scdensity-package

This package computes one-dimensional Gaussian kernel density estimates subject to a
variety of shape constraints, including unimodality, bimodality, symmetry, and others.

internal

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.

Mark A Wolters

scdensity

Shape-Constrained Kernel Density Estimation

scdensity-package function

Maintainer: Mark A. Wolters <a href="/link/mark%40mwolters.com?package=scdensity&version=1.0.3" data-mini-rdoc="scdensity::mark@mwolters.com">mark@mwolters.com</a> (<a href="https://orcid.org/0000-0001-7638-8222">ORCID</a>)

Author

scdensity: Shape-constrained kernel density estimation. — scdensity-package

Maintainer: Mark A. Wolters <a href='mailto:mark@mwolters.com'>mark@mwolters.com</a> (<a href='https://orcid.org/0000-0001-7638-8222'>ORCID</a>)

scdensity-package: scdensity: Shape-constrained kernel density estimation.

Description

Arguments

Author

Details