{"product_id":"9780387908090","title":"Lecture Notes in Statistics: From Parametric to Non-Parametric, Using Bayesian or Non-Bayesian Approaches","description":"\u003ch1\u003eLecture Notes in Statistics: From Parametric to Non-Parametric, Using Bayesian or Non-Bayesian Approaches\u003c\/h1\u003e \u003ch2\u003eFlorens, J.P.; Mouchart, M.; Raoult, J.P.; Simar, L.; Smith, A.F.M.\u003c\/h2\u003e \u003cp\u003eDuring 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) ~~~£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.\u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 1983-01-24\u003c\/p\u003e \u003cp\u003eFormat: Paperback\u003c\/p\u003e \u003cp\u003eISBN-13: 9780387908090\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-1-4612-5503-1\u003c\/p\u003e \u003cp\u003eDimensions: 235cm x155cm\u003c\/p\u003e \u003cp\u003ePages: 204\u003c\/p\u003e ","brand":"Springer New York","offers":[{"title":"Default Title","offer_id":44450503065740,"sku":"9780387908090","price":49.49,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9780387908090.jpg?v=1775730126","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9780387908090","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}