Results 41 to 50 of about 11,544,586 (297)

A Bayesian method of evaluating discomfort due to glare: the effect of order bias from a large glare source [PDF]

open access: yes, 2018
Replicating scientific findings is a fundamental aspect of research. However, in studies of discomfort due to glare, it is difficult to make comparisons between the results of different experiments since the statistical tests usually reported do not ...
Cheung, T.   +4 more
core   +1 more source

A Bayesian Approach to Fault Identification in the Presence of Multi-component Degradation

open access: yesInternational Journal of Prognostics and Health Management, 2017
Fault diagnosis typically consists of fault detection, isolation and identification. Fault detection and isolation determine the presence of a fault in a system and the location of the fault.
Yufei Lin, Skaf Zakwan, Ian Jennions
doaj   +1 more source

Bayesian Varying-coefficient Models using Adaptive Regression Splines [PDF]

open access: yes, 2000
Varying-coefficient models provide a flexible framework for semi- and nonparametric generalized regression analysis. We present a fully Bayesian B-spline basis function approach with adaptive knot selection.
Ludwig Fahrmeir   +3 more
core   +1 more source

Bayesian Computational Methods [PDF]

open access: yes, 2011
In this chapter, we will first present the most standard computational challenges met in Bayesian Statistics, focussing primarily on mixture estimation and on model choice issues, and then relate these problems with computational solutions. Of course, this chapter is only a terse introduction to the problems and solutions related to Bayesian ...
openaire   +6 more sources

Bayesian Methods for Graph Clustering [PDF]

open access: yes, 2009
Networks are used in many scientific fields such as biology, social science, and information technology. They aim at modelling, with edges, the way objects of interest, represented by vertices, are related to each other. Looking for clusters of vertices, also called communities or modules, has appeared to be a powerful approach for capturing the ...
Latouche, Pierre   +2 more
openaire   +3 more sources

Objective Bayesian Estimation for Tweedie Exponential Dispersion Process

open access: yesMathematics, 2021
An objective Bayesian method for the Tweedie Exponential Dispersion (TED) process model is proposed in this paper. The TED process is a generalized stochastic process, including some famous stochastic processes (e.g., Wiener, Gamma, and Inverse Gaussian ...
Weian Yan   +3 more
doaj   +1 more source

Bayesian Methods in the Field of Rehabilitation

open access: yesAmerican Journal of Physical Medicine & Rehabilitation, 2019
Abstract Bayesian techniques, as an alternative method of statistical analysis in rehabilitation studies, have some advantages such as handling small sample sizes, allowing incorporation of previous experience of the researchers or clinicians, being suitable for different kinds of studies, and managing highly complex models.
Quintela-del-Río, Alejandro   +5 more
openaire   +3 more sources

Reconstructing enzyme evolution by protein engineering

open access: yesFEBS Letters, EarlyView.
Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler   +2 more
wiley   +1 more source

A General Method for Robust Bayesian Modeling

open access: yes, 2018
Robust Bayesian models are appealing alternatives to standard models, providing protection from data that contains outliers or other departures from the model assumptions.
Chong Wang   +3 more
core   +1 more source

A Continuation Method in Bayesian Inference

open access: yesSIAM/ASA Journal on Uncertainty Quantification, 2023
We present a continuation method that entails generating a sequence of transition probability density functions from the prior to the posterior in the context of Bayesian inference for parameter estimation problems. The characterization of transition distributions, by tempering the likelihood function, results in a homogeneous nonlinear partial integro-
openaire   +2 more sources

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