BCM – Bayesian analysis of Computational Models using samplers. BCM is a C++ software package for the Bayesian analysis of computational models. It provides efficient implementations of eleven sampling algorithms for generating posterior samples and calculating marginal likelihoods. Additional tools are included which facilitate the process of specifying models and visualizing the sampling output. This toolkit can be used for analyzing the uncertainty in the parameters and the predictions of computational models using Bayesian statistics.
Keywords for this software
References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Clerx, M., Robinson, M., Lambert, B., Lei, C.L., Ghosh, S., Mirams, G.R. and Gavaghan, D.J.: Probabilistic Inference on Noisy Time Series (PINTS) (2019) not zbMATH
- Bram Thijssen, Lodewyk F.A. Wessels: Approximating multivariate posterior distribution functions from Monte Carlo samples for sequential Bayesian inference (2017) arXiv