fmrs

This is the development version of fmrs; for the stable release version, see fmrs.

Variable Selection in Finite Mixture of AFT Regression and FMR Models


Bioconductor version: Development (3.21)

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.

Author: Farhad Shokoohi [aut, cre]

Maintainer: Farhad Shokoohi <shokoohi at icloud.com>

Citation (from within R, enter citation("fmrs")):

Installation

To install this package, start R (version "4.5") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("fmrs")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("fmrs")
Using fmrs package HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews DimensionReduction, Regression, Software, Survival
Version 1.17.0
In Bioconductor since BioC 3.12 (R-4.0) (4 years)
License GPL-3
Depends R (>= 4.3.0)
Imports methods, survival, stats
System Requirements
URL
Bug Reports https://github.com/shokoohi/fmrs/issues
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Suggests BiocGenerics, testthat, knitr, utils
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package fmrs_1.17.0.tar.gz
Windows Binary (x86_64)
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/fmrs
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/fmrs
Bioc Package Browser https://code.bioconductor.org/browse/fmrs/
Package Short Url https://bioconductor.org/packages/fmrs/
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