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PySSM: A Python Module for Bayesian Inference of Linear Gaussian State Space Models

机译:PySSM:用于线性高斯状态空间模型的贝叶斯推断的Python模块

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PySSM is a Python package that has been developed for the analysis of time series using linear Gaussian state space models. PySSM is easy to use; models can be set up quickly and efficiently and a variety of different settings are available to the user. It also takes advantage of scientific libraries NumPy and SciPy and other high level features of the Python language. PySSM is also used as a platform for interfacing between optimized and parallelized Fortran routines. These Fortran routines heavily utilize basic linear algebra and linear algebra Package functions for maximum performance. PySSM contains classes for filtering, classical smoothing as well as simulation smoothing.
机译:PySSM是一个Python软件包,已开发用于使用线性高斯状态空间模型分析时间序列。 PySSM易于使用;可以快速有效地设置模型,并且用户可以使用各种不同的设置。它还利用了科学库NumPy和SciPy以及Python语言的其他高级功能。 PySSM还用作优化和并行Fortran例程之间接口的平台。这些Fortran例程大量利用基本的线性代数和线性代数Package函数来获得最佳性能。 PySSM包含用于过滤,经典平滑以及模拟平滑的类。

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