Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: María Oliveira, Rosa M. Crujeiras, Alberto Rodríguez-Casal
Title: NPCirc: An R Package for Nonparametric Circular Methods
Abstract: Nonparametric density and regression estimation methods for circular data are included in the R package NPCirc. Specifically, a circular kernel density estimation procedure is provided, jointly with different alternatives for choosing the smoothing parameter. In the regression setting, nonparametric estimation for circular-linear, circular-circular and linear-circular data is also possible via the adaptation of the classical Nadaraya-Watson and local linear estimators. In order to assess the significance of the features observed in the smooth curves, both for density and regression with a circular covariate and a linear response, a SiZer technique is developed for circular data, namely CircSiZer. Some data examples are also included in the package, jointly with a routine that allows generating mixtures of different circular distributions.

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Paper: NPCirc: An R Package for Nonparametric Circular Methods     Download PDF (Downloads: 5251)
NPCirc_2.0.1.tar.gz: R source package Download (Downloads: 265; 176KB)
v61i09.R: R example code from the paper Download (Downloads: 311; 5KB)

DOI: 10.18637/jss.v061.i09

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.