Limits of the Application of Bayesian Modeling to Perception/ (Record no. 12491)

MARC details
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fixed length control field 01445nab a2200229 4500
005 - DATE & TIME
control field 20220803092534.0
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100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Luccio, Riccardo
245 ## - TITLE STATEMENT
Title Limits of the Application of Bayesian Modeling to Perception/
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc sage
Date of publication, distribution, etc 2019
300 ## - PHYSICAL DESCRIPTION
Pages Vol 48, Issue 10, 2019: ( 901-917 p.).
520 ## - SUMMARY, ETC.
Summary, etc The general lines of Bayesian modeling (BM) in the study of perception are outlined here. The main thesis argued here is that BM works well only in the so-called secondary processes of perception, and in particular in cases of imperfect discriminability between stimuli, or when a judgment is required, or in cases of multistability. In cases of “primary processes,” on the other hand, it is often arbitrary and anyway superfluous, as with the laws of Gestalt. However, it is pointed out that in these latter cases, simpler and more well-established methodologies already exist, such as signal detection theory and individual choice theory. The frequent recourse to arbitrary values of a priori probabilities is also open to question.
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Subject Bayes’ rule,
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Subject imperfect discriminability,
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Subject assignment of probabilities,
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Subject SDT
773 0# - HOST ITEM ENTRY
Host Biblionumber 12374
Host Itemnumber 16462
Place, publisher, and date of publication Sage,
Title Perception
International Standard Serial Number 1468-4233
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1177/0301006619868125
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Koha item type Articles
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