2010
Type Conference
Year 2007
Where WCE
Authors Rosa M. Fernández-Alcalá, Jesús Navarro-Moreno, Juan Carlos Ruiz-Molina, Antonia Oya
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