Librería: Anybook.com, Lincoln, Reino Unido
EUR 37,30
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Añadir al carritoCondición: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In fair condition, suitable as a study copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,450grams, ISBN:9780387944784.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 115,56
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Añadir al carritoCondición: New. In.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 133,83
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Añadir al carritoCondición: New. pp. 244.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 151,93
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Añadir al carritoPaperback. Condición: Brand New. 1st edition. 238 pages. 9.50x6.50x0.50 inches. In Stock.
Librería: Buchpark, Trebbin, Alemania
EUR 64,11
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Añadir al carritoCondición: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | INTRODUCTION 1) Introduction In 1979, Efron introduced the bootstrap method as a kind of universal tool to obtain approximation of the distribution of statistics. The now well known underlying idea is the following : consider a sample X of Xl ' n independent and identically distributed H.i.d.) random variables (r. v,'s) with unknown probability measure (p.m.) P . Assume we are interested in approximating the distribution of a statistical functional T(P ) the -1 nn empirical counterpart of the functional T(P) , where P n := n l:i=l aX. is 1 the empirical p.m. Since in some sense P is close to P when n is large, n ¿ ¿ LLd. from P and builds the empirical p.m. if one samples Xl ' . , Xm n n -1 mn ¿ ¿ P T(P ) conditionally on := mn l: i =1 a ¿ ' then the behaviour of P m n,m n n n X. 1 T(P ) should imitate that of when n and mn get large. n This idea has lead to considerable investigations to see when it is correct, and when it is not. When it is not, one looks if there is any way to adapt it.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 112,77
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - INTRODUCTION 1) Introduction In 1979, Efron introduced the bootstrap method as a kind of universal tool to obtain approximation of the distribution of statistics. The now well known underlying idea is the following : consider a sample X of Xl ' n independent and identically distributed H.i.d.) random variables (r. v,'s) with unknown probability measure (p.m.) P . Assume we are interested in approximating the distribution of a statistical functional T(P ) the -1 nn empirical counterpart of the functional T(P) , where P n := n l:i=l aX. is 1 the empirical p.m. Since in some sense P is close to P when n is large, n - - LLd. from P and builds the empirical p.m. if one samples Xl ' . , Xm n n -1 mn - - P T(P ) conditionally on := mn l: i =1 a - ' then the behaviour of P m n,m n n n X. 1 T(P ) should imitate that of when n and mn get large. n This idea has lead to considerable investigations to see when it is correct, and when it is not. When it is not, one looks if there is any way to adapt it.
Librería: Mispah books, Redhill, SURRE, Reino Unido
EUR 163,40
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Añadir al carritoPaperback. Condición: Like New. Like New. book.
Idioma: Inglés
Publicado por Springer New York, Springer New York Feb 1995, 1995
ISBN 10: 0387944788 ISBN 13: 9780387944784
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 106,99
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -INTRODUCTION 1) Introduction In 1979, Efron introduced the bootstrap method as a kind of universal tool to obtain approximation of the distribution of statistics. The now well known underlying idea is the following : consider a sample X of Xl ' n independent and identically distributed H.i.d.) random variables (r. v,'s) with unknown probability measure (p.m.) P . Assume we are interested in approximating the distribution of a statistical functional T(P ) the -1 nn empirical counterpart of the functional T(P) , where P n := n l:i=l aX. is 1 the empirical p.m. Since in some sense P is close to P when n is large, n - - LLd. from P and builds the empirical p.m. if one samples Xl ' . , Xm n n -1 mn - - P T(P ) conditionally on := mn l: i =1 a - ' then the behaviour of P m n,m n n n X. 1 T(P ) should imitate that of when n and mn get large. n This idea has lead to considerable investigations to see when it is correct, and when it is not. When it is not, one looks if there is any way to adapt it. 244 pp. Englisch.
Librería: moluna, Greven, Alemania
EUR 92,27
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. INTRODUCTION 1) Introduction In 1979, Efron introduced the bootstrap method as a kind of universal tool to obtain approximation of the distribution of statistics. The now well known underlying idea is the following : consider a sample X of Xl n independen.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 147,32
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. Print on Demand pp. 244 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 148,90
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. PRINT ON DEMAND pp. 244.
Idioma: Inglés
Publicado por Springer, Springer Feb 1995, 1995
ISBN 10: 0387944788 ISBN 13: 9780387944784
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 106,99
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -INTRODUCTION 1) Introduction In 1979, Efron introduced the bootstrap method as a kind of universal tool to obtain approximation of the distribution of statistics. The now well known underlying idea is the following : consider a sample X of Xl ' n independent and identically distributed H.i.d.) random variables (r. v,'s) with unknown probability measure (p.m.) P . Assume we are interested in approximating the distribution of a statistical functional T(P ) the -1 nn empirical counterpart of the functional T(P) , where P n := n l:i=l aX. is 1 the empirical p.m. Since in some sense P is close to P when n is large, n ¿ ¿ LLd. from P and builds the empirical p.m. if one samples Xl ' . , Xm n n -1 mn ¿ ¿ P T(P ) conditionally on := mn l: i =1 a ¿ ' then the behaviour of P m n,m n n n X. 1 T(P ) should imitate that of when n and mn get large. n This idea has lead to considerable investigations to see when it is correct, and when it is not. When it is not, one looks if there is any way to adapt it.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 244 pp. Englisch.