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Books on the topic 'A priori probability'

Author: Grafiati

Published: 4 June 2021

Last updated: 5 February 2022

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1

S, Korkhin Arnold, and SpringerLink (Online service), eds. Regression Analysis Under A Priori Parameter Restrictions. Springer Science+Business Media, LLC, 2012.

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2

Rahul, Mukerjee, ed. Probability Matching Priors: Higher Order Asymptotics. Springer New York, 2004.

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3

Datta, Gauri Sankar, and Rahul Mukerjee. Probability Matching Priors: Higher Order Asymptotics. Springer New York, 2004. http://dx.doi.org/10.1007/978-1-4612-2036-7.

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4

Wasserman, Larry. Prior envelopes based on belief functions. University of Toronto, Dept. of Statistics, 1987.

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5

Donnelly, Christl A. Statistical aspects of BSE and vCJD: Models for epidemics. Chapman & Hall/CRC, 2000.

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6

Knopov, Pavel S., and Arnold S. Korkhin. Regression Analysis Under A Priori Parameter Restrictions. Springer, 2011.

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7

Knopov, Pavel S., and Arnold S. Korkhin. Regression Analysis Under A Priori Parameter Restrictions. Springer, 2013.

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8

Hasan, Ali. In Defense of Rationalism about Abductive Inference. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198746904.003.0010.

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Laurence BonJour and more recently James Beebe have argued that the best way to defend the claim that abduction or inference to the best explanation is epistemically justified is the rationalist view that it is justified a priori. However, rationalism about abduction faces a number of challenges. This chapter focuses on one particular, highly influential objection, that there is no interpretation of probability available which is compatible with rationalism about abduction. The rationalist who wants to maintain a strong connection between epistemic justification and probability would do best t

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9

Probability Matching Priors: Higher Order Asymptotics. Springer, 2004.

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10

Sklar, Lawrence. Causation in Statistical Mechanics. Edited by Helen Beebee, Christopher Hitchcock, and Peter Menzies. Oxford University Press, 2010. http://dx.doi.org/10.1093/oxfordhb/9780199279739.003.0033.

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In statistical mechanics causation appears at the micro-level as the postulation that the full state of a system at one time can be specified by the dynamical state of all its micro-constituents (the positions and momenta of the molecules in a gas or, alternatively the wave function of these at one time), and that this state at one time generates, following the laws of dynamics (classical or quantum) the future dynamical state of the system characterized in these micro-constituent terms. So what is ‘non-causal’ in nature in explanations in statistical mechanics? This article explores two issue

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11

Venegas-Martinez, Francisco. Some studies on information measures and prior distributions. 1988.

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12

McCarthy, David. Probability in Ethics. Edited by Alan Hájek and Christopher Hitchcock. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199607617.013.36.

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It is natural to think that the most basic questions in ethical theory do not have much to do with probability. Given answers to these questions, we can try to extend them to cases involving probability, though this job might best be handled by more technical disciplines. This chapter is an argument for the opposite view. The major ethical problems to do with probability involve very little mathematics; many topics which seem to have nothing to do with probability are arguably all about probability; and thinking about various problems to do with probability can help solve analogous problems wh

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13

Isotropic probability measures in infinite dimensional spaces: Inverse problems/prior information/stochastic inversion. National Aeronautics and Space Administration, 1987.

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14

Donnelly, C. A., and N. M. Ferguson. Statistical Aspects of BSE and vCJD: Models for Epidemics (Monographs on Statistics and Applied Probability). Chapman & Hall/CRC, 1999.

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15

Butz, Martin V., and Esther F. Kutter. Top-Down Predictions Determine Perceptions. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780198739692.003.0009.

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While bottom-up visual processing is important, the brain integrates this information with top-down, generative expectations from very early on in the visual processing hierarchy. Indeed, our brain should not be viewed as a classification system, but rather as a generative system, which perceives something by integrating sensory evidence with the available, learned, predictive knowledge about that thing. The involved generative models continuously produce expectations over time, across space, and from abstracted encodings to more concrete encodings. Bayesian information processing is the key t

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16

Benton, Matthew A., John Hawthorne, and Dani Rabinowitz, eds. Knowledge, Belief, and God. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198798705.001.0001.

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Recent decades have seen a fertile period of theorizing within mainstream epistemology which has had a dramatic impact on how epistemology is done. Investigations into contextualist and pragmatic dimensions of knowledge suggest radically new ways of meeting skeptical challenges and of understanding the relation between the epistemological and practical environment. New insights from social epistemology and formal epistemology about defeat, testimony, a priority, probability, and the nature of evidence all have a potentially revolutionary effect on how we understand our epistemological place in

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17

Rau, Jochen. Statistical Physics and Thermodynamics. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199595068.001.0001.

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Statistical physics and thermodynamics describe the behaviour of systems on the macroscopic scale. Their methods are applicable to a wide range of phenomena: from heat engines to chemical reactions, from the interior of stars to the melting of ice. Indeed, the laws of thermodynamics are among the most universal ones of all laws of physics. Yet this subject can prove difficult to grasp. Many view thermodynamics as merely a collection of ad hoc recipes, or are confused by unfamiliar novel concepts, such as the entropy, which have little in common with the theories to which students have got accu

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