PartitionParameters

a <code>windowsweep</code> object, i.e. the output of the 
<code><a rd-options="" href="/link/WindowSweep?package=bcpa&version=1.3.2" data-mini-rdoc="bcpa::WindowSweep">WindowSweep</a></code> function.

windowsweep

type of estimate to output, whether "smooth" or "flat".

type

the temporal range within which changepoints are 
considered to be within the same cluster (for a "smooth" BCPA).

clusterwidth

Partitions - and, ultimately, estimates - all parameters of a BCPA, either 
as a rolling average (smooth BCPA), or as constant values within fixed 
change points (flat BCPA).

The Behavioral Change Point Analysis (BCPA) is a method of
identifying hidden shifts in the underlying parameters of a time series,
developed specifically to be applied to animal movement data which is
irregularly sampled. The method is based on: E. Gurarie, R. Andrews and
K. Laidre A novel method for identifying behavioural changes in animal
movement data (2009) Ecology Letters 12:5 395-408. A development version is
on <https://github.com/EliGurarie/bcpa>. NOTE: the BCPA method may be useful
for any univariate, irregularly sampled Gaussian time-series, but animal
movement analysts are encouraged to apply correlated velocity change point
analysis as implemented in the smoove package, as of this writing on GitHub
at <https://github.com/EliGurarie/smoove>. An example of a univariate analysis
is provided in the UnivariateBCPA vignette.

Eliezer Gurarie

bcpa

Behavioral Change Point Analysis of Animal Movement

PartitionParameters function

a <code>windowsweep</code> object, i.e. the output of the 
<code><a rd-options='' href='WindowSweep'>WindowSweep</a></code> function.

PartitionParameters: Partition parameters

Description

Usage

Arguments

Value

See Also