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Bayesian estimation

by Nationaal Lucht- En Ruimtevaartlaboratorium, H. A. P. Blom, E. A. Bloem, Multitarget Tracking , 2006
"... information processing, and control ..."
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information processing, and control

Bayesian Estimations ☆

by Sebastian Sienknecht, Friedrich Schiller, Sebastian Sienknecht , 2010
"... www.jenecon.de ..."
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www.jenecon.de

Bayesian Estimation of CIR Model

by Xiaoxia Feng , Dejun Xie - Journal of Data Science , 2012
"... Abstract: This article concerns the Bayesian estimation of interest rate models based on Euler-Maruyama approximation. Assume the short term interest rate follows the CIR model, an iterative method of Bayesian estimation is proposed. Markov Chain Monte Carlo simulation based on Gibbs sampler is use ..."
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Abstract: This article concerns the Bayesian estimation of interest rate models based on Euler-Maruyama approximation. Assume the short term interest rate follows the CIR model, an iterative method of Bayesian estimation is proposed. Markov Chain Monte Carlo simulation based on Gibbs sampler

Estimating Continuous Distributions in Bayesian Classifiers

by George H. John , et al. , 1995
"... ..."
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Bayesian Estimation Of Motion Vector Fields

by Janusz Konrad, Eric Dubois - IEEE Trans. Pattern Anal. Machine Intell , 1992
"... This paper presents a new approach to the estimation of two-dimensional motion vector fields from time-varying images. The approach is stochastic, both in its formulation and in the solution method. The formulation involves the specification of a deterministic structural model, along with stochastic ..."
Abstract - Cited by 137 (19 self) - Add to MetaCart
This paper presents a new approach to the estimation of two-dimensional motion vector fields from time-varying images. The approach is stochastic, both in its formulation and in the solution method. The formulation involves the specification of a deterministic structural model, along

BAYESIAN ESTIMATION FOR THE MULTIFRACTALITY PARAMETER

by Herwig Wendt, Nicolas Dobigeon, Jean-yves Tourneret, Patrice Abry
"... Multifractal analysis has matured into a widely used signal and image processing tool. Due to the statistical nature of multifractal processes (strongly non-Gaussian and intricate dependence) the accurate estimation of multifractal parameters is very challenging in situations where the sample size i ..."
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is small (notably including a range of biomedical applications) and currently available estimators need to be improved. To overcome such limitations, the present contribution proposes a Bayesian estimation procedure for the multifractality (or intermittence) parameter. Its originality is threefold: First

Bayesian Estimation Supersedes the t Test

by John K. Kruschke
"... This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Bayesian estimation for 2 groups provides complete distributions of credible valu ..."
Abstract - Cited by 12 (2 self) - Add to MetaCart
This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Bayesian estimation for 2 groups provides complete distributions of credible

Bayesian estimation in homodyne interferometry

by Stefano Olivares, Matteo G. A. Paris , 901
"... Abstract. We address phase-shift estimation by means of squeezed vacuum probe and homodyne detection. We analyze Bayesian estimator, which is known to asymptotically saturate the classical Cramér-Rao bound to the variance, and discuss convergence looking at the a posteriori distribution as the numbe ..."
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Abstract. We address phase-shift estimation by means of squeezed vacuum probe and homodyne detection. We analyze Bayesian estimator, which is known to asymptotically saturate the classical Cramér-Rao bound to the variance, and discuss convergence looking at the a posteriori distribution

Bayesian density estimation and inference using mixtures.

by Michael D Escobar , Mike West - J. Amer. Statist. Assoc. , 1995
"... JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about J ..."
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JSTOR, please contact support@jstor.org. We describe and illustrate Bayesian inference in models for density estimation using mixtures of Dirichlet processes. These models provide natural settings for density estimation and are exemplified by special cases where data are modeled as a sample from

Bayesian Estimators As Voting Rules

by Lirong Xia
"... Abstract We investigate the fairness of Bayesian estimators (BEs) by viewing them as (irresolute) voting rules and evaluating them by satisfaction of desirable social choice axioms. We characterize the class of BEs that satisfy neutrality by the class of BEs with neutral structures. We prove that a ..."
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Abstract We investigate the fairness of Bayesian estimators (BEs) by viewing them as (irresolute) voting rules and evaluating them by satisfaction of desirable social choice axioms. We characterize the class of BEs that satisfy neutrality by the class of BEs with neutral structures. We prove
Results 1 - 10 of 13,177