Prior Probabilities

Prior Probabilities (1968)

by Edwin T. Jaynes

Venue:	IEEE Transactions on Systems Science and Cybernetics
Citations:	133 - 3 self

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Datum	Value	Source
TITLE	Prior Probabilities	user correction - Legacy Corrections
AUTHOR NAME	Edwin T. Jaynes	SVM HeaderParse 0.1
AUTHOR AFFIL	Department of Physics, Washington University, St. Louis, Missouri	SVM HeaderParse 0.2
ABSTRACT	e case of location and scale parameters, rate constants, and in Bernoulli trials with unknown probability of success. In realistic problems, both the transformation group analysis and the principle of maximum entropy are needed to determine the prior. The distributions thus found are uniquely determined by the prior information, independently of the choice of parameters. In a certain class of problems, therefore, the prior distributions may now be claimed to be fully as "objective" as the sampling distributions. I. Background of the problem Since the time of Laplace, applications of probability theory have been hampered by difficulties in the treatment of prior information. In realistic problems of decision or inference, we often have prior information which is highly relevant to the question being asked; to fail to take it into account is to commit the most obvious inconsistency of reasoning and may lead to absurd or dangerously misleading results. As an extreme examp	user correction - Legacy Corrections
YEAR	1968	INFERENCE
VENUE	IEEE Transactions on Systems Science and Cybernetics	INFERENCE
VENUE TYPE	JOURNAL	INFERENCE
PAGES	227--241	INFERENCE
VOLUME	4	INFERENCE
CITATIONS	26 found	ParsCit 1.0