Results 41 to 50 of about 50,503 (261)
Airborne LIDAR-Derived Aboveground Biomass Estimates Using a Hierarchical Bayesian Approach
Remote Sensing, 2019 Conventional ground survey data are very accurate, but expensive. Airborne lidar data can reduce the costs and effort required to conduct large-scale forest surveys. It is critical to improve biomass estimation and evaluate carbon stock when we use lidar
Mengxi Wang +4 more
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Alexandria Engineering Journal, 2023 The hierarchical models have not only a major concern with developing computational schemes but also assist in inferring the multi-parameter problems.
Azeem Iqbal +2 more
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Bayesian hierarchical models for misaligned data: a simulation study
Statistica, 2015 In this paper, the problem of combining information from different data sources is considered. We focus our attention on spatially misaligned data, where available information (typically counts or rates from administrative sources) refers to spatial ...
Giulia Roli, Meri Raggi
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A normative model for Bayesian combination of subjective probability estimates
Judgment and Decision Making, 2023 Combining experts’ subjective probability estimates is a fundamental task with broad applicability in domains ranging from finance to public health. However, it is still an open question how to combine such estimates optimally.
Susanne Trick +2 more
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Hierarchical Bayesian models of delusion
Consciousness and Cognition, 2018 Researchers in the field of computational psychiatry have recently sought to model the formation and retention of delusions in terms of dysfunctions in a process of hierarchical Bayesian inference. I present a systematic review of such models and raise two challenges that have not received sufficient attention in the literature.
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HIERARCHICAL BAYESIAN MODELLING OF A FAMILY OF FRFS
Proceedings of the 14th International Workshop on Structural Health Monitoring, 2023 Population-based structural health monitoring (PBSHM) aims to share valuable information among members of a population, such as normal- and damage-condition data, to improve inferences regarding the health states of the members. Even when the population is comprised of nominally-identical structures, benign variations among the members will exist as a ...
Dardeno, T.A. +4 more
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Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
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Frontiers in Marine Science, 2016 We present a Hierarchical Bayesian version of Pollock's Closed Robust Design for studying the survival, temporary-migration, and abundance of marked animals.
Robert William Rankin +5 more
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Advanced Engineering Materials, EarlyView.We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
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Computation, 2022 Dependence in meta-analytic models can happen due to the same collected data or from the same researchers. The hierarchical Bayesian linear model in a meta-analysis that allows dependence in effect sizes is investigated in this paper.
Junaidi +3 more
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