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Publicado por Oxford University Press, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
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Idioma: Inglés
Publicado por Oxford University Press, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
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Publicado por Oxford University Press, 2006
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Publicado por Oxford University Press, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
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Idioma: Inglés
Publicado por Oxford University Press, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
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Idioma: Inglés
Publicado por Oxford University Press, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
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Añadir al carritoCondición: New. Statistical tools are changing the ways in which scientists analyze and interpret data and models. This book provides consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale. Editor(s): Clark, James S.; Gelfand, Alan E. Num Pages: 216 pages, 73 line drawings, tables. BIC Classification: PBT; PBW; PSAF; UFM. Category: (P) Professional & Vocational. Dimension: 246 x 188 x 12. Weight in Grams: 410. . 2006. Illustrated. paperback. . . . .
Idioma: Inglés
Publicado por Oxford University Press, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
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Publicado por Oxford University Press, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
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Añadir al carritoCondición: New. Statistical tools are changing the ways in which scientists analyze and interpret data and models. This book provides consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale. Editor(s): Clark, James S.; Gelfand, Alan E. Num Pages: 216 pages, 73 line drawings, tables. BIC Classification: PBT; PBW; PSAF; UFM. Category: (P) Professional & Vocational. Dimension: 246 x 188 x 12. Weight in Grams: 410. . 2006. Illustrated. paperback. . . . . Books ship from the US and Ireland.
Idioma: Inglés
Publicado por Oxford University Press, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
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Idioma: Inglés
Publicado por Oxford University Press, Oxford, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
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Añadir al carritoPaperback. Condición: new. Paperback. New Statistical tools are changing the wau in which scientists analyze and interpret data and models. Many of these are emerging as a result of the wide availability of inexpensive, high speed computational power. In particular, hierarchical Bayes and Markov Chain Monte Carlo methods for analysis provide constant framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale. Nowhere arethese methods more promising than in the environmental sciences. Models have developed rapidly, and there is now a requirment for a clear exposition of the methodology through to application for arange of environmental challenges. Statistical tools are changing the ways in which scientists analyze and interpret data and models. This book provides consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Idioma: Inglés
Publicado por Oxford University Press, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
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Idioma: Inglés
Publicado por Oxford University Press, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
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Añadir al carritoPAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Idioma: Inglés
Publicado por Oxford University Press, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
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Idioma: Inglés
Publicado por Oxford University Press, Oxford, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
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Añadir al carritoPaperback. Condición: new. Paperback. New Statistical tools are changing the wau in which scientists analyze and interpret data and models. Many of these are emerging as a result of the wide availability of inexpensive, high speed computational power. In particular, hierarchical Bayes and Markov Chain Monte Carlo methods for analysis provide constant framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale. Nowhere arethese methods more promising than in the environmental sciences. Models have developed rapidly, and there is now a requirment for a clear exposition of the methodology through to application for arange of environmental challenges. Statistical tools are changing the ways in which scientists analyze and interpret data and models. This book provides consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Idioma: Inglés
Publicado por Oxford University Press OUP, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
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Añadir al carritoCondición: New. Print on Demand pp. 216.
Idioma: Inglés
Publicado por Oxford University Press, Oxford, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
Librería: CitiRetail, Stevenage, Reino Unido
EUR 108,52
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Añadir al carritoPaperback. Condición: new. Paperback. New Statistical tools are changing the wau in which scientists analyze and interpret data and models. Many of these are emerging as a result of the wide availability of inexpensive, high speed computational power. In particular, hierarchical Bayes and Markov Chain Monte Carlo methods for analysis provide constant framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale. Nowhere arethese methods more promising than in the environmental sciences. Models have developed rapidly, and there is now a requirment for a clear exposition of the methodology through to application for arange of environmental challenges. Statistical tools are changing the ways in which scientists analyze and interpret data and models. This book provides consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Idioma: Inglés
Publicado por Oxford University Press, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
Librería: moluna, Greven, Alemania
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Statistical tools are changing the ways in which scientists analyze and interpret data and models. This book provides consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses de.
Idioma: Inglés
Publicado por Oxford University Press, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
Librería: Majestic Books, Hounslow, Reino Unido
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Añadir al carritoCondición: New. Print on Demand pp. 216 73 Figures, 50:B&W 7.44 x 9.69 in or 246 x 189 mm (Crown 4vo) Perfect Bound on White w/Gloss Lam.
Idioma: Inglés
Publicado por Oxford University Press, 2006
ISBN 10: 019856967X ISBN 13: 9780198569671
Librería: Biblios, Frankfurt am main, HESSE, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. Hierarchical Modelling for the Environmental Sciences | Statistical Methods and Applications | James S. Clark (u. a.) | Taschenbuch | Kartoniert / Broschiert | Englisch | 2006 | OUP Oxford | EAN 9780198569671 | Verantwortliche Person für die EU: Deutsche Bibelgesellschaft, Postfach:81 03 40, 70567 Stuttgart, vertrieb[at]dbg[dot]de | Anbieter: preigu Print on Demand.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - New Statistical tools are changing the wau in which scientists analyze and interpret data and models. Many of these are emerging as a result of the wide availability of inexpensive, high speed computational power. In particular, hierarchical Bayes and Markov Chain Monte Carlo methods for analysis provide constant framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale. Nowhere are these methods more promising than in the environmental sciences. Models have developed rapidly, and there is now a requirment for a clear exposition of the methodology through to application for a range of environmental challenges.