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Bayesian Statistics 9

José M. Bernardo, M. J. Bayarri, James O. Berger, A. P. Dawid, David Heckerman, Adrian F. M. Smith, and Mike West (eds)

Published in print:
2011
Published Online:
January 2012
ISBN:
9780199694587
eISBN:
9780191731921
Item type:
book
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199694587.001.0001
Subject:
Mathematics, Probability / Statistics

The Valencia International Meetings on Bayesian Statistics – established in 1979 and held every four years – have been the forum for a definitive overview of current concerns and activities in ... More


Bayesian Smoothing and Regression for Longitudinal, Spatial and Event History Data

Ludwig Fahrmeir and Thomas Kneib

Published in print:
2011
Published Online:
September 2011
ISBN:
9780199533022
eISBN:
9780191728501
Item type:
book
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199533022.001.0001
Subject:
Mathematics, Probability / Statistics, Biostatistics

Several recent advances in smoothing and semiparametric regression are presented in this book from a unifying, Bayesian perspective. Simulation-based full Bayesian Markov chain Monte Carlo (MCMC) ... More


Markov Chain Monte Carlo

N. Thompson Hobbs and Mevin B. Hooten

in Bayesian Models: A Statistical Primer for Ecologists

Published in print:
2015
Published Online:
October 2017
ISBN:
9780691159287
eISBN:
9781400866557
Item type:
chapter
Publisher:
Princeton University Press
DOI:
10.23943/princeton/9780691159287.003.0007
Subject:
Biology, Ecology

This chapter explains how to implement Bayesian analyses using the Markov chain Monte Carlo (MCMC) algorithm, a set of methods for Bayesian analysis made popular by the seminal paper of Gelfand and ... More


Inference from a Single Model

N. Thompson Hobbs and Mevin B. Hooten

in Bayesian Models: A Statistical Primer for Ecologists

Published in print:
2015
Published Online:
October 2017
ISBN:
9780691159287
eISBN:
9781400866557
Item type:
chapter
Publisher:
Princeton University Press
DOI:
10.23943/princeton/9780691159287.003.0008
Subject:
Biology, Ecology

This chapter shows how to make inferences using MCMC samples. Here, the process of inference begins on the assumption that a single model is being analyzed. The objective is to estimate parameters, ... More


Parsimony and Bayesian phylogenetics

Pablo A. Goloboff and Diego Pol

in Parsimony, Phylogeny, and Genomics

Published in print:
2006
Published Online:
September 2007
ISBN:
9780199297306
eISBN:
9780191713729
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199297306.003.0008
Subject:
Biology, Evolutionary Biology / Genetics

The intent of a statistically-based phylogenetic method is to estimate tree topologies and values of possibly relevant parameters, as well as the uncertainty inherent in those estimations. A method ... 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


Advances in Markov chain Monte Carlo

Griffin Jim E and Stephens David A

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/9780199695607.003.0007
Subject:
Mathematics, Probability / Statistics

This chapter traces some of the key developments that further developed the underpinning theory and potential applications of Markov chain Monte Carlo (MCMC) since the mid 1990s. In particular, it ... More


Molecular Evolution: A Statistical Approach

Ziheng Yang

Published in print:
2014
Published Online:
August 2014
ISBN:
9780199602605
eISBN:
9780191782251
Item type:
book
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199602605.001.0001
Subject:
Biology, Biomathematics / Statistics and Data Analysis / Complexity Studies, Evolutionary Biology / Genetics

This book summarizes the statistical models and computational algorithms for comparative analysis of genetic sequence data in the fields of molecular evolution, molecular phylogenetics, and ... More


Bridges: Inference and the Monte Carlo method

Marc Mézard and Andrea Montanari

in Information, Physics, and Computation

Published in print:
2009
Published Online:
September 2009
ISBN:
9780198570837
eISBN:
9780191718755
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198570837.003.0013
Subject:
Physics, Theoretical, Computational, and Statistical Physics

The mathematical structure highlighted in this chapter by the factor graph representation is the locality of probabilistic dependencies between variables. Locality also emerges in many problems of ... More


