Sinopsis
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.
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Acerca del autor
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.
De la contraportada
WILEY-INTERSCIENCE PAPERBACK SERIES
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.
From the Reviews of Robust Statistics
"Robust Statistics is required reading for anyone involved in robustness research or desiring to start a research program in robustness."
?Journal of the American Statistical Association
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Robust Statistics (Wiley Series in Probability and Statistics)
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Wiley-Interscience, 2003
ISBN 10: 0471650722
ISBN 13: 9780471650720
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Paperback. Condición: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less. Nº de ref. del artículo: G0471650722I3N00
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Robust Statistics (Wiley Series in Probability and Statistics)
Publicado por
Wiley-Interscience, 2004
ISBN 10: 0471650722
ISBN 13: 9780471650720
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Soft cover. Condición: New. 1st Edition. IX+308 pages. Wiley-Interscience, 2004. New Soft cover. 9.0"x6.0"x0.75", be45. Nº de ref. del artículo: ABE-1734475429615
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Robust Statistics
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John Wiley & Sons, 2004
ISBN 10: 0471650722
ISBN 13: 9780471650720
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Condición: Sehr gut. 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. Nº de ref. del artículo: 353662
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