用于时间序列频域分析的Julia包_Julia_TeX_下载.zip

 [](https://github.com/lootie/Multitaper.jl/actions) [](https://coveralls.io/github/lootie/Multitaper.jl?branch=master) When doing exploratory analysis of time series, frequency domain methods, that is, statistical methods that display information about the temporal correlations of one or more time series in terms of frequencies, can be used to infer physical mechanisms for underlying process dynamics in e.g. geophysical time series, medical time series, etc.). The [multitaper method](https://en.wikipedia.org/wiki/Multitaper), which leverages Slepian functions to estimate power spectral densities, coherences, and so forth, is implemented here for application to univariate, multivariate, and higher-dimensional (e.g. space-time) processes. See documentation below. [](https://lootie.github.io/Multitaper.jl/stable) [](https://lootie.github.io/Multitaper.jl/dev) ## Installation Please install using ``` Pkg> add Multitaper ``` This package runs on julia v 1.4.2 and above. ## Paper If you make use of Multitaper.jl, please cite the following paper: [](https://doi.org/10.21105/joss.02463). A previous, unregistered version of Multitaper.jl was hosted on bitbucket. ## Python Python users may wish to make use of the python wrapper for this package . A demo for its useage is available . We also highly recommend the multitaper python package by G. A. Prieto, available . ## Contributing We welcome input of any kind via [issues](https://github.com/lootie/Multitaper.jl/issues) or by pull requests. Support requests can be directed to haley@anl.gov.