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A SURVEY ON THE USE OF MARKOV CHAINS TO RANDOMLY SAMPLE COLOURINGS

Alan Frieze and Eric Vigoda

in Combinatorics, Complexity, and Chance: A Tribute to Dominic Welsh

Published in print:
2007
Published Online:
September 2007
ISBN:
9780198571278
eISBN:
9780191718885
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198571278.003.0004
Subject:
Mathematics, Probability / Statistics

In recent years, considerable progress has been made on the analysis of Markov chains for generating a random colouring of an input graph. These improvements have come in conjunction with refinements ... More


Inference

Jesper Møller

in New Perspectives in Stochastic Geometry

Published in print:
2009
Published Online:
February 2010
ISBN:
9780199232574
eISBN:
9780191716393
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199232574.003.0009
Subject:
Mathematics, Geometry / Topology

This contribution concerns statistical inference for parametric models used in stochastic geometry and based on quick and simple simulation free procedures as well as more comprehensive methods based ... More


Bayesian computation (MCMC)

Ziheng Yang

in Molecular Evolution: A Statistical Approach

Published in print:
2014
Published Online:
August 2014
ISBN:
9780199602605
eISBN:
9780191782251
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199602605.003.0007
Subject:
Biology, Biomathematics / Statistics and Data Analysis / Complexity Studies, Evolutionary Biology / Genetics

This chapter provides a detailed introduction to modern Bayesian computation. The Metropolis–Hastings algorithm is illustrated using a simple example of distance estimation between two sequences. A ... More


A primer on probabilistic inference

Thomas L. Griffiths and Alan Yuille

in The Probabilistic Mind:: Prospects for Bayesian cognitive science

Published in print:
2008
Published Online:
March 2012
ISBN:
9780199216093
eISBN:
9780191695971
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199216093.003.0002
Subject:
Psychology, Cognitive Psychology

This chapter provides the technical introduction to Bayesian methods. Probabilistic models of cognition are often referred to as Bayesian models, reflecting the central role that Bayesian inference ... More


Bayesian Theory and Applications

Paul Damien, Petros Dellaportas, Nicholas G. Polson, and David A. Stephens (eds)

Published in print:
2013
Published Online:
May 2013
ISBN:
9780199695607
eISBN:
9780191744167
Item type:
book
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199695607.001.0001
Subject:
Mathematics, Probability / Statistics

The development of hierarchical models and Markov chain Monte Carlo (MCMC) techniques forms one of the most profound advances in Bayesian analysis since the 1970s and provides the basis for advances ... More


Bayesian Inference in Dynamic Econometric Models

Luc Bauwens, Michel Lubrano, and Jean-François Richard

Published in print:
2000
Published Online:
September 2011
ISBN:
9780198773122
eISBN:
9780191695315
Item type:
book
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198773122.001.0001
Subject:
Economics and Finance, Econometrics

This book contains an up-to-date coverage of the last twenty years of advances in Bayesian inference in econometrics, with an emphasis on dynamic models. It shows how to treat Bayesian inference in ... More


Online Bayesian learning in dynamic models: an illustrative introduction to particle methods

Hedibert F Lopes and Carlos M Carvalho

in Bayesian Theory and Applications

Published in print:
2013
Published Online:
May 2013
ISBN:
9780199695607
eISBN:
9780191744167
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199695607.003.0011
Subject:
Mathematics, Probability / Statistics

This chapter provides a step-by-step review of Monte Carlo (MC) methods for filtering in general nonlinear and non-Gaussian dynamic models, also known as state-space models or hidden Markov models. ... More


Markov chain Monte Carlo methods in corporate finance

ARTHUR KORTEWEG

in Bayesian Theory and Applications

Published in print:
2013
Published Online:
May 2013
ISBN:
9780199695607
eISBN:
9780191744167
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199695607.003.0026
Subject:
Mathematics, Probability / Statistics

This chapter introduces Markov chain Monte Carlo (MCMC) methods and provides a hands-on guide to writing algorithms. It also illustrates some of the many applications of MCMC in corporate finance. ... More


Modelling bivariate processes

Eric Renshaw

in Stochastic Population Processes: Analysis, Approximations, Simulations

Published in print:
2011
Published Online:
September 2011
ISBN:
9780199575312
eISBN:
9780191728778
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199575312.003.0007
Subject:
Mathematics, Applied Mathematics, Mathematical Biology

This chapter examines the general bivariate process, and illustrates the basic approaches involved by first developing a simple process for which the preceding methods of solution do carry across. ... More


Monte Carlo computational approaches in Bayesiancodon-substitution modelling

Nicolas Rodrigue and Nicolas Lartillot

in Codon Evolution: Mechanisms and Models

Published in print:
2012
Published Online:
May 2015
ISBN:
9780199601165
eISBN:
9780191810114
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:osobl/9780199601165.003.0004
Subject:
Biology, Evolutionary Biology / Genetics

This chapter reviews Markov Chain Monte Carlo (MCMC) approaches in codon-substitution modelling. It outlines the process of data analysis using the Bayesian framework. It describes the algorithms for ... More


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