An implementation of 'Conic Multivariate Adaptive Regression Splines (CMARS)' in R.
    See Weber et al. (2011) CMARS: a new contribution to nonparametric regression with 
    multivariate adaptive regression splines supported by continuous optimization, 
    <DOI:10.1080/17415977.2011.624770>. It constructs models by using the terms
    obtained from the forward step of MARS and then estimates parameters by using 
    'Tikhonov' regularization and conic quadratic optimization. It is possible to 
    construct models for prediction and binary classification. It provides performance 
    measures for the model developed. The package needs the optimisation software 'MOSEK' 
    <https://www.mosek.com/> to construct the models. Please follow the instructions in 
    'Rmosek' for the installation.

Provides functions to perform matching algorithms for causal inference with clustered data, as described in B. Arpino and M. Cannas (2016) <doi:10.1002/sim.6880>. Pure within-cluster and preferential within-cluster matching are implemented. Both algorithms provide causal estimates with cluster-adjusted estimates of standard errors.

Conditional mixture model fitted via EM (Expectation Maximization) algorithm for model-based clustering, including parsimonious procedure, optimal conditional order exploration, and visualization.

Implements the Bayesian calibration model described
    in Pratola and Chkrebtii (2018) <DOI:10.5705/ss.202016.0403> for stochastic 
    and deterministic simulators.  Additive and multiplicative discrepancy models 
    are currently supported. See <http://www.matthewpratola.com/software> for 
    more information and examples.

An open-source implementation of the 'Congruent Matching Cells' 
    method for cartridge case identification as proposed by Song (2013) <https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=911193> as well 
    as an extension of the method proposed by Tong et al. (2015) <doi:10.6028/jres.120.008>.
    Provides a wide range of pre, inter, and post-processing options when
    working with cartridge case scan data and their associated comparisons. See
    the cmcR package website for more details and examples.