Description Usage Arguments Value Author(s) References Examples
Computes the Movement Coordination Index as described in Mueller, T., et al. (2011).
1 | mci(x)
|
x |
data frame of synchronized relocations of a set of individuals. The data frame must containing the following columns: syncID: numeric (integer), ID marking the synchronization event. For each synchronization event every individual must have a record. Therefore each ID must appear as often as every other ID (e.g. not c(1,1,1,2,2,3,3,3) but c(1,1,1,2,2,2,3,3,3)). utm.easting: numeric, planar x coordinate. Although the name indicates UTM coordinates other planar coordinate systems are also allowed. utm.northing: analogue to utm.easting (Further columns are allowed, but will be ignored. Usually a column naming the individual is present in the data frame.) Such a data frame is returned by the function |
Returns a numeric vector of MCI values, one for each pair of subsequent synchronization events.
Martin Rimmler (maintainer, martin.rimmler[AT]gmail.com), Thomas Mueller
Mueller, T., et al. (2011) How landscape dynamics link individual- to population-level movement patterns: a multispecies comparison of ungulate relocation data, Global Ecology and Biogeography, 20, pages 683–694.
1 2 3 4 5 6 7 8 9 10 11 | # load example data
data(gazelleRelocations)
# create input data frame
syncRelocs <- syncSubsample(x = gazelleRelocations,
startSearch = "2007-09-05 00:00:00",
syncIntervalSecs = 3600*24*16,
syncAccuracySecs = 3600*24)
# calculate MCI
mci(syncRelocs$data[[1]])
|
[1] 0.317825616 0.153706396 0.011148805 0.333439694 0.327357176
[6] -0.129572617 0.035848357 0.089358466 0.480498041 0.184815286
[11] 0.730352983 0.001592177 0.506946448 0.162653450 0.301404987
[16] -0.123385509 0.019643408 -0.226141832 -0.107816261
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