Modelling the mean of a doubly stochastic Poisson process by functional data analysis

Rodríguez Bouzas, Paula; Valderrama Bonnet, Mariano José; Aguilera Del Pino, Ana María; Ruiz-Fuentes, Nuria

doi:https://doi.org/10.1016/j.csda.2005.04.015

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Identificadores

URI: http://hdl.handle.net/10481/73003

DOI: https://doi.org/10.1016/j.csda.2005.04.015

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Editorial

Elsevier

Materia

Doubly stochastic Poisson process

Monotone piecewise cubic interpolation

Functional principal component analysis

Functional data analysis

Fecha

2006-06-20

Referencia bibliográfica

P.R. Bouzas, M.J. Valderrama, A.M. Aguilera, N. Ruiz-Fuentes, Modelling the mean of a doubly stochastic Poisson process by functional data analysis, Computational Statistics & Data Analysis, Volume 50, Issue 10, 2006, Pages 2655-2667, ISSN 0167-9473, https://doi.org/10.1016/j.csda.2005.04.015

Patrocinador

Projects MTM2004-05992 of Dirección General de Investigación, and MTM2004-04230 of Plan Nacional de I+D+I, Ministerio de Ciencia y Tecnología jointly by the FEDER

Resumen

A new procedure for estimating the mean process of a doubly stochastic Poisson process is introduced. The proposed estimation is based on monotone piecewise cubic interpolation of the sample paths of the mean. In order to estimate the continuous time structure of the mean process functional principal component analysis is applied to its trajectories previously adapted to their functional form. A validation of the estimation method is presented by means of some simulations.

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