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Essential bayesian models

By: Material type: TextTextSeries: A derivative of handbook of statistics: bayesian thinking - modeling and computation, Vol. 25Publication details: 2011 Elsevier AmsterdamDescription: xii, 574 pISBN:
  • 9780444537324
Subject(s): DDC classification:
  • 519.5 E8
Summary: This accessible reference includes selected contributions from Bayesian Thinking - Modeling and Computation, Volume 25 in the Handbook of Statistics Series, with a focus on key methodologies and applications for Bayesian models and computation. It describes parametric and nonparametric Bayesian methods for modeling, and how to use modern computational methods to summarize inferences using simulation. The book covers a wide range of topics including objective and subjective Bayesian inferences, with a variety of applications in modeling categorical, survival, spatial, spatiotemporal, Epidemiological, small area and micro array data. (http://www.elsevier.com/wps/find/bookdescription.cws_home/724259/description#description)
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Item type Current library Item location Shelving location Call number Status Date due Barcode
Books Vikram Sarabhai Library Rack 28-B / Slot 1411 (0 Floor, East Wing) General Stacks 519.5 E8 (Browse shelf(Opens below)) Available 172379

This accessible reference includes selected contributions from Bayesian Thinking - Modeling and Computation, Volume 25 in the Handbook of Statistics Series, with a focus on key methodologies and applications for Bayesian models and computation. It describes parametric and nonparametric Bayesian methods for modeling, and how to use modern computational methods to summarize inferences using simulation. The book covers a wide range of topics including objective and subjective Bayesian inferences, with a variety of applications in modeling categorical, survival, spatial, spatiotemporal, Epidemiological, small area and micro array data. (http://www.elsevier.com/wps/find/bookdescription.cws_home/724259/description#description)

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