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Bayesian Analysis
The chapter explores the fundamental concepts and applications of Bayesian statistics. It begins with an introduction to basic terminologies like...
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Bayesian Analysis of the Data from PoGO+
PoGO+ is a Compton-scattering polarimeter, which measured the linear polarization of hard X-rays (∼20–170 keV) emitted by the Crab nebula/pulsar and...
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Bayesian analysis of linear regression models with autoregressive symmetrical errors and incomplete data
Observations collected over time are often autocorrelated rather than independent, and sometimes include incomplete information, for example censored...
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Bayesian analysis of Box-Cox transformation model for multi-state progression-free survival data
In this study, we address the inference problem associated with the Box-Cox transformation model when dealing with multi-state progression-free...
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Bayesian Multimodal Data Analytics: AnIntroduction
Bayesian methods for multimodal data have attracted the interest of researchers and practitioners in a variety of real-world applications. Indeed,...
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Bayesian Compendium
This book describes how Bayesian methods work. Aiming to demystify the approach, it explains how to parameterize and compare models while accounting...
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Data-driven risk analysis of nonlinear factor interactions in road safety using Bayesian networks
This paper aims to demonstrate nonlinear risk factor interactions based on a data-driven approach using a Bayesian network model, providing a road...
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Wavelet-based Bayesian approximate kernel method for high-dimensional data analysis
Kernel methods are often used for nonlinear regression and classification in statistics and machine learning because they are computationally cheap...
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Bayesian Modeling on Microbiome Data Analysis: Application to Subgingival Microbiome Study
The study of microbiome data has been widely used to investigate associations between the abundance of microbial taxa and human diseases. Identifying...
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Bayesian Analysis of Two-Part Latent Variable Model with Mixed Data
In analyzing semi-continuous data, two-part model is a widely appreciated tool, in which two components are enclosed to characterize the mixing...
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On A New Extended Log-Normal Distribution: Properties, Regression, Bayesian Regression, and Data Analysis
This article introduces and investigates the Marshall-Olkin Topp-Leone log-normal (MOTLLN) distribution, a novel extension of the log-normal...
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Scalable Bayesian Tensor Ring Factorization for Multiway Data Analysis
Tensor decompositions play a crucial role in numerous applications related to multi-way data analysis. By employing a Bayesian framework with...
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Graph-Guided Bayesian Factor Model for Integrative Analysis of Multi-modal Data with Noisy Network Information
There is a growing body of literature on factor analysis that can capture individual and shared structures in multi-modal data. However, few of these...
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Data-driven analysis of the beauty hadron production in pp collisions at the LHC with Bayesian unfolding
Heavy flavour production in proton-proton (pp) collisions provides insights into the fundamental properties of Quantum Chromodynamics (QCD). Beauty...
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A discrete extension of the exponential type II distribution: statistical characterizations, reliability analysis, and Bayesian vs. non-Bayesian inferences for random right-censored and complete count data
This study focuses on applying a discrete distribution designed to effectively model both complete and censored data. The proposed distribution...
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Estimation of the Radial Tungsten Concentration Profiles from Soft X-ray Measurements at WEST with Bayesian Integrated Data Analysis
The accumulation of heavy impurities like tungsten in the plasma core of fusion devices can cause significant radiative power losses or even lead to...
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Bayesian Multivariate Analysis of Mixed Data
Graphical models provide an effective tool to represent conditional independences among variables. While this class of models has been extensively...
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Evaluating the Performance of Bayesian Approach for Imputing Missing Data under different Missingness Mechanism
In the realm of data analysis, missing data pose a significant challenge, requiring robust imputation methods to ensure the integrity and reliability...
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Variational Bayesian analysis of survival data using a log-logistic accelerated failure time model
The log-logistic regression model is one of the most commonly used accelerated failure time (AFT) models in survival analysis, for which statistical...
