Show simple item record

dc.contributor.authorRodríguez Bouzas, Paula 
dc.contributor.authorValderrama Bonnet, Mariano José 
dc.contributor.authorAguilera Del Pino, Ana María 
dc.contributor.authorRuiz-Fuentes, Nuria
dc.identifier.citationP.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,
dc.description.abstractA 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.es_ES
dc.description.sponsorshipProjects 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 FEDERes_ES
dc.rightsAtribución-SinDerivadas 3.0 España*
dc.subjectDoubly stochastic Poisson processes_ES
dc.subjectMonotone piecewise cubic interpolationes_ES
dc.subjectFunctional principal component analysises_ES
dc.subjectFunctional data analysises_ES
dc.titleModelling the mean of a doubly stochastic Poisson process by functional data analysises_ES

Files in this item


This item appears in the following Collection(s)

Show simple item record

Atribución-SinDerivadas 3.0 España
Except where otherwise noted, this item's license is described as Atribución-SinDerivadas 3.0 España