Jump to ContentJump to Main Navigation

You are looking at 1-10 of 51 items

  • Keywords: Bayesian inference 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


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


How to Improve Bayesian Reasoning without Instruction

Gerd Gigerenzer

in Adaptive Thinking: Rationality in the Real World

Published in print:
2002
Published Online:
October 2011
ISBN:
9780195153729
eISBN:
9780199849222
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195153729.003.0006
Subject:
Philosophy, General

This chapter defines the concepts of natural sampling, natural frequencies, and reports experimental evidence for the impact of various external representations on statistical thinking. The mental ... More


Innateness and (Bayesian) Visual Perception: Reconciling Nativism and Development

Brian J. Scholl

in The Innate Mind: Structure and Contents

Published in print:
2005
Published Online:
January 2007
ISBN:
9780195179675
eISBN:
9780199869794
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195179675.003.0003
Subject:
Philosophy, Metaphysics/Epistemology

This chapter explores a way in which visual processing may involve innate constraints and attempts to show how such processing overcomes one enduring challenge to nativism. In particular, many ... More


Murder and (of?) the Likelihood Principle: A Trialogue

Jie W Weiss and David J Weiss

in A Science of Decision Making: The Legacy of Ward Edwards

Published in print:
2008
Published Online:
January 2009
ISBN:
9780195322989
eISBN:
9780199869206
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195322989.003.0017
Subject:
Psychology, Cognitive Psychology

The Likelihood Principle of Bayesian inference asserts that only likelihoods matter to single-stage inference. A likelihood is the probability of evidence given a hypothesis multiplied by a positive ... More


Rational Statistical Inference and Cognitive Development

Fei Xu

in The Innate Mind, Volume 3: Foundations and the Future

Published in print:
2008
Published Online:
January 2008
ISBN:
9780195332834
eISBN:
9780199868117
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195332834.003.0010
Subject:
Philosophy, Philosophy of Mind

This chapter advocates a view that is a substantive middle ground between the extreme versions of nativism and empiricism — a view dubbed ‘rational constructivism’. This is a view that commits us to ... More


Decision Theory and Bayesian Inference

Luc Bauwens, Michel Lubrano, and Jean-François Richard

in Bayesian Inference in Dynamic Econometric Models

Published in print:
2000
Published Online:
September 2011
ISBN:
9780198773122
eISBN:
9780191695315
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198773122.003.0001
Subject:
Economics and Finance, Econometrics

This chapter discusses the relationship between mathematical statistics, decision theory, and the application of Bayesian inference to econometrics. It analyses the Bayesian approach to decision ... 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


Bayesian Statistics and Linear Regression

Luc Bauwens, Michel Lubrano, and Jean-François Richard

in Bayesian Inference in Dynamic Econometric Models

Published in print:
2000
Published Online:
September 2011
ISBN:
9780198773122
eISBN:
9780191695315
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198773122.003.0002
Subject:
Economics and Finance, Econometrics

This chapter presents the basic concepts and tools that are useful for modelling and for Bayesian inference. It defines density kernels useful for simplifying notation and computations and explains ... More


Intuitive Theories as Grammars for Causal Inference

Joshua B. Tenenbaum, Thomas L. Griffiths, and Sourabh Niyogi

in Causal Learning: Psychology, Philosophy, and Computation

Published in print:
2007
Published Online:
April 2010
ISBN:
9780195176803
eISBN:
9780199958511
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195176803.003.0020
Subject:
Psychology, Developmental Psychology

This chapter presents a framework for understanding the structure, function, and acquisition of causal theories from a rational computational perspective. Using a “reverse engineering” approach, it ... More


View: