Name: specifying statistical models: from parametric to non-parametric, using bayesian or non-bayesian approaches (en Inglés)
Price: 65740.00 CLP
Availability: InStock
Author: Florens, J. P. ; Mouchart, M. ; Raoult, J. P.
ISBN: 9780387908090

portada specifying statistical models: from parametric to non-parametric, using bayesian or non-bayesian approaches (en Inglés)

specifying statistical models: from parametric to non-parametric, using bayesian or non-bayesian approaches (en Inglés)

Formato

Libro Físico

Ilustrado por

Editorial

Autor

Florens, J. P. ; Mouchart, M. ; Raoult, J. P.

Año

1983

Idioma

Inglés

N° páginas

204

Encuadernación

Tapa Blanda

Dimensiones

23.4 x 15.6 x 1.2 cm

Peso

0.31 kg.

ISBN

0387908099

ISBN13

9780387908090

Categorías

Probabilidad y estadística
Matemáticas aplicadas

specifying statistical models: from parametric to non-parametric, using bayesian or non-bayesian approaches (en Inglés)

J. P. Florens (Ilustrado por) · M. Mouchart (Ilustrado por) · J. P. Raoult (Ilustrado por) · Springer · Tapa Blanda

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Reseña del libro "specifying statistical models: from parametric to non-parametric, using bayesian or non-bayesian approaches (en Inglés)"

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.