Jingchen hu (3 Ergebnisse)
Albert, J: Probability and Bayesian Modeling
Jim Albert (Emeritus Professor at Bowling Green State Uni.)|Jingchen Hu
Sprache: Englisch
Verlag: CRC Press, 2019
Serie: Buch 65 von 59 - Chapman & Hall/CRC Texts in Statistical Science
- Hardcover
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EUR 119,14
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Zustand: New. Jim Albert is a Distinguished University Professor of Statistics at Bowling Green State University. His research interests include Bayesian modeling and applications of statistical thinking in sports. He has authored or coauthored severa.
Sprache: Englisch
Verlag: CRC Press Dez 2019, 2019
Serie: Buch 65 von 59 - Chapman & Hall/CRC Texts in Statistical Science
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Buch. Zustand: Neu. Neuware - Probability and Bayesian Modeling is an introduction to probability and Bayesian thinking for undergraduate students with a calculus background. The first part of the book provides a broad view of probability including foundations, conditional probability, discrete and continuous distributions, and…joint distributions. Statistical inference is presented completely from a Bayesian perspective. The text introduces inference and prediction for a single proportion and a single mean from Normal sampling. After fundamentals of Markov Chain Monte Carlo algorithms are introduced, Bayesian inference is described for hierarchical and regression models including logistic regression. The book presents several case studies motivated by some historical Bayesian studies and the authors' research.This text reflects modern Bayesian statistical practice. Simulation is introduced in all the probability chapters and extensively used in the Bayesian material to simulate from the posterior and predictive distributions. One chapter describes the basic tenets of Metropolis and Gibbs sampling algorithms; however several chapters introduce the fundamentals of Bayesian inference for conjugate priors to deepen understanding. Strategies for constructing prior distributions are described in situations when one has substantial prior information and for cases where one has weak prior knowledge. One chapter introduces hierarchical Bayesian modeling as a practical way of combining data from different groups. There is an extensive discussion of Bayesian regression models including the construction of informative priors, inference about functions of the parameters of interest, prediction, and model selection.The text uses JAGS (Just Another Gibbs Sampler) as a general-purpose computational method for simulating from posterior distributions for a variety of Bayesian models. An R package ProbBayes is available containing all of the book datasets and special functions for illustrating concepts from the book.A complete solutions manual is available for instructors who adopt the book in the Additional Resources section.
Verlag: Art Sight Gallery. [2008]., ??.[Beijing]., 2008
Anbieter: Asia Bookroom ANZAAB/ILAB, Canberra, ACT, AustralienAsia Bookroom ANZAAB/ILAB
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In den WarenkorbColour plates of the artists works, 61pp, very good in card covers. 26 x 18cm. Bilingual Chinese and English.
