locFun: BiVariate Gaussian Bridge Stats
In MovingUngulate/Part: Ungulate Parturition Modeling and Predicting

Description Usage Arguments Value Examples

Create BiVariate Gaussian Bridge Stats using the move package. Specifically creates parallel and orthogonal variance measures in format to append to data.frame of movement data. This can be a lengthy process and therefore, this code is internally parallelized. You must give an ncpus > 1 to run in parallel.

1	locFun(vidat, locdat)

`data`	GPS data either as data.frame
`xname`	name of X coordinate column
`yname`	name of Y coordinate column
`timename`	name of POSIX time/date column
`idname`	name of unique identifier for each animal column
`projstring`	Correct proj4string for the data/coordinates
`ncpus`	Number of CPUs for parallel processing. Recommend 1-2 less than max.
`msize`	Margin size for dynBGB. Defaults to 21.
`winsize`	Window size for dynBGB. Defaults to 43.

Resulting object is a data.frame of original data with dynBGB parameters added as columns. See Kraunstauber 2015 for more info.

`paraSd`	Parallel Variance Measure
`orthSd`	orthogonal variance measure

1 2	BGBFun(data=df, xname='Easting',yname='Northing',timename='TelemDate',idname='Serial', projstring='+proj=longlat +datum=WGS84 +no_defs',ncpus=6,msize=21,winsize=43)