Large-Scale Inference
"Sinopsis" puede pertenecer a otra edición de este libro.
Bradley Efron is Max H. Stein Professor of Statistics and Biostatistics at the Stanford University School of Humanities and Sciences, and the Department of Health Research and Policy with the School of Medicine.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: BooksRun, Philadelphia, PA, Estados Unidos de America
Paperback. Condición: Very Good. Reprint. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting. Nº de ref. del artículo: 110761967X-11-1
Cantidad disponible: 1 disponibles
Librería: BooksRun, Philadelphia, PA, Estados Unidos de America
Paperback. Condición: Very Good. Reprint. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting. Nº de ref. del artículo: 110761967X-8-1
Cantidad disponible: 1 disponibles
Librería: Austin Goodwill 1101, Austin, TX, Estados Unidos de America
Condición: good. Book shows general signs of use and handling. May have light wear on the cover or edges and minimal writing or highlighting. Binding remains tight, and pages are clean and readable. Nº de ref. del artículo: CTXV.110761967X.G
Cantidad disponible: 1 disponibles
Librería: Goodwill of Ventura and Santa Barbara Counties, Oxnard, CA, Estados Unidos de America
Condición: good. Good: The book has been read but is in good condition. It has very minimal damage to the cover, including scuff marks, but no holes or tears. The dust jacket for hard covers may not be included. The binding has minimal wear. The majority of pages are undamaged with minimal creasing or tearing, minimal pencil underlining of text, no highlighting of text, and no writing in the margins. There are no missing pages. See the seller's listing for full details and a description of any imperfections. Nº de ref. del artículo: VSBV.110761967X.G
Cantidad disponible: 1 disponibles
Librería: Better World Books: West, Reno, NV, Estados Unidos de America
Condición: Very Good. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good. Nº de ref. del artículo: 45258124-6
Cantidad disponible: 1 disponibles
Librería: HPB-Red, Dallas, TX, Estados Unidos de America
Paperback. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! Nº de ref. del artículo: S_481038587
Cantidad disponible: 1 disponibles
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 18846056
Cantidad disponible: Más de 20 disponibles
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Condición: New. Nº de ref. del artículo: 18846056-n
Cantidad disponible: Más de 20 disponibles
Librería: California Books, Miami, FL, Estados Unidos de America
Condición: New. Nº de ref. del artículo: I-9781107619678
Cantidad disponible: Más de 20 disponibles
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
Paperback. Condición: New. We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines routinely produce thousands and sometimes millions of parallel data sets, each with its own estimation or testing problem. Doing thousands of problems at once is more than repeated application of classical methods. Taking an empirical Bayes approach, Bradley Efron, inventor of the bootstrap, shows how information accrues across problems in a way that combines Bayesian and frequentist ideas. Estimation, testing and prediction blend in this framework, producing opportunities for new methodologies of increased power. New difficulties also arise, easily leading to flawed inferences. This book takes a careful look at both the promise and pitfalls of large-scale statistical inference, with particular attention to false discovery rates, the most successful of the new statistical techniques. Emphasis is on the inferential ideas underlying technical developments, illustrated using a large number of real examples. Nº de ref. del artículo: LU-9781107619678
Cantidad disponible: Más de 20 disponibles