malp: Maximum Agreement Linear Prediction

Provides tools for estimation and prediction using Maximum Agreement Linear Predictors (MALPs). MALPs provide an alternative to least squares linear predictors when agreement between predicted and observed values, as measured by Lin's Concordance Correlation Coefficient (CCC), is of primary interest. Applications include missing value imputation and calibration studies. The package includes functions for model estimation, prediction, statistical inference, cross-validation, and model diagnostics. The implemented methodology is described in Kim et al. (2026) <doi:10.1214/26-EJS2550>.

Version:	1.1-0
Depends:	R (≥ 4.0.0)
Imports:	stats, sandwich, graphics, boot
Published:	2026-08-03
DOI:	10.32614/CRAN.package.malp (may not be active yet)
Author:	Pierre Chausse [aut, cre], Taeho Kim [aut], Edsel A. Pena [aut], George Luta [ctb]
Maintainer:	Pierre Chausse <pchausse at uwaterloo.ca>
BugReports:	https://github.com/pchausse/malp/issues
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	malp results

Documentation:

Reference manual:

malp.html , malp.pdf

Downloads:

Package source:	malp_1.1-0.tar.gz
Windows binaries:	r-devel: malp_1.1-0.zip, r-release: not available, r-oldrel: malp_1.1-0.zip
macOS binaries:	r-release (arm64): malp_1.1-0.tgz, r-oldrel (arm64): malp_1.1-0.tgz, r-release (x86_64): malp_1.1-0.tgz, r-oldrel (x86_64): malp_1.1-0.tgz

Linking:

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