• PReMiuM

  • Referenced in 8 articles [sw14746]
  • Profile Regression. Bayesian clustering using a Dirichlet process mixture model. This model is an alternative...
  • dpmixsim

  • Referenced in 3 articles [sw24713]
  • package dpmixsim: Dirichlet Process Mixture model simulation for clustering and image segmentation. The package implements ... Dirichlet Process Mixture (DPM) model for clustering and image segmentation. The DPM model...
  • BNPmix

  • Referenced in 2 articles [sw28208]
  • mixture models, and Griffiths-Milne Dependent Dirichlet process mixture models. Pitman-Yor process mixture models ... importance conditional sampler a GM-Dependent Dirichlet process mixture model...
  • profdpm

  • Referenced in 2 articles [sw24502]
  • Package profdpm: Profile Dirichlet Process Mixtures. This package facilitates profile inference (inference at the posterior ... product partition models (PPM). The Dirichlet process mixture is currently the only available member...
  • PhyloBayes MPI

  • Referenced in 2 articles [sw23042]
  • Modeling across site variation of the substitution process is increasingly recognized as important for obtaining ... infinite mixture models. In particular, a fast but simplified version of a Dirichlet process model ... interface version of PhyloBayes, implementing the Dirichlet process mixture models as well as more classical ... truncated stick-breaking representation for the Dirichlet process prior. The implementation shows close to linear...
  • pyMEF

  • Referenced in 2 articles [sw07455]
  • mixtures by simplifying kernel density estimators Gaussian mixture models are a widespread tool for modeling ... promising stochastic modeling methods include Dirichlet process mixtures and $k$-maximum likelihood estimators. Most...
  • growfunctions

  • Referenced in 2 articles [sw16375]
  • field (iGMRF) prior formulations where a Dirichlet process mixture allows sub-groupings of the functions...
  • BNSP

  • Referenced in 1 article [sw24225]
  • semi-parametric models: 1. Dirichlet process mixtures & 2. spike-slab for variable selection in mean/variance...
  • DPWeibull

  • Referenced in 0 articles [sw20438]
  • package DPWeibull. Use Dirichlet process Weibull mixture model and dependent Dirichlet process Weibull mixture model ... with and without competing risks. Dirichlet process Weibull mixture model is used for data without ... competing risks. Inside each cluster of Dirichlet process, we assume a multiplicative effect of covariates ... dimensional data with Dirichlet mixture of Gaussian distributions...
  • BNPMIXcluster

  • Referenced in 1 article [sw18028]
  • based on a location mixture model with a Poisson-Dirichlet process prior on the location...
  • lrgs

  • Referenced in 0 articles [sw16144]
  • either a Gaussian mixture of specified size or a Dirichlet process with a Gaussian base...
  • ANSYS

  • Referenced in 643 articles [sw00044]
  • ANSYS offers a comprehensive software suite that spans...
  • Gmsh

  • Referenced in 528 articles [sw00366]
  • Gmsh is a 3D finite element grid generator...
  • HSL

  • Referenced in 265 articles [sw00418]
  • HSL (formerly the Harwell Subroutine Library) is a...
  • LAPACK

  • Referenced in 1586 articles [sw00503]
  • LAPACK is written in Fortran 90 and provides...
  • Magma

  • Referenced in 2718 articles [sw00540]
  • Computer algebra system (CAS). Magma is a large...
  • Maple

  • Referenced in 4919 articles [sw00545]
  • The result of over 30 years of cutting...
  • Mathematica

  • Referenced in 5703 articles [sw00554]
  • Almost any workflow involves computing results, and that...
  • Matlab

  • Referenced in 11496 articles [sw00558]
  • MATLAB® is a high-level language and interactive...
  • mclust

  • Referenced in 234 articles [sw00563]
  • R package mclust: Normal Mixture Modeling for Model...