Bayesian cluster analysis
S Wade - … Transactions of the Royal Society A, 2023 - royalsocietypublishing.org
Bayesian cluster analysis offers substantial benefits over algorithmic approaches by
providing not only point estimates but also uncertainty in the clustering structure and …
providing not only point estimates but also uncertainty in the clustering structure and …
A review on Bayesian model-based clustering
C Grazian - arXiv preprint arXiv:2303.17182, 2023 - arxiv.org
Clustering is an important task in many areas of knowledge: medicine and epidemiology,
genomics, environmental science, economics, visual sciences, among others …
genomics, environmental science, economics, visual sciences, among others …
On posterior contraction of parameters and interpretability in Bayesian mixture modeling
On posterior contraction of parameters and interpretability in Bayesian mixture modeling
Page 1 Bernoulli 27(4), 2021, 2159–2188 https://doi.org/10.3150/20-BEJ1275 On posterior …
Page 1 Bernoulli 27(4), 2021, 2159–2188 https://doi.org/10.3150/20-BEJ1275 On posterior …
General Bayesian loss function selection and the use of improper models
Statisticians often face the choice between using probability models or a paradigm defined
by minimising a loss function. Both approaches are useful and, if the loss can be re-cast into …
by minimising a loss function. Both approaches are useful and, if the loss can be re-cast into …
Bayesian repulsive Gaussian mixture model
We develop a general class of Bayesian repulsive Gaussian mixture models that encourage
well-separated clusters, aiming at reducing potentially redundant components produced by …
well-separated clusters, aiming at reducing potentially redundant components produced by …
Heterogeneous large datasets integration using Bayesian factor regression
The supplementary materials are as follow: Proofs for Lemma 1, Lemma 2 and Lemma 3.
EM algorithm under a flat, Normal-SS, MOM-SS, Laplace-SS and Laplace-MOM-SS on the …
EM algorithm under a flat, Normal-SS, MOM-SS, Laplace-SS and Laplace-MOM-SS on the …
MCMC computations for Bayesian mixture models using repulsive point processes
Repulsive mixture models have recently gained popularity for Bayesian cluster detection.
Compared to more traditional mixture models, repulsive mixture models produce a smaller …
Compared to more traditional mixture models, repulsive mixture models produce a smaller …
Distributed online expectation-maximization algorithm for Poisson mixture model
Q Wang, G Guo, G Qian, X Jiang - Applied Mathematical Modelling, 2023 - Elsevier
Traffic flow data, in the form of multiple time series of aggregated traffic volume observed
from various vehicle detector stations, are investigated as a motivating example. By the very …
from various vehicle detector stations, are investigated as a motivating example. By the very …
Cohesion and repulsion in Bayesian distance clustering
Clustering in high-dimensions poses many statistical challenges. While traditional distance-
based clustering methods are computationally feasible, they lack probabilistic interpretation …
based clustering methods are computationally feasible, they lack probabilistic interpretation …
On the stability of general Bayesian inference
We study the stability of posterior predictive inferences to the specification of the likelihood
model and perturbations of the data generating process. In modern big data analyses, useful …
model and perturbations of the data generating process. In modern big data analyses, useful …