ChangePointSummary: Obtain summary of BCPA analysis

In bcpa: Behavioral Change Point Analysis of Animal Movement

Obtain summary of BCPA analysis

Description

Produces a summary of change points for a "flat" analysis, identifying phases (periods between change points) with estimated parameters, clustering neighboring ones according to a kernel density of the windowsweep breaks.

Usage

ChangePointSummary(windowsweep, clusterwidth = 1, tau = TRUE)

Arguments

windowsweep	a windowsweep object, i.e. the output of the WindowSweep function.
clusterwidth	the temporal range within which change points are considered to be within the same cluster. Corresponds to the bandwidth of the density of the break distribution.
tau	logical, whether to estimate the characteristic time tau (preferred) or not. If FALSE, the autocorrelation parameter rho is calculated.

Value

a list containing two elements:

breaks	a data frame containing columns: middle - each change point, size - the number of windows that selected the change point, modelmode - the most frequently selected of the seven possible models (M0 - the null model - is excluded), and middle.POSIX - the mid-point as a POSIX time object.
phases	a data frame containing columns mu.hat, s.hat, rho.hat - the estimated mean, standard deviation, and time scale (or auto-correlation) within each phase (i.e. period between change points), t0 - the beginning of the phase, t1 - the end of the phase, and interval - the total duration of the phase.

Author(s)

Eliezer Gurarie

See Also

WindowSweep

Examples

if(!exists("Simp.VT")){
 data(Simp)
 Simp.VT <- GetVT(Simp)}
if(!exists("Simp.ws"))
 Simp.ws <- WindowSweep(Simp.VT, "V*cos(Theta)", windowsize = 50, windowstep = 1, progress=TRUE)
# too many change points:
ChangePointSummary(Simp.ws)
# about the right number of change points:
ChangePointSummary(Simp.ws, clusterwidth=3)

bcpa documentation built on May 30, 2022, 5:07 p.m.