Robust Statistics

Huber, Peter J.

ISBN 10: 0471650722 / ISBN 13: 9780471650720

Editore: John Wiley & Sons, 2004

308 Seiten Zustand: Einband etwas berieben, Schnitt mit kleinem Fleck // Englische Ausgabe. Wiley Series in Probability and Stochastics The traditional setting of statistical inference involves finite or known spaces and subjects. During the past few decades, a theory has been developed that allows the sample space to be abstract or unknown. More recently, mathematical techniques-especially the method of sieves-have been constructed to enable inferences to be made in abstract parameter spaces. This work began with the author's 1950 monograph on inference in stochastic processes (for general sample space) and with the sieve methodology (for general parameter space) This paperback reprint of a Wiley bestseller studies both of these cases and represents the first comprehensive treatment of the subject. /// Versand gratis Innerhalb Deutschlands - Portofrei in Deutschland- ab 20 Euro mit Post ID - Gratisversand deutschlandweit innerhalb Deutschlands gratis Versand -Versandkostenfrei innerhalb Deutschlands /// Sprache: Englisch Gewicht in Gramm: 408 23,0 x 15,5 cm, Softcover/Paperback. Codice articolo 353662

Riassunto:

The first systematic, book-length treatment of the subject. Begins with a general introduction and the formal mathematical background behind qualitative and quantitative robustness. Stresses concepts. Provides selected numerical algorithms for computing robust estimates, as well as convergence proofs. Tables contain quantitative robustness information for a variety of estimates.

Informazioni sull'autore: Peter J. Huber was formerly a Professor of Statistics at Harvard University and ETH Zurich. Dr. Huber received his Ph.D. in Mathematics from ETH Zurich in 1961.

Dati bibliografici

Titolo: Robust Statistics
Casa editrice: John Wiley & Sons
Data di pubblicazione: 2004
Legatura: Brossura
Condizione: Sehr gut