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Random partition models with regression on covariates
(ELSEVIER SCIENCE BV, 2010)
Many recent applications of nonparametric Bayesian inference use random partition models, i.e. probability models for clustering a set of experimental units. We review the popular basic constructions. We then focus on an ...
Similarity analysis in Bayesian random partition models
(ELSEVIER, 2011)
This work proposes a method to assess the influence of individual observations in the clustering generated by any process that involves random partitions. We call it Similarity Analysis. It basically consists of decomposing ...
Perfect simulation for interacting point processes, loss networks and Ising models
(Elsevier Science BvAmsterdamHolanda, 2002)
Analytic Representation of Bayes Labeling and Bayes Clustering Operators for Random Labeled Point Processes
(Institute of Electrical and Electronics Engineers, 2015-03)
Clustering algorithms typically group points based on some similarity criterion, but without reference to an underlying random process to make clustering algorithms rigorously predictive. In fact, there exists a probabilistic ...
Exploring the random genesis of co-occurrence networks
(ELSEVIER SCIENCE BV, 2011)
Using the network random generation models from Gustedt (2009)[23], we simulate and analyze several characteristics (such as the number of components, the degree distribution and the clustering coefficient) of the generated ...
Performance of balanced two-stage empirical predictors of realized cluster latent values from finite populations: A simulation study
(ELSEVIER SCIENCE BV, 2008)
Predictors of random effects are usually based on the popular mixed effects (ME) model developed under the assumption that the sample is obtained from a conceptual infinite population; such predictors are employed even ...