scholarly journals Advantage of Bayesian approach to geotechnical designing

2009 ◽  
Vol 41 (2) ◽  
pp. 83-93
Author(s):  
Kazimierz Garbulewski ◽  
Stanisław Jabłonowski ◽  
Simon Rabarijoely
Keyword(s):  
Bayesian Analysis ◽  
Bayesian Approach ◽  
Geotechnical Engineering ◽  
Soil Parameters ◽  
Geotechnical Parameters ◽  
The Bayesian Approach

Advantage of Bayesian approach to geotechnical designing The paper addresses the possibility of the Bayesian approach's application to geotechnical engineering. First the principal information on the Bayesian analysis has been presented and its applications to estimate the soil parameters based on the CPT/DMT tests at SGGW Campus in Warsaw afterwards. The CPT/DMT tests had been carried out in order to recognize the geotechnical conditions in the foundations of design campus buildings. The data from two layers of glacial boulder clays have been analysed. The results demonstrate that the Bayesian approach is a useful tool in evaluation of ground properties and estimation of the geotechnical parameters in specified circumstances.

A Survey of Bayesian Data Mining

Data Mining ◽  
2011 ◽  
pp. 1-26 ◽  
Author(s):  
Stefan Arnborg
Keyword(s):  
Data Mining ◽  
Bayesian Analysis ◽  
Graphical Models ◽  
Bayesian Approach ◽  
Data Sets ◽  
Media Distribution ◽  
Dirichlet Prior ◽  
Approach Problem ◽  
The Bayesian Approach ◽  
Selection Of

This chapter reviews the fundamentals of inference, and gives a motivation for Bayesian analysis. The method is illustrated with dependency tests in data sets with categorical data variables, and the Dirichlet prior distributions. Principles and problems for deriving causality conclusions are reviewed, and illustrated with Simpson’s paradox. The selection of decomposable and directed graphical models illustrates the Bayesian approach. Bayesian and EM classification is shortly described. The material is illustrated on two cases, one in personalization of media distribution, one in schizophrenia research. These cases are illustrations of how to approach problem types that exist in many other application areas.

Bayesian Procedures for Discriminating Among Hypotheses With Discrete Distributions: Inheritance in the Tetraploid Astilbe biternata

Genetics ◽  
1997 ◽  
Vol 147 (4) ◽  
pp. 1933-1942
Author(s):  
Matthew S Olson
Keyword(s):  
Bayesian Analysis ◽  
Prior Knowledge ◽  
Bayesian Approach ◽  
Discrete Distributions ◽  
Southern Appalachians ◽  
Herbaceous Plant ◽  
Bayesian Procedures ◽  
Disomic Inheritance ◽  
Cytogenetic Evidence ◽  
The Bayesian Approach

Abstract Discrimination between disomic and tetrasomic inheritance aids in determining whether tetraploids originated by allotetraploidy or autotetraploidy, respectively. Past assessments of inheritance in tetraploids have used analyses whereby each inheritance hypothesis is tested independently. I present a Bayesian analysis that is appropriate for discriminating among several inheritance hypotheses and can be used in any case where hypotheses are defined by discrete distributions. The Bayesian approach incorporates prior knowledge of the probability of occurrence of disomic and tetrasomic hypotheses so that the results of the analysis are not biased by the fact that there is a single tetrasomic hypothesis and multiple disomic hypotheses. This analysis is used to interpret data from crosses in the tetraploid Astilbe biternata, a herbaceous plant native to the southern Appalachians. The progeny ratios from all crosses favored the hypothesis of disomic inheritance at both the PGM and slow-PGI loci. These results support earlier cytogenetic evidence for the allotetraploid origin of Astilbe biternata.

