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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Oliveira, M., Crujeiras, R. M., & Rodríguez-Casal, A. (2014). NPCirc: An R package for nonparametric circular methods. Journal of Statistical Software, 61(9), 1–26. https://doi.org/10.18637/jss.v061.i09
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