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Activity Number: 253 - Contributed Poster Presentations: Section on Statistical Computing
Type: Contributed
Date/Time: Monday, July 30, 2018 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Computing
Abstract #327060
Title: Scdensity: An R Package for Shape-Constrained Kernel Density Estimation
Author(s): Mark Wolters*
Companies: Shanghai Center for Mathematical Sciences
Keywords: density estimation; nonparametric statistics; optimization

The new R package "scdensity" provides facility for obtaining density estimates subject to shape restrictions such as unimodality, bimodality, symmetry, tail monotonicity, and restrictions on the number of inflection points of the density or its derivative. The package is intuitive and easy to use, because it is based on the familiar kernel density estimator. The underlying estimation routine unifies a recently-proposed method, based on adjustment curves, with an earlier method using a weighted estimator. Its implementation overcomes certain numerical challenges. The presentation will explain the new estimation approach, and demonstrate the package's use as applied to axon diameter distribution estimation.

Authors who are presenting talks have a * after their name.

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