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Bayesian Models: A Statistical Primer for Ecologists

N. Thompson Hobbs and Mevin B. Hooten

Published in print:
2015
Published Online:
October 2017
ISBN:
9780691159287
eISBN:
9781400866557
Item type:
book
Publisher:
Princeton University Press
DOI:
10.23943/princeton/9780691159287.001.0001
Subject:
Biology, Ecology

Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This book provides a comprehensive ... More


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


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


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


Reforming the German Civil Servant Pension Plan

Raimond Maurer, Olivia S. Mitchell, and Ralph Rogalla

in The Future of Public Employee Retirement Systems

Published in print:
2009
Published Online:
February 2010
ISBN:
9780199573349
eISBN:
9780191721946
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199573349.003.0009
Subject:
Business and Management, Public Management, Pensions and Pension Management

This chapter analyzes the risks and rewards of moving from an unfunded defined benefit pension system to a funded plan for civil servants in Germany, allowing for alternative portfolio mixes using a ... More


Estimating and Applying Uncertainty in Assessment models

Thomas B. Kirchner

in Radiological Risk Assessment and Environmental Analysis

Published in print:
2008
Published Online:
September 2008
ISBN:
9780195127270
eISBN:
9780199869121
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195127270.003.0011
Subject:
Biology, Ecology, Biochemistry / Molecular Biology

This chapter discusses probabilistic methods for conducting uncertainty analysis, methods that can be use to evaluate both local and global sensitivity of models to parameters, and issues related to ... More


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


Quantifying Uncertainty in Net Primary Production Measurements

Mark E. Harmon, Donald L. Phillips, John J. Battles, Andrew Rassweiler, Robert O. Hall Jr., and William K. Lauenroth

in Principles and Standards for Measuring Primary Production

Published in print:
2007
Published Online:
September 2007
ISBN:
9780195168662
eISBN:
9780199790128
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195168662.003.0012
Subject:
Biology, Ecology

Because primary production usually is estimated from several variables that are themselves subject to error in measurement, these errors propagate as the variables are combined mathematically. ... More


Introduction to Probability and Random Variables

M. Vidyasagar

in Hidden Markov Processes: Theory and Applications to Biology

Published in print:
2014
Published Online:
October 2017
ISBN:
9780691133157
eISBN:
9781400850518
Item type:
chapter
Publisher:
Princeton University Press
DOI:
10.23943/princeton/9780691133157.003.0001
Subject:
Mathematics, Probability / Statistics

This chapter provides an introduction to probability and random variables. Probability theory is an attempt to formalize the notion of uncertainty in the outcome of an experiment. For instance, ... 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


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