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L vy Matters IV [electronic resource] : Estimation for Discretely Observed L vy Processes / by Denis Belomestny, Fabienne Comte, Valentine Genon-Catalot, Hiroki Masuda, Markus Rei .

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dc.contributor.author Belomestny, Denis. author.
dc.contributor.author Comte, Fabienne. author.
dc.contributor.author Genon-Catalot, Valentine. author.
dc.contributor.author Masuda, Hiroki. author.
dc.contributor.author Rei , Markus. author.
dc.contributor.author SpringerLink (Online service)
dc.date.accessioned 2017-11-30T19:38:28Z
dc.date.available 2017-11-30T19:38:28Z
dc.date.created 2015.
dc.date.issued 2015
dc.identifier.isbn 9783319123738
dc.identifier.uri http://dspace.conacyt.gov.py/xmlui/handle/123456789/12236
dc.description XV, 286 p. 21 illus., 14 illus. in color.
dc.description.abstract The aim of this volume is to provide an extensive account of the most recent advances in statistics for discretely observed L vy processes. These days, statistics for stochastic processes is a lively topic, driven by the needs of various fields of application, such as finance, the biosciences, and telecommunication. The three chapters of this volume are completely dedicated to the estimation of L vy processes, and are written by experts in the field. The first chapter by Denis Belomestny and Markus Rei treats the low frequency situation, and estimation methods are based on the empirical characteristic function. The second chapter by Fabienne Comte and Valery Genon-Catalon is dedicated to non-parametric estimation mainly covering the high-frequency data case. A distinctive feature of this part is the construction of adaptive estimators, based on deconvolution or projection or kernel methods. The last chapter by Hiroki Masuda considers the parametric situation. The chapters cover the main aspects of the estimation of discretely observed L vy processes, when the observation scheme is regular, from an up-to-date viewpoint.
dc.description.tableofcontents Estimation and calibration of L vy models via Fourier methods -- Adaptive Estimation for L vy processes -- Parametric estimation of L vy processes.
dc.language eng
dc.publisher Cham : Springer International Publishing : Imprint: Springer, 2015.
dc.relation.ispartofseries Springer eBooks
dc.relation.ispartofseries Lecture Notes in Mathematics, 0075-8434 ; 2128
dc.relation.ispartofseries Lecture Notes in Mathematics, 0075-8434 ; 2128
dc.relation.uri http://cicco.idm.oclc.org/login?url=http://dx.doi.org/10.1007/978-3-319-12373-8
dc.subject Mathematics.
dc.subject Probabilities.
dc.subject Statistics.
dc.subject Economic theory.
dc.subject Mathematics.
dc.subject Probability Theory and Stochastic Processes.
dc.subject Statistics for Business/Economics/Mathematical Finance/Insurance.
dc.subject Economic Theory/Quantitative Economics/Mathematical Methods.
dc.subject.ddc 519.2 23
dc.subject.lcc QA273.A1-274.9
dc.subject.lcc QA274-274.9
dc.subject.other Mathematics and Statistics (Springer-11649)
dc.title L vy Matters IV [electronic resource] : Estimation for Discretely Observed L vy Processes / by Denis Belomestny, Fabienne Comte, Valentine Genon-Catalot, Hiroki Masuda, Markus Rei .
dc.type text
dc.identifier.doi 10.1007/978-3-319-12373-8
dc.identifier.bib 978-3-319-12373-8
dc.format.rdamedia computer
dc.format.rdacarrier online resource
dc.format.rda text file PDF


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