
mclust
 Referenced in 256 articles
[sw00563]
 Estimation , Normal Mixture Modeling fitted via EM algorithm for ModelBased Clustering, Classification, and Density...

flexmix
 Referenced in 107 articles
[sw06087]
 mixtures of regression models using the EM algorithm. FlexMix provides the Estep...

RegEM
 Referenced in 16 articles
[sw04943]
 Maximization The modules implement the regularized EM algorithm described in T. Schneider, 2001: Analysis ... Climate, 14, 853871. 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...

Stem
 Referenced in 32 articles
[sw12287]
 spatiotemporal model using the EM algorithm, estimation of the parameter standard errors using...

EMMIX
 Referenced in 20 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...

FAMT
 Referenced in 28 articles
[sw11123]
 parameters are estimated thanks to an EM algorithm. Adjusted tests statistics are derived, as well...

HAPLO
 Referenced in 23 articles
[sw04580]
 HAPLO: A Program Using the EM Algorithm to Estimate the Frequencies of Multisite Haplotypes...

PRISM
 Referenced in 33 articles
[sw23359]
 examples with the help of the EM learning algorithm. As a knowledge representation language appropriate...

EMMIXskew
 Referenced in 13 articles
[sw07968]
 EMMIXskew: The EM Algorithm and Skew Mixture Distribution EM algorithm for Mixture of Multivariate Skew...

funHDDC
 Referenced in 18 articles
[sw11130]
 estimation procedure based on the EM algorithm is proposed for determining both the model parameters...

GAKREM
 Referenced in 10 articles
[sw02712]
 characteristics of the Kmeans 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 Kmeans algorithm, and the likelihood...

bivpois
 Referenced in 16 articles
[sw20812]
 Poisson regression models. An ExpectationMaximization (EM) algorithm is implemented. Inflated models allow for modelling...

SQUAREM
 Referenced in 14 articles
[sw12282]
 extrapolation methods for accelerating fixedpoint iterations. Algorithms for accelerating the convergence of slow, monotone ... smooth, contraction mapping such as the EM algorithm. It can be used to accelerate...

R/qtl
 Referenced in 13 articles
[sw20451]
 data. We have implemented the main HMM algorithms, with allowance for the presence of genotyping ... scans, by interval mapping (with the EM algorithm), HaleyKnott regression, and multiple imputation...

EMMIXskew
 Referenced in 8 articles
[sw19758]
 package EMMIXskew: EM Algorithm for Mixture of Multivariate Skew Normal/t Distributions...

System Identification Toolbox
 Referenced in 164 articles
[sw05686]
 parametric, subspacebased, and predictionerror algorithms coupled (in the latter case) with either MIMO ... parametrizations, and the employment of Expectation Maximization (EM) methods...

EMCluster
 Referenced in 5 articles
[sw24496]
 package EMCluster: EM Algorithm for ModelBased Clustering of Finite Mixture Gaussian Distribution. EM algorithms...

admixture
 Referenced in 5 articles
[sw26449]
 allele frequencies using the expectation maximization (EM) algorithm. (See admixture.barebones.R and admixture.barebones.demo ... improve the very slow convergence of EM. The ADMIXTURE software is implemented using a quasi ... quickly to a solution than the EM algorithm. I’ve modified the model to allow...

PSPMCM
 Referenced in 7 articles
[sw27707]
 parametric models and through an EM algorithm for the Cox’s proportional hazards mixture cure...

CHIME
 Referenced in 4 articles
[sw28514]
 highdimensional Gaussian mixtures with EM algorithm and its optimality. Unsupervised learning is an important ... CHIME, that is based on the EM algorithm and a direct estimation method ... that is based on the classical EM algorithm...