• mclust

  • Referenced in 257 articles [sw00563]
  • Classification, and Density Estimation , Normal Mixture Modeling fitted via EM algorithm for Model-Based Clustering...
  • PGMM

  • Referenced in 69 articles [sw07981]
  • Gaussian mixture models. Carries out model-based clustering or classification using parsimonious Gaussian mixture models...
  • mixture

  • Referenced in 22 articles [sw14633]
  • Classification. An implementation of all 14 Gaussian parsimonious clustering models (GPCMs) for model-based clustering ... model-based classification...
  • teigen

  • Referenced in 13 articles [sw07950]
  • package teigen: Model-based clustering and classification with the multivariate t-distribution. Fits multivariate...
  • MixGHD

  • Referenced in 9 articles [sw18474]
  • package MixGHD. Model Based Clustering, Classification and Discriminant Analysis Using the Mixture ... Generalized Hyperbolic Distributions. Carries out model-based clustering, classification and discriminant analysis using five different...
  • EMan

  • Referenced in 8 articles [sw09056]
  • iterative process, which utilizes classification by model-based projection matching. CTF (contrast transfer function) parameters...
  • MBCbook

  • Referenced in 2 articles [sw29892]
  • Companion Package for the Book ”Model-Based Clustering and Classification for Data Science” by Bouveyron ... used in the book ”Model-Based Clustering and Classification for Data Science” by Charles Bouveyron...
  • partykit

  • Referenced in 21 articles [sw10634]
  • classification models. This unified infrastructure can be used for reading/coercing tree models from different sources ... conditional inference trees (ctree) and model-based recursive partitioning (mob) from the party package...
  • Mixmod

  • Referenced in 36 articles [sw06991]
  • Model-based cluster and discriminant analysis with the MIXMOD software. The Mixture Modeling (MIXMOD) program ... fits mixture models to a given data set for the purposes of density estimation, clustering ... estimate the mixture parameters are proposed (EM, Classification EM, Stochastic EM), and it is possible...
  • SelvarMix

  • Referenced in 3 articles [sw24498]
  • variable selection in the model-based clustering and classification frameworks. First, the variables are arranged...
  • MixAll

  • Referenced in 1 article [sw35315]
  • package MixAll: Clustering and Classification using Model-Based Mixture Models. Algorithms and methods for model...
  • longclust

  • Referenced in 2 articles [sw20487]
  • package longclust: Model-Based Clustering and Classification for Longitudinal Data. Clustering or classification of longitudinal...
  • mixSPE

  • Referenced in 1 article [sw35312]
  • Exponential Distributions for Use in Model-Based Clustering and Classification. Mixtures of skewed and elliptical...
  • migrateR

  • Referenced in 1 article [sw27353]
  • migrateR provides a framework for model-based quantification and classification of animal movement. The core...
  • vscc

  • Referenced in 3 articles [sw20486]
  • classification framework. In particular, it can be used in an automated fashion using mixture model ... based methods (tEIGEN and MCLUST are currently supported...
  • ordinalClust

  • Referenced in 1 article [sw26302]
  • Classification. Ordinal data classification, clustering and co-clustering using model-based approach with...
  • PLASQ

  • Referenced in 6 articles [sw18746]
  • PLASQ: A generalized linear model-based procedure to determine allelic dosage in cancer cells from ... based upon a generalized linear model that takes advantage of a novel classification of probes...
  • CoClust

  • Referenced in 3 articles [sw19990]
  • require either to choose a starting classification or to set a priori the number ... CoClust selects them by using a criterion based on the log-likelihood of a copula ... dependence scenarios and compare it with a model-based clustering technique. Finally, we show applications...
  • FlowFP

  • Referenced in 1 article [sw19119]
  • contrast with model-based methods such as Gaussian Mixture Modeling. FlowFP is computationally efficient ... data quality control and to the automated classification of Acute Myeloid Leukemia...
  • CLEMM

  • Referenced in 1 article [sw31323]
  • Model-based clustering with envelopes. Clustering analysis is an important unsupervised learning technique in multivariate ... models called CLEMM (in short for Clustering with Envelope Mixture Models) that is based ... model assumptions and the nascent research area of envelope methodology. Formulated mostly for regression models ... recent formulation of envelope discriminant subspace for classification and discriminant analysis. Motivated by the envelope...