Jump to ContentJump to Main Navigation

You are looking at 1-10 of 34 items

  • Keywords: Bayesian models x
Clear All Modify Search

View:

Bayesian Statistical Inference

Željko Ivezi, Andrew J. Connolly, Jacob T. VanderPlas, Alexander Gray, Željko Ivezi, Andrew J. Connolly, Jacob T. VanderPlas, and Alexander Gray

in Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data

Published in print:
2014
Published Online:
October 2017
ISBN:
9780691151687
eISBN:
9781400848911
Item type:
chapter
Publisher:
Princeton University Press
DOI:
10.23943/princeton/9780691151687.003.0005
Subject:
Physics, Particle Physics / Astrophysics / Cosmology

This chapter introduces the most important aspects of Bayesian statistical inference and techniques for performing such calculations in practice. It first reviews the basic steps in Bayesian ... More


Developing predictive models

E. J. Milner-Gulland and Marcus Rowcliffe

in Conservation and Sustainable Use: A Handbook of Techniques

Published in print:
2007
Published Online:
January 2008
ISBN:
9780198530367
eISBN:
9780191713095
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198530367.003.0005
Subject:
Biology, Biodiversity / Conservation Biology

The effective management of natural resources use requires a mechanistic understanding of the system, not just correlations between variables of the kind discussed in Chapter 4. Understanding may ... More


Hierarchical Bayesian Models

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/9780691159287.003.0006
Subject:
Biology, Ecology

This chapter seeks to explain hierarchical models and how they differ from simple Bayesian models and to illustrate building hierarchical models using mathematically correct expressions. It begins ... More


Thinking about Evidence1

DAVID LAGNADO

in Evidence, Inference and Enquiry

Published in print:
2011
Published Online:
January 2013
ISBN:
9780197264843
eISBN:
9780191754050
Item type:
chapter
Publisher:
British Academy
DOI:
10.5871/bacad/9780197264843.003.0007
Subject:
Sociology, Methodology and Statistics

This chapter argues that people reason about legal evidence using small-scale qualitative networks. These cognitive networks are typically qualitative and incomplete, and based on people's causal ... More


Simple Bayesian Models

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/9780691159287.003.0005
Subject:
Biology, Ecology

This chapter lays out the basic principles of Bayesian inference, building on the concepts of probability developed in Chapter 3. It seeks to use the rules of probability to show how Bayes' theorem ... More


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


Writing Bayesian Models

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/9780691159287.003.0010
Subject:
Biology, Ecology

This chapter offers a general set of steps for writing models to assist the researcher in formulating their own approach to the Bayesian model. The crucial skill of specifying models is often ... More


Humans' Multisensory Perception, from Integration to Segregation, Follows Bayesian Inference

Ladan Shams and Ulrik Beierholm

in Sensory Cue Integration

Published in print:
2011
Published Online:
September 2012
ISBN:
9780195387247
eISBN:
9780199918379
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195387247.003.0013
Subject:
Psychology, Cognitive Neuroscience, Cognitive Psychology

This chapter first discusses experimental findings showing that multisensory perception encompasses a spectrum of phenomena ranging from full integration (or fusion), to partial integration, to ... More


Spatial variation in risk

Dirk U. Pfeiffer, Timothy P. Robinson, Mark Stevenson, Kim B. Stevens, David J. Rogers, and Archie C. A. Clements

in Spatial Analysis in Epidemiology

Published in print:
2008
Published Online:
September 2008
ISBN:
9780198509882
eISBN:
9780191709128
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198509882.003.0006
Subject:
Biology, Disease Ecology / Epidemiology

This chapter discusses spatial variation in risk. Epidemiological disease investigations should include an assessment of the spatial variation of disease risk, as this may provide important clues ... More


Preview

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/9780691159287.003.0001
Subject:
Biology, Ecology

This chapter sketches an approach to inference applicable to an enormous range of research problems—one that can be understood from first principles and that can be unambiguously communicated to ... More


View: