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Economical Group Chain Sampling Plans for Weibull Distribution Using Bayesian Approach
The paper focuses on the economic design of group chain sampling plans (GChSP) for the Weibull distribution using Bayesian methodology. The GChSP is...
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A Bayesian approach to modeling topic-metadata relationships
The objective of advanced topic modeling is not only to explore latent topical structures, but also to estimate relationships between the discovered...
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Semiparametric regression modelling of current status competing risks data: a Bayesian approach
The current status censoring takes place in survival analysis when the exact event times are not known, but each individual is monitored once for...
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A Bayesian approach for clustering and exact finite-sample model selection in longitudinal data mixtures
We consider mixtures of longitudinal trajectories, where one trajectory contains measurements over time of the variable of interest for one...
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A flexible Bayesian variable selection approach for modeling interval data
Interval datasets are not uncommon in many disciplines including medical experiments, econometric studies, environmental studies etc. For modeling...
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Bayesian Scan Statistics
In this chapter we describe Bayesian scan statistics, a class of methods which build both on the prior literature on scan statistics and on Bayesian...
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Multi-pass Bayesian estimation: a robust Bayesian method
The prior plays a central role in Bayesian inference but specifying a prior is often difficult and a prior considered appropriate by a modeler may be...
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Topp–Leone Poisson Exponential Distribution: A Classical and Bayesian Approach
In this paper, we propose a new three-parameter lifetime distribution, which has increasing, decreasing and constant failure rate. The new...
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Semiparametric Bayesian approach to assess non-inferiority with assay sensitivity in a three-arm trial with normally distributed endpoints
The non-inferiority (NI) trial is designed to show that an experimental treatment is not worse than an active reference by more than a pre-specified...
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A Bayesian Approach for Data-Driven Dynamic Equation Discovery
Many real-world scientific and engineering processes are governed by complex nonlinear interactions, and differential equations are commonly used to...
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A hybrid deterministic–deterministic approach for high-dimensional Bayesian variable selection with a default prior
Identifying relevant variables among numerous potential predictors has been of primary interest in modern regression analysis. While stochastic...
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Sample Size for Estimating Disease Prevalence in Free-Ranging Wildlife Populations: A Bayesian Modeling Approach
A two-parameter model and a Bayesian statistical framework are proposed for estimating prevalence and determining sample size requirements for...
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A Bayesian variable selection approach to longitudinal quantile regression
The literature on variable selection for mean regression is quite rich, both in the classical as well as in the Bayesian setting. However, if the...
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A Modified Bayesian Optimization Approach for Determining a Training Set to Identify the Best Genotypes from a Candidate Population in Genomic Selection
Training set optimization is a crucial factor affecting the probability of success for plant breeding programs using genomic selection....
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Semiparametric transformation model in presence of cure fraction: a hierarchical Bayesian approach assuming the unknown hazards as latent factors
The class of semiparametric or transformation models has been presented in the literature as a promising alternative for the analysis of lifetime...
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Learning Bayesian Networks from Ordinal Data - The Bayesian Way
We propose a new Bayesian method for Bayesian network structure learning from ordinal data. Our Bayesian method is similar to a recently proposed...
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A new Bayesian discrepancy measure
The aim of this article is to make a contribution to the Bayesian procedure of testing precise hypotheses for parametric models. For this purpose, we...
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The expectation–maximization approach for Bayesian additive Cox regression with current status data
In this paper, we propose a Bayesian additive Cox model for analyzing current status data based on the expectation–maximization variable selection...
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Bayesian Alternatives
The current discussion in psychological research methods and applied statistics has seen increasingly forceful requests to complement or even replace...
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Bayesian Methods
Earlier, Bayes’ theorem was introduced. Now Bayesian methods are described for inference and information, especially using Markov Chain Monte Carlo...