statistical models parametric non parametric (7 résultats)

Broschiert. Etat : Gut. 204 Seiten; Das hier angebotene Buch stammt aus einer teilaufgelösten wissenschaftlichen Bibliothek und trägt die entsprechenden Kennzeichnungen (Rückenschild, Instituts-Stempel.); Schnitt und Einband sind etwas staubschmutzig; der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. Text in ENGLISCHER Sprache! Sprache: Englisch Gewicht in Gramm: 350.

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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - During the last decades. the evolution of theoretical statistics has been marked by a considerable expansion of the number of mathematically and computationaly trac table models. Faced with this inflation. applied statisticians feel more and more un comfortable: they are often hesitant about their traditional (typically parametric) assumptions. such as normal and i. i. d . - ARMA forms for time-series. etc . - but are at the same time afraid of venturing into the jungle of less familiar models. The prob lem of the justification for taking up one model rather than another one is thus a crucial one. and can take different forms. (a) ~~~ Pds. ifi~~~iQ~ : Do observations suggest the use of a different model from the one initially proposed (e. g. one which takes account of outliers). or do they render plau sible a choice from among different proposed models (e. g. fixing or not the value of a certai n parameter) (b) tlQ~~L~~l!rQ1!iIMHQ~ : How is it possible to compute a 'distance' between a given model and a less (or more) sophisticated one. and what is the technical meaning of such a 'distance' (c) BQe~~~~~~ : To what extent do the qualities of a procedure. well adapted to a 'small' model. deteriorate when this model is replaced by a more general one This question can be considered not only. as usual. in a parametric framework (contamina tion) or in the extension from parametriC to non parametric models but also.

Taschenbuch. Etat : Neu. Specifying Statistical Models | From Parametric to Non-Parametric, Using Bayesian or Non-Bayesian Approaches | J. P. Florens (u. a.) | Taschenbuch | Lecture Notes in Statistics | xii | Englisch | 1983 | Springer | EAN 9780387908090 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

paperback. Etat : New. Pub Date: 2015-01-01 Pages: 181 Language: Chinese Publisher: Science Press. a non-parametric statistical analysis of continuous-time financial models system introduces a non-parametric statistical inference method and its application of continuous time financial models. including a dimensional diffusion model. time-varying diffusion models. non-parametric estimation and model specification test questions and stochastic volatility model for multi-dimensional diffusion model. and briefly descri.