Circular Statistics, from "Topics in Circular Statistics"
        (2001) S. Rao Jammalamadaka and A. SenGupta, World Scientific.

Circular Statistics, from "Topics in circular Statistics" (2001) S. Rao Jammalamadaka and A. SenGupta, World Scientific.

Circular drift-diffusion model for continuous reports.

General functions for performing extreme value analysis on a circular 
    domain as part of the statistical methodology in the paper by Konzen, E., 
    Neves, C., and Jonathan, P. (2021). Modeling nonstationary extremes of storm severity: Comparing parametric and semiparametric inference. Environmetrics, 32(4), e2667.

Provides recent kernel density estimation methods for circular data, including adaptive and higher-order techniques. The implementation is based on recent advances in bandwidth selection and circular smoothing. Key methods include adaptive bandwidth selection methods by Zámečník et al. (2024) <doi:10.1007/s00180-023-01401-0>, complete cross-validation by Hasilová et al. (2024) <doi:10.59170/stattrans-2024-024>, Fourier-based plug-in rules by Tenreiro (2022) <doi:10.1080/10485252.2022.2057974>, and higher-order kernels by Tsuruta & Sagae (2017) <doi:10.1016/j.spl.2017.08.003>.

Calculating silhouette information for clusters on
 circular or linear data using fast algorithms. These algorithms run in
 linear time on sorted data, in contrast to quadratic time by the
 definition of silhouette. When used together with the fast and optimal
 circular clustering method FOCC (Debnath & Song 2021)
 <doi:10.1109/TCBB.2021.3077573> implemented in R package 'OptCirClust',
 circular silhouette can be maximized to find the optimal number of
 circular clusters; it can also be used to estimate the period of noisy
 periodical data.

Circumplex models, which organize constructs in a circle around two 
    underlying dimensions, are popular for studying interpersonal functioning, 
    mood/affect, and vocational preferences/environments. This package provides 
    tools for analyzing and visualizing circular data, including scoring 
    functions for relevant instruments and a generalization of the bootstrapped 
    structural summary method from Zimmermann & Wright (2017) 
    <doi:10.1177/1073191115621795> and functions for creating publication-ready 
    tables and figures from the results.