Sampling from high dimensional distributions and volume approximation of convex bodies are fundamental operations that appear in optimization, finance, engineering and machine learning. In this paper we present volesti, a C++ package with an R interface that provides efficient, scalable algorithms for volume estimation, uniform and Gaussian sampling from convex polytopes. volesti scales to hundreds of dimensions, handles efficiently three different types of polyhedra and provides non existing sampling routines to R. We demonstrate the power of volesti by solving several challenging problems using the R language.

中文翻译：

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volesti：R 中凸多面体的体积近似和采样

从高维分布采样和凸体的体积近似是优化、金融、工程和机器学习中出现的基本操作。在本文中，我们介绍了 volesti，这是一个带有 R 接口的 C++ 包，它提供了有效的、可扩展的算法，用于从凸多胞体中进行体积估计、均匀和高斯采样。volesti 可扩展到数百个维度，有效处理三种不同类型的多面体，并为 R 提供不存在的采样例程。我们通过使用 R 语言解决几个具有挑战性的问题来展示 volesti 的强大功能。