Fetching the paper…
Reading the bibliography…
Scientists and engineers are often interested in learning the number of subpopulations (or components) present in a data set.
Identifiability of mixtures
H. Teicher · 1961
Earlier work this paper cites.
Identifiability of finite mixtures
H. Teicher · 1963
Earlier work this paper cites.
On Bayes procedures
L. Schwartz · 1965
Earlier work this paper cites.
On the identifiability of finite mixtures
S. J. Yakowitz and J. D. Spragins · 1968
Earlier work this paper cites.
Principles of Mathematical Analysis
W. Rudin · 1976
Earlier work this paper cites.
Probability and Measure
P. Billingsley · 1986
Earlier work this paper cites.
Model-based Gaussian and non-Gaussian clustering
J. D. Banfield and A. E. Raftery · 1993
Earlier work this paper cites.
Bayesian analysis of finite mixture distributions
A. Nobile · 1994
Earlier work this paper cites.
Optimal rate of convergence for finite mixture models
J. Chen · 1995
Earlier work this paper cites.
On Bayesian analysis of mixtures with an unknown number of components (with discussion)
S. Richardson and P. J. Green · 1997
Earlier work this paper cites.
Practical Bayesian density estimation using mixtures of normals
K. Roeder and L. Wasserman · 1997
Earlier work this paper cites.
Three types of gamma-ray bursts
S. Mukherjee, E. D. Feigelson, G. J. Babu, F. Murtagh, C. Fraley, and A. Raftery · 1998
Earlier work this paper cites.
Posterior consistency of Dirichlet mixtures in density estimation
S. Ghosal, J. Ghosh, and R. Ramamoorthi · 1999
Earlier work this paper cites.
Markov chain sampling methods for Dirichlet process mixture models
R. M. Neal · 2000
Earlier work this paper cites.
Inference of population structure using multilocus genotype data
J. K. Pritchard, M. Stephens, and P. Donnelly · 2000
Earlier work this paper cites.
MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia
S. A. Armstrong, J. E. Staunton, L. B. Silverman, R. Pieters, M. L. d. Boer, M. D. Minden, S. E. Sallan, E. S. Lander, T. R. Golub, and S. J. Korsmeyer · 2001
Earlier work this paper cites.
Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses
A. Bhattacharjee, W. G. Richards, J. Staunton, C. Li, S. Monti, P. Vasa, C. Ladd, J. Beheshti, R. Bueno, M. Gillette, M. Loda, G. Weber, E. Mark, E. Lander, W. Wong, B. Johnson, T. Golub, D. Sugarbaker, and M. Meyerson · 2001
Earlier work this paper cites.
Bayesian model selection in finite mixtures by marginal density decompositions
H. Ishwaran, L. F. James, and J. Sun · 2001
Earlier work this paper cites.
Validating clustering for gene expression data
K. Y. Yeung, D. R. Haynor, and W. L. Ruzzo · 2001
Earlier work this paper cites.
A mixture model-based approach to the clustering of microarray expression data
G. J. McLachlan, R. Bean, and D. Peel · 2002
Earlier work this paper cites.
Bayesian infinite mixture model based clustering of gene expression profiles
M. Medvedovic and S. Sivaganesan · 2002
Earlier work this paper cites.
A nonparametric Bayesian approach to detect the number of regimes in Markov switching models
E. Otranto and G. M. Gallo · 2002
Earlier work this paper cites.
Bayesian Nonparametrics
J. Ghosh and R. Ramamoorthi · 2003
Earlier work this paper cites.
Bayesian asymptotics under misspecification
B. Kleijn · 2003
Earlier work this paper cites.
A split-merge Markov chain Monte Carlo procedure for the Dirichlet process mixture model
S. Jain and R. M. Neal · 2004
Earlier work this paper cites.
Extending Doob’s consistency theorem to nonparametric densities
A. Lijoi, I. Prünster, and S. Walker · 2004
Earlier work this paper cites.
Bayesian mixture model based clustering of replicated microarray data
M. Medvedovic, K. Y. Yeung, and R. E. Bumgarner · 2004
Earlier work this paper cites.
Clustering univariate observations via mixtures of unimodal normal mixtures
F. Bartolucci · 2005
Cited alongside, same era.
Finite mixture and Markov switching models
S. Frühwirth-Schnatter · 2006
Cited alongside, same era.
Regional genetic structuring and evolutionary history of the impala aepyceros melampus
E. D. Lorenzen, P. Arctander, and H. R. Siegismund · 2006
Cited alongside, same era.
The Gibbs and split merge sampler for population mixture analysis from genetic data with incomplete baselines
J. Pella and M. Masuda · 2006
Cited alongside, same era.
Posterior consistency of Dirichlet location-scale mixture of normals in density estimation and regression
S. T. Tokdar · 2006
Cited alongside, same era.
Robust estimation of mixture complexity
M.-J. Woo and T. Sriram · 2006
A Bayesian cluster analysis method for single-molecule localization microscopy data
J. Griffié, M. Shannon, C. L. Bromley, L. Boelen, G. L. Burn, D. J. Williamson, N. A. Heard, A. P. Cope, D. M. Owen, and P. Rubin-Delanchy · 2016
Later among the works it cites.
