Author : Jon Williamson
Publisher : Oxford University Press
Page : 192 pages
File Size : 31,96 MB
Release : 2010-05-13
Category : Computers
ISBN : 0199228000
Objective Bayesianism is a methodological theory that is currently applied in statistics, philosophy, artificial intelligence, physics and other sciences. This book develops the formal and philosophical foundations of the theory, at a level accessible to a graduate student with some familiarity with mathematical notation.
Author : Jon Williamson
Publisher : OUP Oxford
Page : 192 pages
File Size : 48,16 MB
Release : 2010-05-13
Category : Mathematics
ISBN : 0191576131
How strongly should you believe the various propositions that you can express? That is the key question facing Bayesian epistemology. Subjective Bayesians hold that it is largely (though not entirely) up to the agent as to which degrees of belief to adopt. Objective Bayesians, on the other hand, maintain that appropriate degrees of belief are largely (though not entirely) determined by the agent's evidence. This book states and defends a version of objective Bayesian epistemology. According to this version, objective Bayesianism is characterized by three norms: · Probability - degrees of belief should be probabilities · Calibration - they should be calibrated with evidence · Equivocation - they should otherwise equivocate between basic outcomes Objective Bayesianism has been challenged on a number of different fronts. For example, some claim it is poorly motivated, or fails to handle qualitative evidence, or yields counter-intuitive degrees of belief after updating, or suffers from a failure to learn from experience. It has also been accused of being computationally intractable, susceptible to paradox, language dependent, and of not being objective enough. Especially suitable for graduates or researchers in philosophy of science, foundations of statistics and artificial intelligence, the book argues that these criticisms can be met and that objective Bayesianism is a promising theory with an exciting agenda for further research.
Author : Ali Paya
Publisher : ICAS Press
Page : 752 pages
File Size : 28,60 MB
Release : 2021-01-01
Category : Social Science
ISBN : 1907905529
This book presents the first comprehensive introduction to methods and methodologies in the humanities and social sciences in general, and Islamic Studies in particular, from a critical rationalist point of view. The book aims to be a self-sufficient theoretical and practical guide to the topics that it introduces. It contains a large selection of fully worked out review activities and review questions plus topics for further discussion which are devised to assist readers to better understand the issues which are discussed in the book. Last but not least, all efforts have been made to make sure that most (if not all) of the reading materials which are recommended in the book are not only of the highest quality but also freely available on the internet.
Author : Jan Sprenger
Publisher :
Page : 414 pages
File Size : 49,3 MB
Release : 2019
Category : Mathematics
ISBN : 0199672113
Jan Sprenger and Stephan Hartmann offer a fresh approach to central topics in philosophy of science, including causation, explanation, evidence, and scientific models. Their Bayesian approach uses the concept of degrees of belief to explain and to elucidate manifold aspects of scientific reasoning.
Author : James Franklin
Publisher : JHU Press
Page : 520 pages
File Size : 12,14 MB
Release : 2015-08
Category : History
ISBN : 1421418800
The Science of Conjecture provides a history of rational methods of dealing with uncertainty and explores the coming to consciousness of the human understanding of risk.
Author : Luciano Floridi
Publisher : Routledge
Page : 447 pages
File Size : 43,78 MB
Release : 2016-06-17
Category : Philosophy
ISBN : 1317633490
Information and communication technology occupies a central place in the modern world, with society becoming increasingly dependent on it every day. It is therefore unsurprising that it has become a growing subject area in contemporary philosophy, which relies heavily on informational concepts. The Routledge Handbook of Philosophy of Information is an outstanding reference source to the key topics and debates in this exciting subject and is the first collection of its kind. Comprising over thirty chapters by a team of international contributors the Handbook is divided into four parts: basic ideas quantitative and formal aspects natural and physical aspects human and semantic aspects. Within these sections central issues are examined, including probability, the logic of information, informational metaphysics, the philosophy of data and evidence, and the epistemic value of information. The Routledge Handbook of Philosophy of Information is essential reading for students and researchers in philosophy, computer science and communication studies.
