Markov chain Monte Carlo in practice

Contributor(s):

Material type: Text

TextPublication details: London Chapman & Hall/CRC 1998 Description: xvii, 486 pISBN:

9780412055515

Subject(s):

DDC classification:

519.1

Summary: In a family study of breast cancer, epidemiologists in Southern California increase the power for detecting a gene-environment interacIn a family study of breast cancer, epidemiologists in Southern California increase the power for detecting a gene-environment interaction. In Gambia, a study helps a vaccination program reduce the incidence of Hepatitis B carriage. Archaeologists in Austria place a Bronze Age site in its true temporal location on the calendar scale. And in France, researchers map a rare disease with relatively little variation.Each of these studies applied Markov chain Monte Carlo methods to produce more accurate and inclusive results. General state-space Markov chain theory has seen several developments that have made it both more accessible and more powerful to the general statistician. Markov Chain Monte Carlo in Practice introduces MCMC methods and their applications.

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Item type	Current library	Call number	Status	Date due	Barcode	Item holds
Book	Ahmedabad	519.1 M21 (Browse shelf(Opens below))	Available		158969

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Previous	519.1 L2A7 Applied probability	519.1 L6P7/78-II Probability theory	519.1 M2 Matrix-analytic methods in stochastic models	519.1 M21 Markov chain Monte Carlo in practice	519.1 M2S8 Stochastic optimization methods	519.1 M3S8/94 Stochastic processes	519.1 M6D4 Discrete stochastic	Next

In a family study of breast cancer, epidemiologists in Southern California increase the power for detecting a gene-environment interacIn a family study of breast cancer, epidemiologists in Southern California increase the power for detecting a gene-environment interaction. In Gambia, a study helps a vaccination program reduce the incidence of Hepatitis B carriage. Archaeologists in Austria place a Bronze Age site in its true temporal location on the calendar scale. And in France, researchers map a rare disease with relatively little variation.Each of these studies applied Markov chain Monte Carlo methods to produce more accurate and inclusive results. General state-space Markov chain theory has seen several developments that have made it both more accessible and more powerful to the general statistician. Markov Chain Monte Carlo in Practice introduces MCMC methods and their applications.

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