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Modelling function-valued stochastic processes, with applications to fertility dynamics
dc.contributor.author | Chen, Kehui |
dc.contributor.author | Delicado Useros, Pedro Francisco |
dc.contributor.author | Müller, Hans-Georg |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa |
dc.date.accessioned | 2019-01-14T09:21:43Z |
dc.date.available | 2019-01-14T09:21:43Z |
dc.date.issued | 2017 |
dc.identifier.citation | Chen, K., Delicado, P., Müller, H-G. Modelling function-valued stochastic processes, with applications to fertility dynamics. "Journal of the Royal Statistical Society. Series B, statistical methodology", 2017, vol. 79, núm. 1, p. 177-196. |
dc.identifier.issn | 1369-7412 |
dc.identifier.uri | http://hdl.handle.net/2117/126653 |
dc.description.abstract | We introduce a simple and interpretable model for functional data analysis for situations where the observations at each location are functional rather than scalar. This new approach is based on a tensor product representation of the function-valued process and utilizes eigenfunctions of marginal kernels. The resulting marginal principal components and product principal components are shown to have nice properties. Given a sample of independent realizations of the underlying function-valued stochastic process, we propose straightforward fitting methods to obtain the components of this model and to establish asymptotic consistency and rates of convergence for the estimates proposed. The methods are illustrated by modelling the dynamics of annual fertility profile functions for 17 countries. This analysis demonstrates that the approach proposed leads to insightful interpretations of the model components and interesting conclusions. |
dc.format.extent | 20 p. |
dc.language.iso | eng |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Spain |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa |
dc.subject.other | Asymptotics |
dc.subject.other | Demography |
dc.subject.other | Functional data analysis |
dc.subject.other | Marginal kernel |
dc.subject.other | Product principal component analysis |
dc.subject.other | Tensor product representation |
dc.title | Modelling function-valued stochastic processes, with applications to fertility dynamics |
dc.type | Article |
dc.contributor.group | Universitat Politècnica de Catalunya. ADBD - Anàlisi de Dades Complexes per a les Decisions Empresarials |
dc.identifier.doi | 10.1111/rssb.12160 |
dc.description.peerreviewed | Peer Reviewed |
dc.subject.ams | Classificació AMS::90 Operations research, mathematical programming |
dc.relation.publisherversion | http://onlinelibrary.wiley.com/doi/10.1111/rssb.12160/abstract |
dc.rights.access | Open Access |
local.identifier.drac | 17555734 |
dc.description.version | Postprint (author's final draft) |
dc.relation.projectid | info:eu-repo/grantAgreement/MINECO//MTM2013-43992-R/ES/MUESTRAS DE MUESTRAS: APLICACIONES RELEVANTES DE LA ESTADISTICA EN LA ECONOMIA Y LA SOCIEDAD DIGITAL/ |
local.citation.author | Chen, K.; Delicado, P.; Müller, H-G. |
local.citation.publicationName | Journal of the Royal Statistical Society. Series B, statistical methodology |
local.citation.volume | 79 |
local.citation.number | 1 |
local.citation.startingPage | 177 |
local.citation.endingPage | 196 |
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