dynBGBvariance-methods: Calculates the Bivariate Gaussian Bridge motion variance

In move: Visualizing and Analyzing Animal Track Data

Calculates the Bivariate Gaussian Bridge motion variance

Description

A function to calculate the dynamic Bivariate Gaussian Bridge orthogonal and parallel variance for a movement track

Usage

dynBGBvariance(move, locErr, margin, windowSize,...)

Arguments

move	a move object. This object must be in a projection different to longitude/latitude, use spTransform to transform your coordinates.
locErr	single numeric value or vector of the length of coordinates that describes the error of the location (sender/receiver) system in map units. Or a character string with the name of the column containing the location error can be provided.
margin	The margin used for the behavioral change point analysis. This number has to be odd.
windowSize	The size of the moving window along the track. Larger windows provide more stable/accurate estimates of the brownian motion variance but are less well able to capture more frequent changes in behavior. This number has to be odd.
...	Additional arguments

Details

The function uses windowApply with the BGBvarbreak function in order to implement a dynamic calculation of the variance

Value

a dBGBvariance-class object

Author(s)

Bart Kranstauber & Anne Scharf

References

Kranstauber, B., Safi, K., Bartumeus, F.. (2014), Bivariate Gaussian bridges: directional factorization of diffusion in Brownian bridge models. Movement Ecology 2:5. doi:10.1186/2051-3933-2-5.

See Also

dynBGB, brownian.motion.variance.dyn

Examples

data(leroy)
leroy <- leroy[230:265,]

## change projection method to aeqd and center the coordinate system to the track
dataAeqd <- spTransform(leroy, CRSobj="+proj=aeqd +ellps=WGS84", center=TRUE)

dBGBvar <- dynBGBvariance(dataAeqd, locErr=9, windowSize=31, margin=15)
dBGBvar

move documentation built on July 9, 2023, 6:09 p.m.