
mclust
 Referenced in 159 articles
[sw00563]
 Estimation , Normal Mixture Modeling fitted via EM algorithm for ModelBased Clustering, Classification, and Density...

flexmix
 Referenced in 59 articles
[sw06087]
 mixtures of regression models using the EM algorithm. FlexMix provides the Estep...

RegEM
 Referenced in 12 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...

HAPLO
 Referenced in 21 articles
[sw04580]
 HAPLO: A Program Using the EM Algorithm to Estimate the Frequencies of Multisite Haplotypes...

EMMIX
 Referenced in 14 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 19 articles
[sw11123]
 parameters are estimated thanks to an EM algorithm. Adjusted tests statistics are derived, as well...

EMMIXskew
 Referenced in 11 articles
[sw07968]
 EMMIXskew: The EM Algorithm and Skew Mixture Distribution EM algorithm for Mixture of Multivariate Skew...

PRISM
 Referenced in 25 articles
[sw23359]
 examples with the help of the EM learning algorithm. As a knowledge representation language appropriate...

GAKREM
 Referenced in 9 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...

SQUAREM
 Referenced in 10 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 10 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...

Stem
 Referenced in 8 articles
[sw12287]
 spatiotemporal model using the EM algorithm, estimation of the parameter standard errors using...

bivpois
 Referenced in 8 articles
[sw20812]
 Poisson regression models. An ExpectationMaximization (EM) algorithm is implemented. Inflated models allow for modelling...

funHDDC
 Referenced in 7 articles
[sw11130]
 estimation procedure based on the EM algorithm is proposed for determining both the model parameters...

System Identification Toolbox
 Referenced in 124 articles
[sw05686]
 parametric, subspacebased, and predictionerror algorithms coupled (in the latter case) with either MIMO ... parametrizations, and the employment of Expectation Maximization (EM) methods...

curvclust
 Referenced in 5 articles
[sw07435]
 which we develop an EMalgorithm for maximum likelihood estimation. The properties of the overall...

MIXREG
 Referenced in 5 articles
[sw24547]
 marginal likelihood estimation, utilizing both the EM algorithm and a Fisherscoring solution...

CARTHAGENE
 Referenced in 3 articles
[sw23159]
 algorithm that mixes the statistical optimization algorithm EM with local search techniques which have been ... communities. An efficient implementation of the EM algorithm provides maximum likelihood recombination fractions, while...

Mixmod
 Referenced in 24 articles
[sw06991]
 large variety of algorithms to estimate the mixture parameters are proposed (EM, Classification EM, Stochastic...

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...