Movatterモバイル変換

McMiso: Multicore Multivariable Isotonic Regression

The goal of 'McMiso' is to provide functions for isotonic regression when there are multiple independent variables. The functions solve the optimization problem using recursion and leverage parallel computing to improvespeed, and are useful for situations with relatively large number of covariates. The estimation method follows theprojective Bayes solution described in Cheung and Diaz (2023) <doi:10.1093/jrsssb/qkad014>.

Version:	0.1.2
Depends:	R (≥ 4.0.0)
Imports:	dplyr,future (≥ 1.33.0), stats
Published:	2025-11-21
DOI:	10.32614/CRAN.package.McMiso
Author:	Cheung Ken [aut, cre]
Maintainer:	Cheung Ken <yc632 at cumc.columbia.edu>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	McMiso results

Documentation:

Reference manual:

McMiso.html ,McMiso.pdf

Downloads:

Package source:	McMiso_0.1.2.tar.gz
Windows binaries:	r-devel:McMiso_0.1.2.zip, r-release:McMiso_0.1.2.zip, r-oldrel:McMiso_0.1.2.zip
macOS binaries:	r-release (arm64):McMiso_0.1.2.tgz, r-oldrel (arm64):McMiso_0.1.2.tgz, r-release (x86_64):McMiso_0.1.2.tgz, r-oldrel (x86_64):McMiso_0.1.2.tgz

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=McMisoto link to this page.