Results 261 to 270 of about 2,020,572 (302)

Bayesian dynamic system estimation

53rd IEEE Conference on Decision and Control, 2014
This paper is directed at developing methods for delivering Bayesian estimates of dynamic system parameters, and functions of them (such as frequency response), for general problems. There are several motivations for the work. One is that due to computational load problems, such methods for Bayesian estimation do not currently exist.
Brett Ninness, Khoa T. Tran, Christopher M. Kellett   +2 more
openaire   +1 more source

Estimation in Bayesian Disease Mapping

Biometrics, 2004
SummaryRecent work on Bayesian inference of disease mapping models discusses the advantages of the fully Bayesian (FB) approach over its empirical Bayes (EB) counterpart, suggesting that FB posterior standard deviations of small‐area relative risks are more reflective of the uncertainty associated with the relative risk estimation than counterparts ...
MacNab, Ying C., Farrell, Patrick J., Gustafson, Paul, Wen, Sijin   +3 more
openaire   +2 more sources

Bayesian Quantile Estimation in Deconvolution

2022
Estimating quantiles of a population is a fundamental problem in nonparametric statistics, with high practical relevance. This note deals, from a Bayesian point of view, with quantile estimation in deconvolution problems with known error distribution. We pursue the analysis for error distributions whose characteristic functions decay polynomially fast,
openaire   +3 more sources

BITE: A Bayesian Intensity Estimator

Computational Statistics, 2003
The BITE software package is described which is designed for the analysis of multivariate survival data. BITE is based on hierarchical Bayes models and Markov Chain Monte Carlo techniques. Analysis of heart transplant data is considered as an example.
openaire   +2 more sources

A Bayesian perspective on magnitude estimation

Trends in Cognitive Sciences, 2015
Our representation of the physical world requires judgments of magnitudes, such as loudness, distance, or time. Interestingly, magnitude estimates are often not veridical but subject to characteristic biases. These biases are strikingly similar across different sensory modalities, suggesting common processing mechanisms that are shared by different ...
Petzschner, Frederike H, Glasauer, Stefan, Stephan, Klaas E   +2 more
openaire   +4 more sources

Bayesian estimation for rheological MRI

SPIE Proceedings, 2003
Magnetic resonance imaging (MRI) is used, in addition to its well known medical and biological applications, for the study of a variety of fluid dynamic phenomena. This paper focuses on the MRI imaging of liquid foams to aid the study of their temporal and spatial dynamics.
Fabien Feron, Ken D. Sauer
openaire   +2 more sources

E-Bayesian and Hierarchical Bayesian Estimation of Inverse Rayleigh Distribution

American Journal of Mathematical and Management Sciences, 2022
E I Abdul-Sathar
exaly  

Bayesian Estimation

2017
Matthew S. Johnson, Sandip Sinharay
openaire   +2 more sources

E‐Bayesian estimation and associated properties of simple step–stress model for exponential distribution based on type‐II censoring

Quality and Reliability Engineering International, 2021
Hassan Okasha, Mohammed Albassam, Mazen Nassar   +2 more
exaly  

The evidence interval and the Bayesian evidence value: On a unified theory for Bayesian hypothesis testing and interval estimation

British Journal of Mathematical and Statistical Psychology, 2022
Riko Kelter
exaly