# ------------------------------------------------ # CITATION.cff file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # ------------------------------------------------ cff-version: 1.2.0 message: 'To cite package "crisp" in publications use:' type: software license: GPL-2.0-or-later title: 'crisp: Fits a Model that Partitions the Covariate Space into Blocks in a Data- Adaptive Way' version: 1.0.0 doi: 10.32614/CRAN.package.crisp abstract: 'Implements convex regression with interpretable sharp partitions (CRISP), which considers the problem of predicting an outcome variable on the basis of two covariates, using an interpretable yet non-additive model. CRISP partitions the covariate space into blocks in a data-adaptive way, and fits a mean model within each block. Unlike other partitioning methods, CRISP is fit using a non-greedy approach by solving a convex optimization problem, resulting in low-variance fits. More details are provided in Petersen, A., Simon, N., and Witten, D. (2016). Convex Regression with Interpretable Sharp Partitions. Journal of Machine Learning Research, 17(94): 1-31 .' authors: - family-names: Petersen given-names: Ashley email: ashleyjpete@gmail.com repository: https://cranhaven.r-universe.dev commit: 1ba45074d851c683785421c5e25c664e88f1c4e9 date-released: '2026-10-12' contact: - family-names: Petersen given-names: Ashley email: ashleyjpete@gmail.com