Bayesian Models for Sparse Regression Analysis of High Dimensional Data *

Sylvia Richardson, Leonardo Bottolo, and Jeffrey S. Rosenthal

in Bayesian Statistics 9

Published in print:
2011
Published Online:
January 2012
ISBN:
9780199694587
eISBN:
9780191731921
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199694587.003.0018
Subject:
Mathematics, Probability / Statistics

This paper considers the task of building efficient regression models for sparse multivariate analysis of high dimensional data sets, in particular it focuses on cases where the numbers q of ... More


Parameter Inference for Stochastic Kinetic Models of Bacterial Gene Regulation: A Bayesian Approach to Systems Biology

Darren J. Wilkinson

in Bayesian Statistics 9

Published in print:
2011
Published Online:
January 2012
ISBN:
9780199694587
eISBN:
9780191731921
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199694587.003.0023
Subject:
Mathematics, Probability / Statistics

Bacteria are single‐celled organisms which often display heterogeneous behaviour, even among populations of genetically identical cells in uniform environmental conditions. Markov process models ... More


Bayesian Variable Selection for Random Intercept Modeling of Gaussian and Non‐Gaussian Data

Sylvia Frühwirth‐Schnatter and Helga Wagner

in Bayesian Statistics 9

Published in print:
2011
Published Online:
January 2012
ISBN:
9780199694587
eISBN:
9780191731921
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199694587.003.0006
Subject:
Mathematics, Probability / Statistics

The paper demonstrates that Bayesian variable selection for random intercept models is closely related to the appropriate choice of the distribution of heterogeneity. If, for instance, a Laplace ... More


Sequential Monte Carlo Methods

Edward P. Herbst and Frank Schorfheide

in Bayesian Estimation of DSGE Models

Published in print:
2015
Published Online:
October 2017
ISBN:
9780691161082
eISBN:
9781400873739
Item type:
chapter
Publisher:
Princeton University Press
DOI:
10.23943/princeton/9780691161082.003.0005
Subject:
Economics and Finance, Econometrics

This chapter analyzes Sequential Monte Carlo (SMC) algorithms and how they were initially developed to solve filtering problems that arise in nonlinear state–space models. The first paper that ... More


Combining Particle Filters with MH Samplers

Edward P. Herbst and Frank Schorfheide

in Bayesian Estimation of DSGE Models

Published in print:
2015
Published Online:
October 2017
ISBN:
9780691161082
eISBN:
9781400873739
Item type:
chapter
Publisher:
Princeton University Press
DOI:
10.23943/princeton/9780691161082.003.0009
Subject:
Economics and Finance, Econometrics

This chapter argues that in order to conduct Bayesian inference, the approximate likelihood function has to be embedded into a posterior sampler. It begins by combining the particle filtering methods ... 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


Markov chain Monte Carlo methods

Chib Siddhartha

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/9780199695607.003.0006
Subject:
Mathematics, Probability / Statistics

This chapter provides a brief summary of Markov chain Monte Carlo (MCMC) methods. The chapter is organized as follows. Section 6.2 describes the Metropolis–Hastings algorithm and its generalized ... 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


Bayesian phylogenetics

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/9780199602605.003.0008
Subject:
Biology, Biomathematics / Statistics and Data Analysis / Complexity Studies, Evolutionary Biology / Genetics

This chapter discusses the implementation of various models of genetic sequence evolution in Bayesian phylogenetic analysis. It discusses the specification of priors for parameters in such models, as ... More


Coalescent theory and species trees

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/9780199602605.003.0009
Subject:
Biology, Biomathematics / Statistics and Data Analysis / Complexity Studies, Evolutionary Biology / Genetics

This chapter introduces Kingman’s coalescent process, which describes the genealogical relationships within a sample of DNA sequences taken from a population, and forms the basis for likelihood-based ... More


Finite Mixture Examples; MAPIS Details

Russell Cheng

in Non-Standard Parametric Statistical Inference

Published in print:
2017
Published Online:
September 2017
ISBN:
9780198505044
eISBN:
9780191746390
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780198505044.003.0018
Subject:
Mathematics, Probability / Statistics

Two detailed numerical examples are given in this chapter illustrating and comparing mainly the reversible jump Markov chain Monte Carlo (RJMCMC) and the maximum a posteriori/importance sampling ... More


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