Testing for Collinearity using Bayesian Analysis

2021 ◽  
pp. 109634802199084
Author(s):  
A. George Assaf ◽  
Mike Tsionas
Keyword(s):  
Bayesian Analysis ◽  
Bayesian Approach ◽  
Attractive Alternative ◽  
Variance Inflation Factor ◽  
Regression Parameters ◽  
Kolmogorov Smirnov ◽  
Inflation Factor ◽  
The Difference ◽  
The Bayesian Approach ◽  
Smirnov Test

Testing for collinearity continues to be a controversial issue in the literature. Multicollinearity detection criteria, such as the variance inflation factor, often fail to detect the true extent of multicollinearity. In this article, we propose utilizing the Bayesian approach as an attractive alternative. Under the Bayesian approach, we recommend comparing the marginal posterior of regression parameters under two different priors. If the difference in the posterior under these two priors is pronounced, one can surmise that collinearity is harmful. The Kolmogorov–Smirnov test can also be used as further evidence to confirm whether the posterior difference is significant.

scholarly journals The promise of Bayesian analysis for prominence seismology

2013 ◽  
Vol 8 (S300) ◽  
pp. 393-394 ◽  
Author(s):  
Iñigo Arregui ◽  
Andrés Asensio Ramos ◽  
Antonio J. Díaz
Keyword(s):  
Bayesian Analysis ◽  
Bayesian Approach ◽  
Model Comparison ◽  
Physical Models ◽  
Physical Parameters ◽  
Solar Prominence ◽  
Bayesian Techniques ◽  
The Bayesian Approach

AbstractWe propose and use Bayesian techniques for the determination of physical parameters in solar prominence plasmas, combining observational and theoretical properties of waves and oscillations. The Bayesian approach also enables to perform model comparison to assess how plausible alternative physical models/mechanisms are in view of data.

scholarly journals Constraining absolute chronologies with the application of Bayesian analysis

ACTA IMEKO ◽  
2016 ◽  
Vol 5 (2) ◽  
pp. 14 ◽  
Author(s):  
Francesco Maspero ◽  
Emanuela Sibilia ◽  
Marco Martini
Keyword(s):  
Bayesian Analysis ◽  
Bayesian Statistics ◽  
Case Studies ◽  
Bayesian Approach ◽  
Common Language ◽  
Multiple Data ◽  
The Common ◽  
The Bayesian Approach

<p class="Abstract"><span lang="EN-US">In this work the application of Bayesian statistics to archaeological problems will be discussed. In particular, three case studies will be analyzed, each presenting complex interpretative scenarios, and the most suitable way to solve them. It will be shown that the Bayesian approach allows to refine a dating when in presence of multiple data, even from different dating techniques. The Bayesian approach is presented as the common language between physicists, archaeologists and statisticians to perform more accurate evaluations on stratigraphies and chronologies.</span></p>

scholarly journals A very simple introduction to Bayesian statistics: From coin flips to insight

2020 ◽  
Author(s):  
Daniel Zuckerman
Keyword(s):  
Biological Sciences ◽  
Bayesian Analysis ◽  
Bayesian Statistics ◽  
Bayesian Approach ◽  
Prior Information ◽  
Model Parameters ◽  
Short Article ◽  
Absolute Minimum ◽  
Wet Lab ◽  
The Bayesian Approach

Bayesian statistical analyses are a growing part of the chemical and biological sciences for several reasons. Most importantly, the Bayesian approach of predicting underlying models based on data corresponds naturally with examination of complex systems, whether using wet-lab or computational means. The Bayesian structure also provides a systematic basis for estimating uncertainty in model parameters and permits incorporation of prior information in a quantitative and consistent way. While easy to state in words, these strengths of Bayesian analysis can be difficult to assimilate for beginners. This short article presents essential Bayesian concepts using very simple examples and the absolute minimum mathematics needed to maintain rigor.

scholarly journals The Bayesian Approach and the Results of the ISAR-REACT 5 Trial

2021 ◽  
Vol 14 (2) ◽  
pp. 231-232
Author(s):  
Adnan Kastrati ◽  
Alexander Hapfelmeier
Keyword(s):  
Bayesian Approach ◽  
The Bayesian Approach

scholarly journals Bayesian analysis of data from segmented super-resolution images for quantifying protein clustering

2020 ◽  
Vol 22 (3) ◽  
pp. 1107-1114
Author(s):  
Tina Košuta ◽  
Marta Cullell-Dalmau ◽  
Francesca Cella Zanacchi ◽  
Carlo Manzo
Keyword(s):  
Bayesian Analysis ◽  
Relative Abundance ◽  
Bayesian Approach ◽  
Super Resolution ◽  
Molecular Aggregates ◽  
Protein Clustering ◽  
Precise Quantification

A Bayesian approach enables the precise quantification of the relative abundance of molecular aggregates of different stoichiometry from segmented super-resolution images.

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