A wrapper for 'circlize'. All components are based on classes and objects. Users can use the addition symbol (+) to combine components for a circular visualization with 'ggplot2' style.The package is described in Zhang Z, Cao T, Huang Y and Xia Y (2025) <doi:10.3389/fgene.2025.1535368>.

Provides tools for estimation and clustering of spherical data, seamlessly integrated with the 'flexmix' package. Includes the necessary M-step implementations for both Poisson Kernel-Based Distribution (PKBD) and spherical Cauchy distribution. Additionally, the package provides random number generators for PKBD and spherical Cauchy distribution. Methods are based on Golzy M., Markatou M. (2020) <doi:10.1080/10618600.2020.1740713>, Kato S., McCullagh P. (2020) <doi:10.3150/20-bej1222> and Sablica L., Hornik K., Leydold J. (2023) <doi:10.1214/23-ejs2149>.

A series of wrapper functions to
    implement the 10 maximum likelihood models of animal orientation
    described by Schnute and Groot (1992) <DOI:10.1016/S0003-3472(05)80068-5>. The
    functions also include the ability to use different optimizer
    methods and calculate various model selection metrics (i.e., AIC,
    AICc, BIC).  The ability to perform variants of the Hermans-Rasson test and
    Pycke test is also included as described in Landler et al. (2019) 
    <DOI:10.1186/s12898-019-0246-8>. The latest version also includes a new
    method to calculate circular-circular and circular-linear distance correlations.

Includes functions for the analysis of circular data using distributions based on Nonnegative Trigonometric Sums (NNTS). The package includes functions for calculation of densities and distributions, for the estimation of parameters, for plotting and more.

Statistical analysis of axial using distributions Nonnegative Trigonometric Sums (NNTS). The package includes functions for calculation of densities and distributions, for the estimation of parameters, and more. Fernandez-Duran, J.J. and Gregorio-Dominguez, M.M. (2025), ''Multimodal distributions for circular axial data", <doi:10.48550/arXiv.2504.04681>.