Results 11 to 20 of about 3,605,404 (198)
On the implementation of local probability matching priors for interest parameters [PDF]
Biometrika, 2005 Summary: Probability matching priors are priors for which the posterior probabilities of certain specified sets are exactly or approximately equal to their coverage probabilities. These priors arise as solutions of partial differential equations that may be difficult to solve, either analytically or numerically. Recently, \textit{R. A.
Sweeting, TJ, Trevor J. Sweeting
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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.
Catia Scricciolo
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Improved stereo image matching using mutual information and hierarchical prior probabilities [PDF]
Object recognition supported by user interaction for service robots, 2003 Mutual information (MI) has shown promise as an effective stereo matching measure for images affected by radiometric distortion. This is due to the robustness of MI against changes in illumination. However MI-based approaches are particularly prone to the generation of false matches due to the small statistical power of the matching windows.
Clinton Fookes +2 more
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On the uniqueness of probability matching priors [PDF]
, 2007 Probability matching priors are priors for which Bayesian and frequentist inference, in the form of posterior quantiles, or confidence intervals, agree to some order of approximation. These priors are constructed by solving a first order partial differential equation, that may be difficult to solve.
Staicu, A-M, Reid, Nancy
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Energies, 2022 In this paper, a competing risks model with dependent causes of failure is considered under left-truncated and right-censoring scenario. When the dependent failure causes follow a Marshall–Olkin bivariate exponential distribution, estimation of model ...
Zhiyuan Zuo, Liang Wang, Yuhlong Lio
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Multiple comparisons of precipitation variations in different areas using simultaneous confidence intervals for all possible ratios of variances of several zero-inflated lognormal models [PDF]
PeerJ, 2021 Flash flooding and landslides regularly cause injury, death, and homelessness in Thailand. An advancedwarning system is necessary for predicting natural disasters, and analyzing the variability of daily precipitation might be usable in this regard ...
Patcharee Maneerat, Sa-Aat Niwitpong
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Using history matching for prior choice [PDF]
, 2018 It can be important in Bayesian analyses of complex models to construct informative prior distributions which reflect knowledge external to the data at hand.
Wang Xueou +12 more
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Sensors, 2018 This work presents a visual information fusion approach for robust probability-oriented feature matching. It is sustained by omnidirectional imaging, and it is tested in a visual localization framework, in mobile robotics.
David Valiente +4 more
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Regularization, Bayesian Inference, and Machine Learning Methods for Inverse Problems
Entropy, 2021 Classical methods for inverse problems are mainly based on regularization theory, in particular those, that are based on optimization of a criterion with two parts: a data-model matching and a regularization term.
Ali Mohammad-Djafari
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Prior distribution elicitation [PDF]
, 2007 An overview of key issues associated with the elicitation of a prior probability distribution is provided. The nature of subjective probability is discussed, and the main causes of biased assessments are identified.
Lesley Walls +12 more
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