diveMove (version 1.6.2)

boutinit,data.frame-method: Fit "broken stick" model to log frequency data for identification of bouts of behaviour

Description

Fits "broken stick" model to the log frequencies modelled as a function of x (well, the midpoints of the binned data), using chosen value(s) to separate the two or three processes.

Usage

# S4 method for data.frame
boutinit(obj, x.break, plot = TRUE, ...)
# S4 method for Bouts
boutinit(obj, x.break, plot = TRUE, ...)

Value

(2,N) matrix with as many columns as the number of processes implied by x.break (i.e. length(x.break) + 1). Rows are named a and lambda, corresponding to starting values derived from broken stick model. A plot is produced as a side effect if argument plot is TRUE.

Arguments

obj

Object of class Bouts or data.frame.

x.break

Numeric vector of length 1 or 2 with x value(s) defining the break(s) point(s) for broken stick model, such that x < x.break[1] is 1st process, and x >= x.break[1] & x < x.break[2] is 2nd one, and x >= x.break[2] is 3rd one.

plot

logical, whether to plot results or not.

...

arguments passed to plot (must exclude type).

Methods (by class)

• data.frame: Fit "broken-stick" model on data.frame object

• Bouts: Fit "broken-stick" model on Bouts object

Author

Sebastian P. Luque

Examples

## 2-process
utils::example("rmixexp", package="diveMove", ask=FALSE)
## 'rndproc2' is a random sample vector from the example
xbouts2 <- boutfreqs(rndprocs2, 5)  # Bouts class result
(startval2 <- boutinit(xbouts2, 80))

## 3-process
## 'rndproc3' is a random sample vector from the example
xbouts3 <- boutfreqs(rndprocs3, 5)
(startval3 <- boutinit(xbouts3, c(75, 220)))