Results 291 to 300 of about 5,701,088 (332)

Approximation of Improper Prior Measures by Prior Probability Measures

1965
It is known that, ordinarily, any admissible decision procedure for a statistical decision problem is, in a fairly strong sense, a limit of Bayes procedures, and in many cases such a limit must be a formal Bayes procedure with respect to a prior measure which may be improper (unbounded).
C. Stein
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Prior Probability

Encyclopedia of Machine Learning and Data Mining, 2011
Geoffrey I. Webb
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Prior Probability Estimation in Dynamically Imbalanced Data Streams

IEEE International Joint Conference on Neural Network, 2021
Despite the fact that real-life data streams may often be characterized by the dynamic changes in the prior class probabilities, there is a scarcity of articles trying to clearly describe and classify this problem as well as suggest new methods dedicated
Joanna Komorniczak, P. Zyblewski, P. Ksieniewicz   +2 more
semanticscholar   +1 more source

On probability matching priors

Canadian Journal of Statistics, 2008
AbstractFirst‐order probability matching priors are priors for which Bayesian and frequentist inference, in the form of posterior quantiles, or confidence intervals, agree to a second order of approximation. The authors show that the matching priors developed by Peers (1965) and Tibshirani (1989) are readily and uniquely implemented in a third‐order ...
Nancy Reid, Ana-Maria Staicu
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An informative prior probability distribution of the gompertz parameters for bayesian approaches in paleodemography.

American Journal of Physical Anthropology, 2016
OBJECTIVES In paleodemography, the Bayesian approach has been suggested to provide an effective means by which mortality profiles of past populations can be adequately estimated, and thus avoid problems of "age-mimicry" inherent in conventional ...
Tomohiko Sasaki, O. Kondo
semanticscholar   +1 more source

Making sense of prior probabilities in research [PDF]

Trends in Molecular Medicine, 2014
In a recent article, Gorski and Novella state that prior probabilities can be so low that putting them to the test makes no sense [1]. A few decades ago the randomised controlled trial (RCT) was demanded because of the low prior probability of clinical methods such as homeopathy.
Robert T. Mathie, Lex Rutten, Raj K Manchanda   +2 more
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Prior probability (the pretest best guess) affects predictive values of diagnostic tests.

Veterinary clinical pathology, 2011
Authors who publish evaluations of dichotomous (yes/no) diagnostic tests often include the predictive values of their test at a single prior probability (eg, the prevalence of the target disease within the evaluation data set).
H. Erb
semanticscholar   +1 more source

Prior probabilities and representational momentum

Visual Cognition, 2010
In many previous experiments on representational momentum (in which memory for the final location of a moving target is displaced in the direction of target motion), participants judged whether a probe presented after a target vanished was at the same location where that target vanished or at a different location.
Martina Lange, Timothy L. Hubbard
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Probability matching priors: a review

Journal of the Italian Statistical Society, 1999
In recent years, extensive work has been done concerning the derivation of noninformative prior distributions assuring approximate frequentist validity of Bayesian inferences. This paper provides a review of matching priors obtained via quantiles andvia the distribution function. Various matching criteria are described and discussed.
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Neglect as a disorder of prior probability

Neuropsychologia, 2008
Subjects with spatial neglect are slower and more variable in detecting visual targets, especially on the side opposite their brain injuries. These deficits can be seen by plotting cumulative distribution functions (CDF) of response times (RT). I demonstrate that dividing RT's by their means normalizes the RT CDF's of neglect subjects.
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