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 Doubly stochastic Poisson process Monotone piecewise cubic interpolation Functional principal component analysis Functional data analysis 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. 2022-02-24T12:54:41Z 2022-02-24T12:54:41Z 2006-06-20 info:eu-repo/semantics/article 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 http://hdl.handle.net/10481/73003 https://doi.org/10.1016/j.csda.2005.04.015 eng http://creativecommons.org/licenses/by-nd/3.0/es/ info:eu-repo/semantics/embargoedAccess Atribución-SinDerivadas 3.0 España Elsevier