Yerlikaya-oezkurt, FatmaYazici, CeydaBatmaz, InciIndustrial Engineering2024-07-052024-07-05202312352-711010.1016/j.softx.2023.1015532-s2.0-85174703053https://doi.org/10.1016/j.softx.2023.101553https://hdl.handle.net/20.500.14411/2152Conic Multivariate Adaptive Regression Splines (CMARS) is a very successful method for modeling nonlinear structures in high-dimensional data. It is based on MARS algorithm and utilizes Tikhonov regularization and Conic Quadratic Optimization (CQO). In this paper, the open-source R package, cmaRs, built to construct CMARS models for prediction and binary classification is presented with illustrative applications. Also, the CMARS algorithm is provided in both pseudo and R code. Note here that cmaRs package provides a good example for a challenging implementation of CQO based on MOSEK solver in R environment by linking R MOSEK through the package Rmosek.eninfo:eu-repo/semantics/openAccessConic multivariate adaptive regression splinesNonparametric regressionTikhonov regularizationConic quadratic programmingInterior point methodBinary classificationcmaRs: A powerful predictive data mining package in RArticleQ224WOS:001101634100001