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 improve speed, and are useful for situations with relatively large number of covariates. The estimation method follows the projective 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 (may not be active yet)
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: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): McMiso_0.1.2.tgz, r-oldrel (arm64): McMiso_0.1.2.tgz, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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