This is a collection of functions that allows one to perform the behavioral change point analysis (BCPA) as described by Gurarie et al. (2009). The key features are estimation of discrete changes in time-series data, notably linear and turning components of gappy velocity times series extracted from movement data.
The package has been on CRAN for a while. The version here is a minor update to address some technical R-check issues. Its development on the Git page will be minimal, mainly because a superior tool for estimating behavioral changes from mechanistic continuous time movement models is available in the
smoove package: https://github.com/EliGurarie/smoove. Animal movement analysts are encouraged to switch to using those tools instead (see Gurarie et al. 2017).
bcpa can be very useful for the identification of structural changes of one-dimensional, Gaussian, irregularly sampled time-series, which can come up in many applications, not necessarily related to movement.
For example, here is a link detailing how to apply this tool directly to a univariate time series: http://htmlpreview.github.io/?https://github.com/EliGurarie/bcpa/blob/master/examples/UnivariateBCPA.html.
Gurarie, E., R. Andrews and K. Laidre. 2009. A novel method for identifying behavioural changes in animal movement data. Ecology Letters 12: 395-408.
Gurarie, E., C. Fleming, W.F. Fagan, K. Laidre, J. Hernández-Pliego, O. Ovaskainen. 2017. Correlated velocity models as a fundamental unit of animal movement: synthesis and applications. Movement Ecology 5:13.
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