
BIOCONDUCTOR . ORG {
}
Title:
Bioconductor - fmrs
Description:
The package obtains parameter estimation, i.e., maximum likelihood estimators (MLE), via the Expectation-Maximization (EM) algorithm for the Finite Mixture of Regression (FMR) models with Normal distribution, and MLE for the Finite Mixture of Accelerated Failure Time Regression (FMAFTR) subject to right censoring with Log-Normal and Weibull distributions via the EM algorithm and the Newton-Raphson algorithm (for Weibull distribution). More importantly, the package obtains the maximum penalized likelihood (MPLE) for both FMR and FMAFTR models (collectively called FMRs). A component-wise tuning parameter selection based on a component-wise BIC is implemented in the package. Furthermore, this package provides Ridge Regression and Elastic Net.
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Keywords {π}
package, bioconductor, fmrs, version, packages, regression, shokoohi, finite, mixture, fmr, release, source, selection, models, algorithm, enter, install, reports, binary, learn, developers, started, software, variable, aft, obtains, parameter, maximum, likelihood, mle, distribution, fmaftr, censoring, weibull, componentwise, farhad, khalili, asgharian, lin, installation, start, documentation, system, details, survival, bioc, stats, url, macos, fmrstgz,
Topics {βοΈ}
org/packages/fmrs source repository joint galaxy/bioconductor conference bioconductor release tgz source repository source package bug reports component-wise bic release //code bioconductor support site maximum likelihood estimators maximum penalized likelihood script reference manual collectively called fmrs gz windows binary package obtains farhad shokoohi [aut fmrs package /shokoohi/fmrs/issues tgz macos binary git clone https newton-raphson algorithm details biocviews stats system requirements package installed packages started install variable selection package /shokoohi/fmrs macos binary bioconductor //bioconductor download stats org registration open finite mixture aft regression expectation-maximization normal distribution log-normal weibull distributions weibull distribution ridge regression elastic net cre] orcid οΏ½capturing heterogeneity covariate effects hidden subpopulations large number
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