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Bayesian Estimation of the Stress-Strength Reliability Based on Generalized Order Statistics for Pareto Distribution
Published 2023-01-01“…The aim of this paper is to obtain a Bayesian estimator of stress-strength reliability based on generalized order statistics for Pareto distribution. …”
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162
Interacting Large Language Model Agents Bayesian Social Learning Based Interpretable Models
Published 2025-01-01Subjects: “…Bayesian social learning…”
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163
Sample size estimation for task-related functional MRI studies using Bayesian updating
Published 2025-01-01Subjects: Get full text
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164
Off-grid DOA estimation algorithm based on unitary transform and sparse Bayesian learning
Published 2017-06-01Subjects: Get full text
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165
Bayesian Estimations under the Weighted LINEX Loss Function Based on Upper Record Values
Published 2021-01-01“…Next, we compared the performance of the proposed method (WLINEX) in this work with Bayesian estimation using the LINEX loss function, Bayesian estimation using the squared-error (SEL) loss function, and maximum likelihood estimation (MLE). …”
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166
Discrepancies Between Bayesian Vancomycin Models Can Affect Clinical Decisions in the Critically Ill
Published 2022-01-01Get full text
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167
A comparison of Bayesian and frequentist confidence intervals in the presence of a late Universe degeneracy
Published 2025-02-01Get full text
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168
Relaxing the confirmatory factor model in the Big Five: Exploratory, Bayesian, and machine learning approaches
Published 2025-01-01“…Three methods have been devised to relax this assumption: Exploratory Structural Equation Model (SEM), Bayesian SEM, and Regularized SEM. Each of these allow for the existence of cross-loadings, but a direct comparison of these methods is missing from the literature. …”
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169
Bayesian Estimation and Prediction for Flexible Weibull Model under Type-II Censoring Scheme
Published 2013-01-01“…We have developed the Bayesian estimation procedure for flexible Weibull distribution under Type-II censoring scheme assuming Jeffrey's scale invariant (noninformative) and Gamma (informative) priors for the model parameters. …”
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170
Modified complex multitask Bayesian compressive sensing using Laplacian scale mixture prior
Published 2022-07-01“…Abstract Bayesian compressive sensing (BCS) is an important sub‐class of sparse signal reconstruction algorithms. …”
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171
Estimation of Urban Link Travel Time Distribution Using Markov Chains and Bayesian Approaches
Published 2018-01-01“…In this case, the study develops a Bayesian approach based on particle filter framework for link TTD estimation using real-time and historical travel time observations from FCD. …”
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172
Within-host bayesian joint modeling of longitudinal and time-to-event data of Leishmania infection.
Published 2024-01-01“…In this work, we present a Bayesian joint model of longitudinal and time-to-event data of Leishmania infection that considers the interplay between key drivers of the disease process: pathogen load, antibody level, and disease. …”
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173
A multidimensional Bayesian IRT method for discovering misconceptions from concept test data
Published 2025-01-01“…We explore the performance of the Bayesian MNCM on synthetic data and find that it is able to recover multidimensional item parameters consistently at achievable sample sizes. …”
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174
Use of Bayesian Inference to Correlate In Vitro Embryo Production and In Vivo Fertility in Zebu Bulls
Published 2011-01-01“…The objective of this experiment was to test in vitro embryo production (IVP) as a tool to estimate fertility performance in zebu bulls using Bayesian inference statistics. Oocytes were matured and fertilized in vitro using sperm cells from three different Zebu bulls (V, T, and G). …”
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Approach for information systems security situation evaluation using improved FAHP and Bayesian network
Published 2009-01-01Subjects: Get full text
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177
Composite Bayesian Optimization in function spaces using NEON—Neural Epistemic Operator Networks
Published 2024-11-01“…We showcase the utility of this method for sequential decision-making by examining the problem of composite Bayesian Optimization (BO), where we aim to optimize a function $$f=g\circ h$$ f = g ∘ h , where $$h:X\rightarrow C(\mathscr {Y},{\mathbb {R}}^{d_s})$$ h : X → C ( Y , R d s ) is an unknown map which outputs elements of a function space, and $$g: C(\mathscr {Y},{\mathbb {R}}^{d_s})\rightarrow {\mathbb {R}}$$ g : C ( Y , R d s ) → R is a known and cheap-to-compute functional. …”
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178
Predicting Large-Scale WLAN Traffic via Granger Causality Based Bayesian Network
Published 2015-08-01Subjects: Get full text
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179
Scenario construction and evolutionary analysis of nonconventional public health emergencies based on Bayesian networks
Published 2025-02-01Subjects: Get full text
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180
Project Portfolio Resource Risk Assessment considering Project Interdependency by the Fuzzy Bayesian Network
Published 2020-01-01“…This paper presents a methodology by using a fuzzy Bayesian network to assess the project portfolio resource risk, determine critical resource risk factors, and propose risk-reduction strategies. …”
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