RT Journal Article
T1 NPCirc: An R package for nonparametric circular methods
A1 Oliveira Pérez, María
A1 Crujeiras Casais, Rosa María
A1 Rodríguez Casal, Alberto
K1 Circular data
K1 CircSiZer
K1 Nonparametric methods
K1 Mixtures
K1 R package
AB Nonparametric density and regression estimation methods for circular data are included in the R package NPCirc. Speci cally, a circular kernel density estimation procedureis provided, jointly with di erent 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-Watsonand local linear estimators. In order to assess the signi cance of the features observed inthe smooth curves, both for density and regression with a circular covariate and a linearresponse, 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 di erent circular distributions
PB American Statistical Association
SN 1548-7660
YR 2014
FD 2014-10
LK http://hdl.handle.net/10347/13954
UL http://hdl.handle.net/10347/13954
LA eng
NO Oliveira, M., Crujeiras, R.M., Rodríguez-Casal, A. (2014). NPCirc: An R package for nonparametric circular methods. "Journal of Statistical Software", 61, 9 [doi: 10.18637/jss.v061.i09]
NO The authors want to acknowledge two anonymous referees for their comments which helped in improving both the paper and the package contents. The authors also acknowledgeProf. A. Pewsey for providing the dragonies and cross beds data. Data from periglacial,collected within the Project POL2006{09071 from the Spanish Ministry of Education and Science have been provided by Prof. A. P erez-Alberti. Data stored in the wind dataset are provided by NCAR/EOL under the sponsorship of the National Science Foundation.This research has been supported by Project MTM2008{03010 from the Spanish Ministryof Science and Innovation, and by the IAP network StUDyS (Developing crucial Statistical methods for Understanding major complex Dynamic Systems in natural, biomedical and social sciences), from Belgian Science Policy
DS Minerva
RD 22 abr 2026