First practical treatment of small-sample asymptotics, enabling practitioners to apply new methods with confidence.
"synopsis" may belong to another edition of this title.
Alessandra Brazzale is a Researcher in Statistics at the Institute of Biomedical Engineering, Italian National Research Council, Padova.
Anthony Davison is a Professor of Statistics at the Ecole Polytechnique Fédérale de Lausanne.
Nancy Reid is a University Professor of Statistics at the University of Toronto.
"About this title" may belong to another edition of this title.
Seller: Shakespeare Book House, Rockford, IL, U.S.A.
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Seller: Anybook.com, Lincoln, United Kingdom
Condition: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Library sticker on front cover. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,650grams, ISBN:9780521847032. Seller Inventory # 5568943
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Seller: GreatBookPrices, Columbia, MD, U.S.A.
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Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condition: new. Hardcover. In fields such as biology, medical sciences, sociology, and economics researchers often face the situation where the number of available observations, or the amount of available information, is sufficiently small that approximations based on the normal distribution may be unreliable. Theoretical work over the last quarter-century has led to new likelihood-based methods that lead to very accurate approximations in finite samples, but this work has had limited impact on statistical practice. This book illustrates by means of realistic examples and case studies how to use the new theory, and investigates how and when it makes a difference to the resulting inference. The treatment is oriented towards practice and comes with code in the R language (available from the web) which enables the methods to be applied in a range of situations of interest to practitioners. The analysis includes some comparisons of higher order likelihood inference with bootstrap or Bayesian methods. New likelihood-based methods now allow very accurate approximations in finite samples and this book illustrates with realistic examples and case studies how to use the new theory. The treatment is oriented towards practice and is accompanied by code in the R language, enabling practitioners to apply the methods with ease. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780521847032
Seller: California Books, Miami, FL, U.S.A.
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Seller: Revaluation Books, Exeter, United Kingdom
Hardcover. Condition: Brand New. illustrated edition. 248 pages. 10.00x6.50x0.50 inches. In Stock. This item is printed on demand. Seller Inventory # __0521847036
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Seller: GreatBookPrices, Columbia, MD, U.S.A.
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Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days. Seller Inventory # C9780521847032
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Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: As New. Unread book in perfect condition. Seller Inventory # 4926165
Quantity: Over 20 available