This is an R package that fits the Nested Dirichlet Process to grouped distance data according to an Inhomogenous Poisson Process model. The primary target audience is researchers interested in the effect of built environment features (BEFs) on human health, though other applications are possible. See the package’s website for an introduction. Currently both normal and beta base measures are implemented. See the documentation for more information.
Examples and code contributions are welcome. Feel free to start/address a feature in the issue tracker and I’ll be notified shortly.
Please note that
bendr is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.