Forked from Brendan Brewer's DNest4 Repository

DNest4 is a C++11 implementation of Diffusive Nested Sampling, a Markov Chain Monte Carlo (MCMC) algorithm for Bayesian Inference and Statistical Mechanics.

Before you use DNest4, you might want to read the paper describing the Diffusive Nested Sampling algorithm. If you find this software useful in your research, please cite this paper.

Diffusive Nested Sampling Brendon J. Brewer, Livia B. Pártay, and Gábor Csányi Statistics and Computing, 2011, 21, 4, 649-656.

The paper is freely available online at the arXiv.

• There are far fewer dependencies --- all you need is a C++ compiler that supports the C++11 standard, along with Python, NumPy, and Matplotlib for the post-processing scripts. Because of this, it should be much easier to compile (at least on a Unix-like operating system such as Ubuntu or Mac OS X).

• The licence is now the permissive MIT licence.

• RJObject (which allows relatively straightforward implementation of hierarchical and trans-dimensional mixture models) is now included in the same repository.

Some functions have slightly different names and specifications compared to DNest3. These changes are purely cosmetic. The manual (in the doc directory) can be compiled with pdflatex.

(c) 2015--2016 Brendon J. Brewer LICENCE: MIT. See the LICENSE file for details.

This work was supported by a Marsden Fast Start grant from the Royal Society of New Zealand.