mclust Version 4 for R : Normal Mixture Modeling for Model-Based Clustering , Classification , and Density Estimation

By Chris Fraley, Adrian E. Raftery. 2012

861 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/bd47b314eecce4fd08bd9f1fa068d1cb4e2db63d

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Citations in the corpus

A Bayesian information criterion for singular models (2013, methodology): “Here, we made explicit that the software that we shall use later, namely the R package mclust (Fraley et al., 2012), uses a lower bound >0 to avoid the well-known singularities in the likelihood surfaces that are obtained by letting one or more variances tend to 0.”
Informative tools for characterizing individual differences in learning: Latent class, latent profile, and latent transition analysis (2017, unknown): “…Bayesian estimation; 1-step, 3-step, LD, time-intensive data LEM (Vermunt, 1997) x x 1-step, LD poLCA (Linzer & Lewis, 2011, 2013) x 1-step MCLUST (Fraley et al., 2012) x DepMixS4 (Visser & Speekenbrink, 2010) x x x 1-step, time-intensive data mixtools (Benaglia et al., 2009) x non-parametric…”
mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture Models (2016, methodology): “Earlier versions of the package have been described in Fraley and Raftery (1999), Fraley and Raftery (2003), and Fraley et al. (2012).”
Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder (2021, methodology): “Finally, the latent embeddings are used to visualize with UMAP [15], and identify spatial domains with various clustering algorithms, such as mclust [16] and Louvain [7] (Fig.”
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 Ratery, 2002) implemented using the R package ‘mclust’ (Fraley et al., 2012).”
Cope's rule and the adaptive landscape of dinosaur body size evolution (2018, methodology): “Nevertheless, our data confirm the presence of a bimodal or trimodal body mass distribution in dinosaurs: fitting a set of mixture models (McLachlan & Basford 1988) using the R package mclust (Fraley et al. 2012) finds support for models positing that the distribution of log-transformed dinosaur bod”
Single cell RNA-seq data clustering using TF-IDF based methods (2018, methodology): “mclust R package [13] was applied to the TF-IDF scores of genes selected”
Spatial transcriptomics at subspot resolution with BayesSpace (2021, methodology): “Specifically, we compare the performance of four non-spatial algorithms commonly applied to scRNA-seq data, k -means, mclust 23 , Louvain 24 and SC3 (ref.”