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Books > Business & Economics > Economics > Econometrics > Economic statistics
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Fundamentals of Nonparametric Bayesian Inference (Hardcover)
Loot Price: R2,850
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Fundamentals of Nonparametric Bayesian Inference (Hardcover)
Series: Cambridge Series in Statistical and Probabilistic Mathematics
Expected to ship within 10 - 15 working days
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Explosive growth in computing power has made Bayesian methods for
infinite-dimensional models - Bayesian nonparametrics - a nearly
universal framework for inference, finding practical use in
numerous subject areas. Written by leading researchers, this
authoritative text draws on theoretical advances of the past twenty
years to synthesize all aspects of Bayesian nonparametrics, from
prior construction to computation and large sample behavior of
posteriors. Because understanding the behavior of posteriors is
critical to selecting priors that work, the large sample theory is
developed systematically, illustrated by various examples of model
and prior combinations. Precise sufficient conditions are given,
with complete proofs, that ensure desirable posterior properties
and behavior. Each chapter ends with historical notes and numerous
exercises to deepen and consolidate the reader's understanding,
making the book valuable for both graduate students and researchers
in statistics and machine learning, as well as in application areas
such as econometrics and biostatistics.
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