CMLS (version 1.0-1)

CMLS-package: tools:::Rd_package_title("CMLS")

Description

tools:::Rd_package_description("CMLS")

Author

tools:::Rd_package_author("CMLS")

Maintainer: tools:::Rd_package_maintainer("CMLS")

Details

The DESCRIPTION file: tools:::Rd_package_DESCRIPTION("CMLS") tools:::Rd_package_indices("CMLS") The cmls function provides a user-friendly interface for solving the MLS problem with 24 common constraint options (the const function prints or returns the different contraint options). The cv.cmls function does k-fold or generalized cross-validation to tune the constraint options of the cmls function. The mlsei function solves the MLS problem subject to user-specified equality and/or inequality (E/I) constraints on the coefficients. The mlsun function solves the MLS problem subject to unimodality constraints and user-specified E/I constraints on the coefficients.

References

Goldfarb, D., & Idnani, A. (1983). A numerically stable dual method for solving strictly convex quadratic programs. Mathematical Programming, 27, 1-33. tools:::Rd_expr_doi("10.1007/BF02591962")

Helwig, N. E. (in prep). Constrained multivariate least squares in R.

Ten Berge, J. M. F. (1993). Least Squares Optimization in Multivariate Analysis. Volume 25 of M & T Series. DSWO Press, Leiden University. ISBN: 9789066950832

Turlach, B. A., & Weingessel, A. (2019). quadprog: Functions to solve Quadratic Programming Problems. R package version 1.5-8. https://CRAN.R-project.org/package=quadprog

Examples

# See examples for cmls, cv.cmls, mlsei, and mlsun