circularKDE: Recent Methods for Kernel Density Estimation of Circular Data

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) , complete cross-validation by Hasilová et al. (2024) , Fourier-based plug-in rules by Tenreiro (2022) , and higher-order kernels by Tsuruta & Sagae (2017) .