Results 71 to 80 of about 527,420 (298)
BayesDensity.jl: Bayesian nonparametric density estimation in Julia
SoftwareXBayesDensity.jl is a Julia package for Bayesian nonparametric estimation of smooth univariate densities. The package provides a unified interface to a range of well-established models from the statistical literature, supporting both Markov chain Monte ...
Oskar Høgberg Simensen
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Seismic Signal Compression Using Nonparametric Bayesian Dictionary Learning via Clustering
Algorithms, 2017 We introduce a seismic signal compression method based on nonparametric Bayesian dictionary learning method via clustering. The seismic data is compressed patch by patch, and the dictionary is learned online.
Xin Tian, Song Li
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Gaussian Process Panel Modeling—Machine Learning Inspired Analysis of Longitudinal Panel Data
Frontiers in Psychology, 2020 In this article, we extend the Bayesian nonparametric regression method Gaussian Process Regression to the analysis of longitudinal panel data. We call this new approach Gaussian Process Panel Modeling (GPPM).
Julian D. Karch +4 more
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Biological Diversity, EarlyView.The first inventory of ants from the Xisha Islands of the South China Sea was compiled, revealing 21 species: 70% native and 30% exotic. Anthropogenic disturbance primarily drove exotic colonization, whereas island area showed weak positive effects on species richness. Most ants were omnivorous, with key mutualistic and seed‐dispersal roles.
Hua‐Yan Chen +4 more
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Adaptive Bayesian Nonparametric Regression via Stationary Smoothness Priors
MathematicsA procedure for Bayesian nonparametric regression is described that automatically adjusts the degree of smoothing as the curvature of the underlying function changes.
Justin L. Tobias
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A Bayesian Nonparametric Approach to Reliability
The Annals of Statistics, 1981 Abstract : It is suggested that problems in a reliability context may be handled by a Bayesian non-parametric approach. A stochastic process is defined whose sample paths may be assumed to be either increasing hazard rates or decreasing hazard rates by properly choosing the parameter functions of the process.
Dykstra, R. L., Laud, Purushottam
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Nonparametric Bayesian Clustering Ensembles [PDF]
, 2010 Forming consensus clusters from multiple input clusterings can improve accuracy and robustness. Current clustering ensemble methods require specifying the number of consensus clusters. A poor choice can lead to under or over fitting. This paper proposes a nonparametric Bayesian clustering ensemble (NBCE) method, which can discover the number of ...
Pu Wang 0002 +2 more
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Business Strategy and the Environment, EarlyView.ABSTRACT This study investigates the structural and distributional factors that influence environmental performance in 27 European Union (EU) countries from 2010 to 2021, focusing especially on circular economy (CE) measures and the increasing use of artificial intelligence (AI)‐based analytical tools.
Cosimo Magazzino +3 more
wiley +1 more source
A Bayesian nonparametric meta‐analysis model [PDF]
Research Synthesis Methods, 2014 In a meta‐analysis, it is important to specify a model that adequately describes the effect‐size distribution of the underlying population of studies. The conventional normal fixed‐effect and normal random‐effects models assume a normal effect‐size population distribution, conditionally on parameters and covariates.
Karabatsos, George +2 more
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Chronic Diseases and Translational Medicine, EarlyView.The Vital Conditions Framework. Graphical representation of the Vital Conditions for Health Framework with seven domains. Images used with permission from The Rippel Foundation: An Introduction to the Vital Conditions for Health and Well‐Being. https://rippel.org/events/webinar-an-introduction-to-the-vital-conditions-for-health-and-well-being/. Federal
Stephanie Kjelstrom +4 more
wiley +1 more source