simdata: Simulated time series to test BEAST

In Rbeast: Bayesian Change-Point Detection and Time Series Decomposition

Simulated time series to test BEAST

Description

simdata is a 300 x 3 matrix, consisting three time series of length 300. Currently, the three time series are the same. It is used to illustrate BEAST can handle multiple time series at a single function call. of BEAST.

Usage

    data(simdata)

Source

Rbeast v0.9.2

References

1. Zhao, K., Wulder, M.A., Hu, T., Bright, R., Wu, Q., Qin, H., Li, Y., Toman, E., Mallick, B., Zhang, X. and Brown, M., 2019. Detecting change-point, trend, and seasonality in satellite time series data to track abrupt changes and nonlinear dynamics: A Bayesian ensemble algorithm. Remote Sensing of Environment, 232, p.111181 (the beast algorithm paper).

2. Zhao, K., Valle, D., Popescu, S., Zhang, X. and Mallick, B., 2013. Hyperspectral remote sensing of plant biochemistry using Bayesian model averaging with variable and band selection. Remote Sensing of Environment, 132, pp.102-119 (the Bayesian MCMC scheme used in beast).

3. Hu, T., Toman, E.M., Chen, G., Shao, G., Zhou, Y., Li, Y., Zhao, K. and Feng, Y., 2021. Mapping fine-scale human disturbances in a working landscape with Landsat time series on Google Earth Engine. ISPRS Journal of Photogrammetry and Remote Sensing, 176, pp.250-261(a beast application paper).

Examples

 library(Rbeast)
 data(simdata)
 plot(simdata[,1],type='l')
 
 ## Not run:  
 #out=beast123(simdata) # Error: whichDimIsTime has to be specified. See below
 out=beast123(simdata, metadata=list(whichDimIsTime=1))  
 
 plot(out,1)
 plot(out,2)
 plot(out,3)
 
## End(Not run)

Rbeast documentation built on May 31, 2023, 9:23 p.m.