{ "_id": "6a13e934acfb0bcc41d2dc89", "Package": "crisp", "Type": "Package", "Title": "Fits a Model that Partitions the Covariate Space into Blocks in\na Data- Adaptive Way", "Version": "1.0.0", "Author": "Ashley Petersen", "Maintainer": "Ashley Petersen ", "Description": "Implements convex regression with interpretable sharp\npartitions (CRISP), which considers the problem of predicting\nan outcome variable on the basis of two covariates, using an\ninterpretable yet non-additive model. CRISP partitions the\ncovariate space into blocks in a data-adaptive way, and fits a\nmean model within each block. Unlike other partitioning\nmethods, CRISP is fit using a non-greedy approach by solving a\nconvex optimization problem, resulting in low-variance fits.\nMore details are provided in Petersen, A., Simon, N., and\nWitten, D. (2016). Convex Regression with Interpretable Sharp\nPartitions. 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