Stan: A Probabilistic Programming Language
Stan: A Probabilistic Programming Language
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DOI：
10.18637/jss.v076.i01
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发表时间：
2017-01-01
影响因子：
5.8
通讯作者：
Riddell, Allen
中科院分区：
文献类型：
--
作者：
Carpenter, Bob;Gelman, Andrew;Riddell, Allen
Stan是一种用于指定统计模型的概率编程语言。Stan程序命令式地在以指定数据和常数为条件的参数上定义对数概率函数。从2.14.0版本开始，Stan通过马尔可夫链蒙特卡罗方法为连续变量模型提供了完整的贝叶斯推理，例如No-U-Turn采样器，这是哈密顿蒙特卡罗采样的一种自适应形式。惩罚的最大似然估计使用优化方法计算，如有限内存Broyden-Fletcher-Goldfarb-Shanno算法。Stan也是一个计算对数密度及其梯度和Hessians的平台，可用于其他算法，如变分贝叶斯，期望传播和使用近似积分的边际推理。为此，Stan的设置使密度、梯度和Hessians以及算法的中间量（如接受概率）易于访问。可以使用cmdstan包从命令行调用Stan，通过R使用rstan包，通过Python使用pystan包。所有三个接口都支持基于诊断和后验分析的采样和优化推理。rstan和pystan还提供对对数概率、梯度、Hessians、参数变换和专门绘图的访问。
Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm.Stan is also a platform for computing log densities and their gradients and Hessians, which can be used in alternative algorithms such as variational Bayes, expectation propagation, and marginal inference using approximate integration. To this end, Stan is set up so that the densities, gradients, and Hessians, along with intermediate quantities of the algorithm such as acceptance probabilities, are easily accessible.Stan can be called from the command line using the cmdstan package, through R using the rstan package, and through Python using the pystan package. All three interfaces support sampling and optimization-based inference with diagnostics and posterior analysis. rstan and pystan also provide access to log probabilities, gradients, Hessians, parameter transforms, and specialized plotting.