This repository contains the supplementary materials, code, and data (application required) for the paper Distortion corrected kernel density estimator on Riemannian manifolds published in the Journal of Computational and Graphical Statistics (JCGS). https://doi.org/10.1080/10618600.2024.2415543

jcgs: The final version of the paper in PDF format.
monash: The paper in the Monash Template format.
R: All scripts and functions used for the simulations (Simulationd.R) and analysis(Electricity2d_0*_*.R).
data: Raw and processed datasets used in the study.
jcgs/figures: Output files, figures, and tables generated from the analysis.
Supplementary Materials: Additional information and extended results not included in the main paper.

R version 4.3.0 or higher
Python version 2.7, 3.5 or 3.6
Anaconda or Miniconda
a C++ compiler such as gcc or g++

If you use this code or data in your research, please cite our paper:

Cheng, F., Hyndman, R. J., & Panagiotelis, A. (2024). Distortion corrected kernel density estimator on Riemannian manifolds. Journal of Computational and Graphical Statistics, 1–19. https://doi.org/10.1080/10618600.2024.2415543

Fan Cheng
Fan.Cheng@monash.edu
Monash University

This project is licensed under the GPL-3.0 license - see the LICENSE file for details.