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Characterizing Uncertainty of Future Climate Change Projections using Hierarchical Bayesian Models *

Claudia Tebaldi, Bruno Sansó, and Richard L. Smith

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/9780199694587.003.0021
Subject:
Mathematics, Probability / Statistics

The use of projections from ensembles of climate models to characterize fu ture climate change at regional scales has become the most widely adopted framework, as opposed to what was standard ... More


Surviving fully Bayesian nonparametric regression models

Timothy E. Hanson and Alejandro Jara

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/9780199695607.003.0030
Subject:
Mathematics, Probability / Statistics

This chapter compares two Bayesian nonparametric models that generalize the accelerated failure time model, based on recent work on probability models for predictor-dependent probability ... More


Approximate marginalization over modelling errors and uncertainties in inverse problems

Jari Kaipio and Ville Kolehmainen

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/9780199695607.003.0032
Subject:
Mathematics, Probability / Statistics

This chapter discusses the so-called approximation error approach, which was originally meant to model numerical model reduction only. The approach is based on a number of consecutive approximations ... More


Flexible Bayesian modelling for clustered categorical responses in developmental toxicology

Kottas Athanasios and Fronczyk Kassandra

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/9780199695607.003.0005
Subject:
Mathematics, Probability / Statistics

Developmental toxicity studies investigate birth defects caused by toxic chemicals. This chapter develops a Bayesian nonparametric modelling approach for risk assessment in developmental toxicity ... More


Revisiting Bayesian curve fitting using multivariate normal mixtures ∗

Stephen G Walker and George Karabatsos

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/9780199695607.003.0015
Subject:
Mathematics, Probability / Statistics

This chapter develops a Bayesian nonparametric regression model which relies on a standard Bayesian nonparametric form for the joint distribution of both the dependent and independent variables. The ... More


Prediction of Clinical Outcomes from Genome-wide Data

Shyam Visweswaran

in Probabilistic Graphical Models for Genetics, Genomics, and Postgenomics

Published in print:
2014
Published Online:
December 2014
ISBN:
9780198709022
eISBN:
9780191779619
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198709022.003.0017
Subject:
Mathematics, Probability / Statistics, Biostatistics

Prognosis is an essential tool in medicine for estimating the likely outcomes of a disease and for preventing it. The traditional approach relies on measuring physiological and environmental ... More


Semi-supervised classification of texts using particle learning for probabilistic automata

ANA PAULA SALES, CHRISTOPHER CHALLIS, RYAN PRENGER, and DANIEL MERL

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/9780199695607.003.0012
Subject:
Mathematics, Probability / Statistics

This chapter presents a novel online learning system for classification of email texts based on particle learning for composite mixture models involving probabilistic automata. The composite mixture ... More


Real-valued Random Processes

Arno Berger and Theodore P. Hill

in An Introduction to Benford's Law

Published in print:
2015
Published Online:
October 2017
ISBN:
9780691163062
eISBN:
9781400866588
Item type:
chapter
Publisher:
Princeton University Press
DOI:
10.23943/princeton/9780691163062.003.0008
Subject:
Mathematics, Probability / Statistics

Benford's law arises naturally in a variety of stochastic settings, including products of independent random variables, mixtures of random samples from different distributions, and iterations of ... More


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