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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "rbpengine" in publications use:'
type: software
license: MIT
title: 'rbpengine: Relevance-Based Prediction for the ''RBP Math Engine'''
version: 2.4.0
doi: 10.32614/CRAN.package.rbpengine
identifiers:
- type: url
  value: https://docs.csanalytics.io/Install/R
abstract: Provides predict_psr(), predict_maxfit(), and predict_grid() for relevance-based
  prediction ('RBP') via the 'RBP Math Engine' C application binary interface ('ABI').
  Returns a 'PredictionResults' nested list that mirrors the 'Python' 'rbp_engine'
  package. The package builds and installs without the private engine; prediction
  and insight entry points load the engine at runtime ('RBP_ENGINE_LIB' or a staged
  install under 'RBP_ENGINE_HOME' / /Library/rbp-engine). Licensing uses 'rbp-license-info'
  and standard license environment variables.
authors:
- name: Cambridge Sports Analytics
- family-names: Kulasekaran
  given-names: Cel
  email: ckulasekaran@csanalytics.io
repository: https://cambridgesportsanalytics.r-universe.dev
repository-code: https://github.com/CambridgeSportsAnalytics/rbp-engine-r
commit: 01dff44862c005dbedcdad1afabdc0d486e0a35b
url: https://cambridgesportsanalytics.r-universe.dev
date-released: '2026-10-05'
contact:
- family-names: Kulasekaran
  given-names: Cel
  email: ckulasekaran@csanalytics.io