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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "MRAM" in publications use:'
type: software
license: GPL-2.0-only
title: 'MRAM: Multivariate Regression Association Measure'
version: 1.0.1
doi: 10.32614/CRAN.package.MRAM
abstract: Implementations of an estimator for the multivariate regression association
  measure (MRAM) proposed in Shih and Chen (2026) <https://doi.org/10.1016/j.csda.2025.108288>
  and its associated variable selection algorithm. The MRAM quantifies the predictability
  of a random vector Y from a random vector X given a random vector Z. It takes the
  maximum value 1 if and only if Y is almost surely a measurable function of X and
  Z, and the minimum value of 0 if Y is conditionally independent of X given Z. The
  MRAM generalizes the Kendall's tau copula correlation ratio proposed in Shih and
  Emura (2021) <https://doi.org/10.1016/j.jmva.2020.104708> by employing the spatial
  sign function. The estimator is based on the nearest neighbor method, and the associated
  variable selection algorithm is adapted from the feature ordering by conditional
  independence (FOCI) algorithm of Azadkia and Chatterjee (2021) <https://doi.org/10.1214/21-AOS2073>.
  For further details, see the paper Shih and Chen (2026) <https://doi.org/10.1016/j.csda.2025.108288>.
authors:
- family-names: Shih
  given-names: Jia-Han
  email: jhshih@math.nsysu.edu.tw
- family-names: Chen
  given-names: Yi-Hau
repository: https://jhshih-stat.r-universe.dev
commit: 3dddfd68ad2fadc01cdfe9ac1275f5fbe4acde81
date-released: '2026-03-04'
contact:
- family-names: Shih
  given-names: Jia-Han
  email: jhshih@math.nsysu.edu.tw