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[null,"1.","Record Nr.",null,"UNINA9910155297503321"]
[null,null,"Autore",null,"Cherubini Umberto"]
[null,null,"Titolo",null,"Convolution Copula Econometrics / / by Umberto Cherubini, Fabio Gobbi, Sabrina Mulinacci"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016"]
[null,null,"Edizione",null,"[1st ed. 2016.]"]
[null,null,"Descrizione fisica",null,"1 online resource (X, 90 p. 31 illus., 30 illus. in color.)"]
[null,null,"Collana",null,"SpringerBriefs in Statistics, , 2191-5458"]
[null,null,"Disciplina",null,"332.015195"]
[null,null,"Soggetti",null,"Statistics"]
[{"$nulls":4},"Probabilities"]
[{"$nulls":4},"Econometrics"]
[{"$nulls":4},"Mathematics"]
[{"$nulls":4},"Statistics in Business, Management, Economics, Finance, Insurance"]
[{"$nulls":4},"Probability Theory"]
[{"$nulls":4},"Statistical Theory and Methods"]
[{"$nulls":4},"Applications of Mathematics"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references at the end of each chapters."]
[null,null,"Nota di contenuto",null,"Preface -- The Dynamics of Economic Variables -- Estimation of Copula Models -- Copulas and Estimation of Markov Processes -- Copula-based Markov Processes: Estimation, Mixing Properties and Long-term Behavior -- Convolution-based Processes -- Application to Interest Rates. ."]
[null,null,null,"Sommario/riassunto","This book presents a novel approach to time series econometrics, which studies the behavior of nonlinear stochastic processes. This approach allows for an arbitrary dependence structure in the increments and provides a generalization with respect to the standard linear independent increments assumption of classical time series models. The book offers a solution to the problem of a general semiparametric approach, which is given by a concept called C-convolution (convolution of dependent variables), and the corresponding theory of convolution-based copulas. Intended for econometrics and statistics scholars with a special interest in time series analysis and copula functions (or other nonparametric approaches), the book is also useful for doctoral students with a basic knowledge of copula functions wanting to learn about the latest "]
[{"$nulls":4},"research developments in the field."]