:notebook: Non-parametric Bayesian Inference for Conservation Decisions
doi: 10.5281/zenodo.12669
This repository contains the research compendium of our work in
nonparametric Bayesian inference for improving ecosystem management under
deep structural uncertainty. The compendium contains all data, code,
and text associated with the publication and has been permanently archived
at the DOI indicated by the above badge.
This repository is organized as an R package, providing functions to integrate
the stochastic dynamic programming and Gaussian process inference
methods explored here. Nevertheless, this package has been written explicitly
for this project and may not yet be suitable for more general purpose use.
The results of this project have now been written up for publication. See
the manuscript directory for details, including the code necessary to
run the examples shown.
See my lab notebook entries under the
nonparametric-bayes
tag for ongoing description of this research.
The issues
tracker lists
both current and accomplished goals in this project, and steps towards
their completion.
See the repository
history
for a fine-grained view of progress and changes.
