# ------------------------------------------------
# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# ------------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "malp" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'malp: Maximum Agreement Linear Prediction'
version: 1.1-1
doi: 10.32614/CRAN.package.malp
abstract: 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) <https://doi.org/10.1214/26-EJS2550>.
authors:
- family-names: Chausse
  given-names: Pierre
  email: pchausse@uwaterloo.ca
- family-names: Kim
  given-names: Taeho
  email: tak422@lehigh.edu
- family-names: Pena
  given-names: Edsel A.
  email: pena@stat.sc.edu
repository: https://pchausse.r-universe.dev
repository-code: https://codeberg.org/pchausse/malp
commit: 52c54c1e2bcdc550668d812d69c161efd8626764
url: https://pchausse.r-universe.dev/malp
date-released: '2026-09-21'
contact:
- family-names: Chausse
  given-names: Pierre
  email: pchausse@uwaterloo.ca