Mixed and mixture regression models for continuous bounded responses using the beta distribution
J Verkuilen, M Smithson - Journal of Educational and …, 2012 - journals.sagepub.com
Doubly bounded continuous data are common in the social and behavioral sciences.
Examples include judged probabilities, confidence ratings, derived proportions such as …
Examples include judged probabilities, confidence ratings, derived proportions such as …
A Digital Twin approach based on nonparametric Bayesian network for complex system health monitoring
This paper proposes a Digital Twin approach for health monitoring. In this approach, a
Digital Twin model based on nonparametric Bayesian network is constructed to denote the …
Digital Twin model based on nonparametric Bayesian network is constructed to denote the …
A Markov chain Monte Carlo approach for joint inference of population structure and inbreeding rates from multilocus genotype data
H Gao, S Williamson, CD Bustamante - Genetics, 2007 - academic.oup.com
Nonrandom mating induces correlations in allelic states within and among loci that can be
exploited to understand the genetic structure of natural populations (Wright 1965). For many …
exploited to understand the genetic structure of natural populations (Wright 1965). For many …
Federated conformal predictors for distributed uncertainty quantification
Conformal prediction is emerging as a popular paradigm for providing rigorous uncertainty
quantification in machine learning since it can be easily applied as a post-processing step to …
quantification in machine learning since it can be easily applied as a post-processing step to …
Sustainable energy management and control for Decarbonization of complex multi-zone buildings with renewable solar and geothermal energies using machine …
Although predictive control is an effective approach leveraging weather forecast information
to control indoor climate, forecast errors would lead to poor energy management decisions …
to control indoor climate, forecast errors would lead to poor energy management decisions …
Dynamic non-parametric mixture models and the recurrent chinese restaurant process: with applications to evolutionary clustering
Clustering is an important data mining task for exploration and visualization of different data
types like news stories, scientific publications, weblogs, etc. Due to the evolving nature of …
types like news stories, scientific publications, weblogs, etc. Due to the evolving nature of …
Clustering consistency with Dirichlet process mixtures
Dirichlet process mixtures are flexible nonparametric models, particularly suited to density
estimation and probabilistic clustering. In this work we study the posterior distribution …
estimation and probabilistic clustering. In this work we study the posterior distribution …
[HTML][HTML] An iterative Bayesian filtering framework for fast and automated calibration of DEM models
The nonlinear, history-dependent macroscopic behavior of a granular material is rooted in
the micromechanics between constituent particles and irreversible, plastic deformations …
the micromechanics between constituent particles and irreversible, plastic deformations …
Pipeline condition monitoring towards digital twin system: A case study
Condition monitoring is essential for the industrial pipelines in manufacturing to ensure the
consistent delivery of high quality products with efficient cost. Traditional pipeline conditional …
consistent delivery of high quality products with efficient cost. Traditional pipeline conditional …
Empirical data analytics
In this paper, we propose an approach to data analysis, which is based entirely on the
empirical observations of discrete data samples and the relative proximity of these points in …
empirical observations of discrete data samples and the relative proximity of these points in …