• mclust

  • Referenced in 124 articles [sw00563]
  • Estimation , Normal Mixture Modeling fitted via EM algorithm for Model-Based Clustering, Classification, and Density...
  • flexmix

  • Referenced in 25 articles [sw06087]
  • mixtures of regression models using the EM algorithm. FlexMix provides the E-step...
  • RegEM

  • Referenced in 9 articles [sw04943]
  • Maximization The modules implement the regularized EM algorithm described in T. Schneider, 2001: Analysis ... Climate, 14, 853-871. The EM algorithm for Gaussian data is based on iterated linear ... regression analyses. In the regularized EM algorithm, a regularized estimation method replaces the conditional maximum ... regression parameters in the conventional EM algorithm for Gaussian data. The modules here provide truncated...
  • mixsmsn

  • Referenced in 18 articles [sw06064]
  • skew-normal independent distributions. A general EM-type algorithm is employed for iteratively computing parameter ... proposed methodology. The proposed EM-type algorithm and methods are implemented in the R package...
  • HAPLO

  • Referenced in 17 articles [sw04580]
  • HAPLO: A Program Using the EM Algorithm to Estimate the Frequencies of Multi-site Haplotypes...
  • EMMIX

  • Referenced in 11 articles [sw08192]
  • using maximum likelihood via the EM algorithm of Dempster, Laird, and Rubin ... full examination of the EM algorithm and related topics, see McLachlan and Krishnan (1997). Many...
  • EMMIX-skew

  • Referenced in 10 articles [sw07968]
  • EMMIXskew: The EM Algorithm and Skew Mixture Distribution EM algorithm for Mixture of Multivariate Skew...
  • GAKREM

  • Referenced in 8 articles [sw02712]
  • characteristics of the K-means and EM algorithms but avoids their weaknesses such ... goals, genetic algorithms for estimating parameters and initializing starting points for the EM are used ... regression instead of running the conventional EM algorithm until its convergence. Another novelty ... comparing its performance with the conventional EM algorithm, the K-means algorithm, and the likelihood...
  • FAMT

  • Referenced in 12 articles [sw11123]
  • parameters are estimated thanks to an EM algorithm. Adjusted tests statistics are derived, as well...
  • SQUAREM

  • Referenced in 8 articles [sw12282]
  • extrapolation methods for accelerating fixed-point iterations. Algorithms for accelerating the convergence of slow, monotone ... smooth, contraction mapping such as the EM algorithm. It can be used to accelerate...
  • Stem

  • Referenced in 4 articles [sw12287]
  • spatio-temporal model using the EM algorithm, estimation of the parameter standard errors using...
  • funHDDC

  • Referenced in 4 articles [sw11130]
  • estimation procedure based on the EM algorithm is proposed for determining both the model parameters...
  • spinyReg

  • Referenced in 2 articles [sw14821]
  • Combining a relaxed EM algorithm with Occam’s razor for Bayesian variable selection in high ... likelihood maximization based on an EM algorithm. Model selection is performed afterwards relying on Occam ... path of models found by the EM algorithm. Numerical comparisons between our method, called spinyReg...
  • System Identification Toolbox

  • Referenced in 87 articles [sw05686]
  • parametric, subspace-based, and prediction-error algorithms coupled (in the latter case) with either MIMO ... parametrizations, and the employment of Expectation Maximization (EM) methods...
  • Mixmod

  • Referenced in 20 articles [sw06991]
  • large variety of algorithms to estimate the mixture parameters are proposed (EM, Classification EM, Stochastic...
  • HMMmix

  • Referenced in 3 articles [sw13500]
  • flexibility. We show that the standard EM algorithm can be adapted to infer the model...
  • Soft-LOST

  • Referenced in 7 articles [sw14921]
  • Soft-LOST: EM on a mixture of oriented lines. Robust clustering of data into overlapping ... present an algorithm that identifies these subspaces using an EM procedure, where the E-step ... norm optimisation, constitutes a blind source separation algorithm for the under-determined case...
  • disclapmix

  • Referenced in 1 article [sw14230]
  • Discrete Laplace Mixture Inference using the EM Algorithm. Make inference in a mixture of discrete ... Laplace distributions using the EM algorithm. This can e.g. be used for modelling the distribution...
  • CAMAN

  • Referenced in 1 article [sw14555]
  • algorithms (flexible support size) and EM algorithms (fixed support size) are provided for univariate...