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bioconductor-fmrs

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Variable Selection in Finite Mixture of AFT Regression and FMR Models

Installation

To install this package, run one of the following:

Conda
$conda install bioconda::bioconductor-fmrs

Usage Tracking

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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.

About

Summary

Variable Selection in Finite Mixture of AFT Regression and FMR Models

Last Updated

Dec 14, 2024 at 17:24

License

GPL-3

Total Downloads

15.7K

Supported Platforms

linux-64
macOS-64