Model-Based Clustering, Discriminant Analysis, and Density Estimation

By Chris Fraley, Adrian E. Raftery. 2002

4,492 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/114e1354cee7a687ae694f7d8134c7afc87abb47

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Citations in the corpus

What is the scanpath signature of syntactic reanalysis (2011, methodology): “See Table 1 for two example calculations.”
From patterns to pathways: gene expression data analysis comes of age (2002, methodology): “Model-based methods assume the data can be generated by a speciﬁed statistical model (such as a mixture of Gaussian distributions), and search for model parameters that best ﬁt the data 47,48 .”
Clearing the garden-path: improving sentence processing through cognitive control training (2014, methodology): “…cluster analysis using R’s mclust function (mclust library, Fraley & Raftery, 2011), which implements maximum likelihood estimation and Bayes criteria to identify the number of naturally occurring clusters of subjects given the distribution of an outcome measure (see Fraley & Raftery, 2002).”
Bayesian inference for palaeoclimate with time uncertainty and stochastic volatility (2015, methodology): “Gaussian mixtures can be created by using the MClust package of Fraley and Raftery (2002).”
Phenomapping for Novel Classification of Heart Failure with Preserved Ejection Fraction (2014, positive): “15 Specifically we used the mclust package in R and explored a full range of covariance structures, some of which relax the requirement for independence of features (i.e. non-diagonal non-diagonal covariance matrices).”
Multiple Hypothesis Testing by Clustering Treatment Effects (2007, background): “BEMMA was able to estimate the true clustering about as well as MCLUST (Fraley and Raftery 1999, 2002) and much better than hierarchical clustering (Hartigan 1975).”
Genomic Selection for Quantitative Adult Plant Stem Rust Resistance in Wheat (2014, methodology): “Cross validation folds were selected to be representative samples using cluster assignment information from hierarchical agglomerative clustering (Fraley and Raftery, 2002) implemented using the R package ‘mclust’ (Fraley et al.”
A review of moving object trajectory clustering algorithms (2016, background): “Therefore, many researches, such as Zhong and Ghosh (2003), and Fraley and Raftery (2002) tried to find a unified clustering model and framework for grouping complex data (Table 1).”
Traits Without Borders: Integrating Functional Diversity Across Scales. (2016, methodology): “Depending on the amount and type of data that are available, other methods such as Gaussian mixture models [85] or multivariate normal distributions [58] could be used to obtain TPDS functions.”
Applications of functional data analysis: A systematic review (2013, methodology): “The MBC method assumes that the data are generated by a multivariate normal mixture distribution with appropriate means and covariance matrix [129].”
Simultaneous modelling of the Cholesky decomposition of several covariance matrices (2007, methodology): “Details of the trial can be found in Kiel et al. (1998). Previous analyses of this trial is reported in Daniels and Hogan (2000).”