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Specifying Statistical Models: From Parametric to Non-Parametric, Using Bayesian or Non-Bayesian Approaches

by J. P. Florens
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Current price ₹3,639.00
Original price ₹5,597.00
Original price ₹5,597.00
Original price ₹5,597.00
(-35%)
₹3,639.00
Current price ₹3,639.00

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Book cover type: Paperback
  • ISBN13: 9780387908090
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Publication Date:
  • Pages: 204
  • Original Price: EUR 49.99
  • Language: English
  • Edition: Softcover Repri
  • Item Weight: 339 grams
  • BISAC Subject(s): Probability & Statistics / General and Applied

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) 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.

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