fmrs

DOI: 10.18129/B9.bioc.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 (3.17)

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 "4.3") 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")

 

HTML R Script Using fmrs package
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Details

biocViews DimensionReduction, Regression, Software, Survival
Version 1.9.0
In Bioconductor since BioC 3.12 (R-4.0) (2 years)
License GPL-3
Depends R (>= 4.1.0)
Imports methods, survival, stats
LinkingTo
Suggests BiocGenerics, testthat, knitr, utils
SystemRequirements
Enhances
URL
BugReports https://github.com/shokoohi/fmrs/issues
Depends On Me
Imports Me HhP
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package fmrs_1.9.0.tar.gz
Windows Binary fmrs_1.9.0.zip (64-bit only)
macOS Binary (x86_64) fmrs_1.9.0.tgz
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
Package Short Url https://bioconductor.org/packages/fmrs/
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