| Specifying Statistical Models: From Parametric to Non-Parametric, Using Bayesian or Non-Bayesian Approaches Softcover Repri Edition Contributor(s): Florens, J. P. (Editor), Mouchart, M. (Editor), Raoult, J. P. (Editor) |
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ISBN: 0387908099 ISBN-13: 9780387908090 Publisher: Springer OUR PRICE: $52.24 Product Type: Paperback - Other Formats Published: January 1983 |
| Additional Information |
| BISAC Categories: - Mathematics | Probability & Statistics - General - Mathematics | Applied |
| Dewey: 519.5 |
| LCCN: 82019314 |
| Series: Grundlehren Der Mathematischen Wissenschaften (Springer Hardcover) |
| Physical Information: 0.46" H x 6.14" W x 9.21" (0.69 lbs) 204 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |