论文标题
贝叶斯：C ++中的贝叶斯混合模型
BayesMix: Bayesian Mixture Models in C++
论文作者
论文摘要
我们描述了用于通用贝叶斯混合模型的MCMC后验模拟的C ++库。 Bayesmix的目的是为计算机科学家，统计学家和从业者提供一个独立的生态系统，以对混合模型进行推理。该库的关键思想是可扩展的，因为我们希望用户可以轻松地将我们的软件适应其特定的贝叶斯混合模型。除了在图书馆中包含的几种模型和MCMC算法外，在混合模型上几乎没有熟悉的新用户和相关的MCMC算法还可以通过最小的编码工作来扩展我们的库。与竞争者软件相比，我们的图书馆在计算上非常有效。示例表明，典型的代码运行时间比竞争对手的数据维度比一个到十的竞争对手快2到25倍。我们的图书馆可在https://github.com/bayesmix-dev/bayesmix/上公开获得。
We describe BayesMix, a C++ library for MCMC posterior simulation for general Bayesian mixture models. The goal of BayesMix is to provide a self-contained ecosystem to perform inference for mixture models to computer scientists, statisticians and practitioners. The key idea of this library is extensibility, as we wish the users to easily adapt our software to their specific Bayesian mixture models. In addition to the several models and MCMC algorithms for posterior inference included in the library, new users with little familiarity on mixture models and the related MCMC algorithms can extend our library with minimal coding effort. Our library is computationally very efficient when compared to competitor software. Examples show that the typical code runtimes are from two to 25 times faster than competitors for data dimension from one to ten. Our library is publicly available on Github at https://github.com/bayesmix-dev/bayesmix/.
