doi:10.1080/03610918.2017.1288247>, Wolters (2012) <doi:10.18637/jss.v047.i06>, and Hall and Huang (2002) <https://www3.stat.sinica.edu.tw/statistica/j12n4/j12n41/j12n41.htm>. See the scdensity() help for for full citations.">

scdensity: Shape-Constrained Kernel Density Estimation (original) (raw)

Implements methods for obtaining kernel density estimates subject to a variety of shape constraints (unimodality, bimodality, symmetry, tail monotonicity, bounds, and constraints on the number of inflection points). Enforcing constraints can eliminate unwanted waves or kinks in the estimate, which improves its subjective appearance and can also improve statistical performance. The main function scdensity() is very similar to the density() function in 'stats', allowing shape-restricted estimates to be obtained with little effort. The methods implemented in this package are described in Wolters and Braun (2017) <doi:10.1080/03610918.2017.1288247>, Wolters (2012) <doi:10.18637/jss.v047.i06>, and Hall and Huang (2002) <https://www3.stat.sinica.edu.tw/statistica/j12n4/j12n41/j12n41.htm>. See the scdensity() help for for full citations.

Version: 1.0.3
Depends: R (≥ 3.3.0)
Imports: quadprog, lpSolve
Suggests: testthat
Published: 2024-08-27
DOI: 10.32614/CRAN.package.scdensity
Author: Mark A. Wolters ORCID iD [aut, cre]
Maintainer: Mark A. Wolters
License: GPL-2
NeedsCompilation: no
CRAN checks: scdensity results

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