Developer Documentation
This section provides supplemental materials that are only relevant to developers of the package. For example, we document mathematical derivations or provide justification for some of the implementation details of the various algorithms used. A typical user of the package's public interface should be able to skip this section.
References
- [1]
- M. Jones and P. Foster. A simple nonnegative boundary correction method for kernel density estimation. Statistica Sinica, 1005–1013 (1996).
- [2]
- A. Lewis. GetDist: a Python package for analysing Monte Carlo samples, arXiv e-prints (2019), arXiv:1910.13970.
- [3]
- B. Hansen. Lecture Notes on Nonparametrics (2009).
- [4]
- Z. Botev, J. Grotowski and D. Kroese. Kernel density estimation via diffusion. The Annals of Statistics 38 (2010), arXiv:1011.2602.