贝叶斯突变点检测与时间序列分解（Matlab）

## BEAST: A Bayesian Ensemble Algorithm for Change-Point Detection and Time Series Decomposition #### BEAST (Bayesian Estimator of Abrupt change, Seasonality, and Trend) is a fast, generic Bayesian model averaging algorithm to decompose time series or 1D sequential data into individual components, such as abrupt changes, trends, and periodic/seasonal variations, as described in <ins>[Zhao et al. (2019)](https://go.osu.edu/beast2019)</ins>. BEAST is useful for *changepoint detection (e.g., breakpoints, structural breaks, regime shifts, or anomalies), trend analysis, time series decomposition (e.g., trend vs seasonality), time series segmentation, and interrupted time series analysis*. See a list of <a href="#publicationid"> selected studies using BEAST </a>. **Quick Installation** > BEAST was impemented in C/C++ but accessible from R, Python, Matlab, and Octave. Run the following to install: * [Python](#python): **`pip install Rbeast`** * [Matlab](#matlab): **`eval(webread('http://b.link/rbeast',weboptions('cert','')))`** * [Octave](#octave): **`eval(webread('http://b.link/rbeast'))`** * [R lang](#r): **`install.packages("Rbeast")`** **Quick Usage** > One-liner code for Python, Matlab and R. Check below or [github.com/zhaokg/Rbeast](https://github.com/zhaokg/Rbeast) for more details. ``` # Python example import Rbeast as rb; (Nile, Year)=rb.load_example('nile'); o=rb.beast(Nile,season='none'); rb.plot(o) # Matlab/Octave example load('Nile'); o = beast(Nile, 'season','none'); plotbeast(o) # R example library(Rbeast); data(Nile); o = beast(Nile); plot(o) ``` ## Installation for R <a name=r> </a> <!--- ===================================================================================== ===================================================================================== ===================================================================================== This is our comments: <table border="0" style='border:none;' bordercolor="#ffffff" > <tr style='border:none;' > <td valign="center" style='border:none;' > <img src="https://www.r-pkg.org/badges/version/Rbeast?color=green"> <img src="http://cranlogs.r-pkg.org/badges/grand-total/Rbeast?color=green"> </td> <td valign="center" style='border:none;' > In CRAN-Task-View: <a href="https://cran.r-project.org/web/views/TimeSeries.html#forecasting-and-univariate-modeling">[Time Series Analysis]</a> <a href="https://cran.r-project.org/web/views/Bayesian.html#time-series-models">[Bayesian inference]</a> <a href="https://cran.r-project.org/web/views/Environmetrics.html#environmental-time-series">[Environmetrics]</a> </td> </tr></table> [](https://cran.r-project.org/package=Rbeast) [](https://cran.r-project.org/package=Rbeast) In CRAN-Task-View: [[**Time Series Analysis**]](https://cran.r-project.org/web/views/TimeSeries.html#forecasting-and-univariate-modeling), [[**Bayesian inference**]](https://cran.r-project.org/web/views/Bayesian.html#time-series-models), and [[**Environmetrics**]](https://cran.r-project.org/web/views/Environmetrics.html#environmental-time-series) from **GitHub**: The latest R versions are also available here at [GitHub](https://github.com/zhaokg/Rbeast) and can be installed using ```R # Windows x86 or x64 (install from binary) install.packages("https://github.com/zhaokg/Rbeast/raw/master/R/Windows/Rbeast_0.9.5.zip" ,repos=NULL) # Linux/Mac (install from source) install.packages("https://github.com/zhaokg/Rbeast/raw/master/R/Rbeast_0.9.5.tar.gz", repos = NULL, type="source") ``` ===================================================================================== ===================================================================================== ===================================================================================== --> <p align="left"> <a href= "https://cran.r-project.org/package=Rbeast"> <img src="https://www.r-pkg.org/badges/version/Rbeast?color=green" height="20"> <img src="http://cranlogs.r-pkg.org/badges/grand-total/Rbeast?color=green" height="20"> <img src="https://img.shields.io/static/v1?style=plastic&logo=r&label=Rbeast%20%20&message= In CRAN-Task-View&color=brightgreen" height="20"> </a> </p> > **Rbeast in CRAN-TASK-VIEW**: <a href="https://cran.r-project.org/web/views/TimeSeries.html#forecasting-and-univariate-modeling">[Time Series Analysis]</a> <a href="https://cran.r-project.org/web/views/Bayesian.html#time-series-models">[Bayesian inference]</a> <a href="https://cran.r-project.org/web/views/Environmetrics.html#environmental-time-series">[Environmetrics]</a> An R package **`Rbeast`** has been deposited at [CRAN](https://CRAN.R-project.org/package=Rbeast). ( On CRAN, there is another Bayesian time-series package named "beast", which has nothing to do with the BEAST algorithim. Our package is `Rbeast`. Also, our package has nothing to do with the famous "Bayesian evolutionary analysis by sampling trees" aglorithm.) Install `Rbeast` in R using ```R install.packages("Rbeast") ``` #### Run and test Rbeast in R The main functions in Rbeast are `beast(Y, ...)`, `beast.irreg(Y, ...)`, and `beast123(Y, metadata, prior, mcmc, extra)`. The code snippet below provides a starting point for the basic usage. ```R library(Rbeast) data(Nile) # annual streamflow of the Nile River out = beast(Nile, season='none') # 'none': trend-only data without seasonlaity print(out) plot(out) ?Rbeast # See more details about the usage of `beast` tetris() # if you dare to waste a few moments of your life minesweeper() # if you dare to waste a few more moments of your life ``` <table border="0" style='border:none;' bordercolor="#ffffff" width=100% > <tr style='border:none;' > <td valign="center" style='border:none;' > <img height="300" align="left" src="https://github.com/zhaokg/Rbeast/raw/master/R/Images/beach.png"> </td> <td valign="center" style='border:none;' > <img height="300" align="center" src="https://github.com/zhaokg/Rbeast/raw/master/R/Images/Nile.png"> </td> </tr> </table> <!--- [](https://cran.r-project.org/package=Rbeast) ---- ---> <br/> ## Installation for Matlab <a name=matlab> </a> [](https://www.mathworks.com/matlabcentral/fileexchange/72515-rbeast) Install the Matlab version of **BEAST** automatically to a local folder of your choice by running ```Matlab beastPath = 'C:\beast\' eval( webread('http://b.link/rbeast') ) %%%%%%%%%%%%%%%%%%%%%%%%%%% Note on Automatic Installtion %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % 1. Write permission needed for your chosen path; the variable name must be 'beastPath'. % % 2. If webread has a certificate error, run the following line instead: % eval( webread( 'http://b.link/rbeast', weboptions('cert','') ) ) % % 3. If the automatic installation fails, please manually download all the files (see blow) % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% ``` > The above will download all the files in the [Rbeast\Matlab folder at Github](https://github.com/zhaokg/Rbeast) to the chosen folder: if `beastPath` is missing, a default temporary folder (e.g., `C:\Users\$user_name$\AppData\Local\Temp\Rbeast for Windows 10`) will be used. If the automatic script fails, please download the Matlab files from