Author : José M. Bernardo
Publisher : John Wiley & Sons
Page : 608 pages
File Size : 13,75 MB
Release : 2009-09-25
Category : Mathematics
ISBN : 047031771X
This highly acclaimed text, now available in paperback, provides a thorough account of key concepts and theoretical results, with particular emphasis on viewing statistical inference as a special case of decision theory. Information-theoretic concepts play a central role in the development of the theory, which provides, in particular, a detailed discussion of the problem of specification of so-called prior ignorance . The work is written from the authors s committed Bayesian perspective, but an overview of non-Bayesian theories is also provided, and each chapter contains a wide-ranging critical re-examination of controversial issues. The level of mathematics used is such that most material is accessible to readers with knowledge of advanced calculus. In particular, no knowledge of abstract measure theory is assumed, and the emphasis throughout is on statistical concepts rather than rigorous mathematics. The book will be an ideal source for all students and researchers in statistics, mathematics, decision analysis, economic and business studies, and all branches of science and engineering, who wish to further their understanding of Bayesian statistics
Author : Alexander Bird
Publisher : Oxford University Press
Page : 297 pages
File Size : 47,72 MB
Release : 2022-10-06
Category : Knowledge, Theory of
ISBN : 019960665X
In Knowing Science, Alexander Bird presents an epistemology of science that rejects empiricism and gives a central place to the concept of knowledge. Science aims at knowledge and progresses when it adds to the stock of knowledge. That knowledge is social knowing--it is known by thescientific community as a whole. Evidence is that from which knowledge can be obtained by inference. From this, it follows that evidence is knowledge, and is not limited to perception, nor to observation. Observation supplies evidence that is basic relative to a field of enquiry and can be highlynon-perceptual. Theoretical knowledge is typically gained by inference to the only explanation, in which competing plausible hypotheses are falsified by the evidence. In cases where not all competing hypotheses are refuted, scientific hypotheses are not known but instead possess varying degrees ofplausibility. Plausibilities in the light of the evidence are probabilities and link eliminative explanationism to Bayesian conditionalization. Bird argues that scientific realism and anti-realism as global metascientific claims should be rejected-the track record gives us only local metascientificclaims.
Author : Rolf Haenni
Publisher : Springer Science & Business Media
Page : 154 pages
File Size : 45,29 MB
Release : 2010-11-19
Category : Science
ISBN : 9400700083
While probabilistic logics in principle might be applied to solve a range of problems, in practice they are rarely applied - perhaps because they seem disparate, complicated, and computationally intractable. This programmatic book argues that several approaches to probabilistic logic fit into a simple unifying framework in which logically complex evidence is used to associate probability intervals or probabilities with sentences. Specifically, Part I shows that there is a natural way to present a question posed in probabilistic logic, and that various inferential procedures provide semantics for that question, while Part II shows that there is the potential to develop computationally feasible methods to mesh with this framework. The book is intended for researchers in philosophy, logic, computer science and statistics. A familiarity with mathematical concepts and notation is presumed, but no advanced knowledge of logic or probability theory is required.
Author : Roy Levy
Publisher : CRC Press
Page : 480 pages
File Size : 46,41 MB
Release : 2017-07-28
Category : Mathematics
ISBN : 1439884684
A Single Cohesive Framework of Tools and Procedures for Psychometrics and Assessment Bayesian Psychometric Modeling presents a unified Bayesian approach across traditionally separate families of psychometric models. It shows that Bayesian techniques, as alternatives to conventional approaches, offer distinct and profound advantages in achieving many goals of psychometrics. Adopting a Bayesian approach can aid in unifying seemingly disparate—and sometimes conflicting—ideas and activities in psychometrics. This book explains both how to perform psychometrics using Bayesian methods and why many of the activities in psychometrics align with Bayesian thinking. The first part of the book introduces foundational principles and statistical models, including conceptual issues, normal distribution models, Markov chain Monte Carlo estimation, and regression. Focusing more directly on psychometrics, the second part covers popular psychometric models, including classical test theory, factor analysis, item response theory, latent class analysis, and Bayesian networks. Throughout the book, procedures are illustrated using examples primarily from educational assessments. A supplementary website provides the datasets, WinBUGS code, R code, and Netica files used in the examples.