On strong identifiability and convergence rates of parameter estimation in finite mixtures
N. Ho and X. Nguyen · 2016
Later among the works it cites.
Probabilistic size-constrained microclustering
A. Klami and A. Jitta · 2016
Later among the works it cites.
Model-based clustering based on sparse finite Gaussian mixtures
G. Malsiner-Walli, S. Frühwirth-Schnatter, and B. Grün · 2016
Later among the works it cites.
Dirichlet process mixture model for correcting technical variation in single-cell gene expression data
S. Prabhakaran, E. Azizi, A. Carr, and D. Pe’er · 2016
Later among the works it cites.
Flexible models for microclustering with application to entity resolution
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Bayesian multi-population haplotype inference via a hierarchical Dirichlet process mixture
E. P. Xing, K.-A. Sohn, M. I. Jordan, and Y.-W. Teh · 2006
Cited alongside, same era.
A mixture of mixture models for a classification problem: The unity measure error
M. Di Zio, U. Guarnera, and R. Rocci · 2007
Cited alongside, same era.
Inference of population structure under a Dirichlet process model
J. P. Huelsenbeck and P. Andolfatto · 2007
Cited alongside, same era.
Robust estimation of mixture complexity for count data
M.-J. Woo and T. Sriram · 2007
Cited alongside, same era.
Bounds for Bayesian order identification with application to mixtures
A. Chambaz and J. Rousseau · 2008
Cited alongside, same era.
Statistical mixture modeling for cell subtype identification in flow cytometry
C. Chan, F. Feng, J. Ottinger, D. Foster, M. West, and T. B. Kepler · 2008
Cited alongside, same era.
G. Zanella, B. Betancourt, H. Wallach, J. Miller, A. Zaidi, and R. C. Steorts · 2016
Later among the works it cites.
Fundamentals of Nonparametric Bayesian Inference
S. Ghosal and A. van der Vaart · 2017
Later among the works it cites.
Inconsistency of Bayesian inference for misspecified linear models, and a proposal for repairing it
P. Grünwald and T. v. Ommen · 2017
Later among the works it cites.
Assigning a value to a power likelihood in a general Bayesian model
C. Holmes and S. Walker · 2017
Later among the works it cites.
Identifying mixtures of mixtures using Bayesian estimation
G. Malsiner-Walli, S. Frühwirth-Schnatter, and B. Grün · 2017
Later among the works it cites.
Reweighted data for robust probabilistic models
Y. Wang, A. Kucukelbir, and D. M. Blei · 2017
Later among the works it cites.
Strong identifiability and optimal minimax rates for finite mixture estimation
P. Heinrich and J. Kahn · 2018
Later among the works it cites.
Principles of Bayesian inference using general divergence criteria
J. Jewson, J. Q. Smith, and C. Holmes · 2018
Later among the works it cites.
Mixture models with a prior on the number of components
J. W. Miller and M. T. Harrison · 2018
Later among the works it cites.
Bayesian target enumeration and labeling using radar data of human gait
F. K. Teklehaymanot, A.-K. Seifert, M. Muma, M. G. Amin, and A. M. Zoubir · 2018
Later among the works it cites.
Identification of subclasses of sepsis that showed different clinical outcomes and responses to amount of fluid resuscitation: a latent profile analysis
Z. Zhang, G. Zhang, H. Goyal, L. Mo, and Y. Hong · 2018
Later among the works it cites.
From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clustering
S. Frühwirth-Schnatter and G. Malsiner-Walli · 2019
Later among the works it cites.
Probabilistic community detection with unknown number of communities
J. Geng, A. Bhattacharya, and D. Pati · 2019
Later among the works it cites.
On posterior contraction of parameters and interpretability in Bayesian mixture modeling
A. Guha, N. Ho, and X. Nguyen · 2019
Later among the works it cites.
Using bagged posteriors for robust inference and model criticism
J. H. Huggins and J. W. Miller · 2019
Later among the works it cites.
Generalized variational inference: Three arguments for deriving new posteriors
J. Knoblauch, J. Jewson, and T. Damoulas · 2019
Later among the works it cites.
Robust Bayesian inference via coarsening
J. W. Miller and D. B. Dunson · 2019
Later among the works it cites.
Fast hierarchical Bayesian analysis of population structure
G. Tonkin-Hill, J. A. Lees, S. D. Bentley, S. D. Frost, and J. Corander · 2019
Later among the works it cites.
Identifiability of nonparametric mixture models and Bayes optimal clustering
B. Aragam, C. Dan, E. P. Xing, and P. Ravikumar · 2020
Closest in time.
Bayesian group learning for shot selection of professional basketball players
G. Hu, H.-C. Yang, and Y. Xue · 2020
Closest in time.
Extended stochastic block models with application to criminal networks
S. Legramanti, T. Rigon, D. Durante, and D. B. Dunson · 2020
Closest in time.
A generalized Bayes framework for probabilistic clustering
T. Rigon, A. H. Herring, and D. B. Dunson · 2020
Closest in time.