BayesDensity.jl: Bayesian nonparametric density estimation in Julia
BayesDensity.jl is a Julia package for Bayesian nonparametric estimation of smooth univariate densities. The package provides a unified interface to a range of well-established models from the statistical literature, supporting both Markov chain Monte Carlo and variational inference for most implemented procedures. Tailor-made inference algorithms facilitate computational efficiency across all supported models. The practical usage of the package is illustrated through several real-data examples, demonstrating its ability to produce smooth, interpretable density estimates with principled uncertainty quantification. The excellent computational performance of the package is demonstrated in two benchmarks.
Authors
- Oskar Høgberg Simensen
Institutions
- Karlsruhe University of Education (DE)
Publication Details
- Journal
- SoftwareX
- Published
- 2026-06-29
- DOI
- https://doi.org/10.1016/j.softx.2026.102847
- Primary Topic
- Markov Chains and Monte Carlo Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00