MICsplines-package: The Computing of Monotonic Spline Bases and Constrained...
In MICsplines: The Computing of Monotonic Spline Bases and Constrained Least-Squares Estimates
Description
The package provides C implementation for the computing of monotonic spline bases, including M-splines, I-splines, and C-splines, denoted by MIC splines. The definitions of the spline bases are described in Meyer (2008). The package also provides the computing of constrained least-squares estimates when a subset of or all of the regression coefficients are constrained to be non-negative, as described in Fraser and Massam (1989).
References
Fraser, D. A. S. and H. Massam (1989). A mixed primal-dual bases algorithm for regression
under inequality constraints. Application to concave regression. Scandinavian Journal
of Statistics 16, 65-74.
Meyer, M. C. (2008). Inference using shape-restricted regression splines. The Annals of
Applied Statistics 2, 1013-1033.
MICsplines documentation built on Sept. 7, 2021, 5:09 p.m.
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Description
The package provides C implementation for the computing of monotonic spline bases, including M-splines, I-splines, and C-splines, denoted by MIC splines. The definitions of the spline bases are described in Meyer (2008). The package also provides the computing of constrained least-squares estimates when a subset of or all of the regression coefficients are constrained to be non-negative, as described in Fraser and Massam (1989).
References
Fraser, D. A. S. and H. Massam (1989). A mixed primal-dual bases algorithm for regression under inequality constraints. Application to concave regression. Scandinavian Journal of Statistics 16, 65-74.
Meyer, M. C. (2008). Inference using shape-restricted regression splines. The Annals of Applied Statistics 2, 1013-1033.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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