find.stationary.location {FLightR} | R Documentation |
find unknown calibration location
Description
Functions attempts to find a location where The function attempts to find a location for a time period assuming animal was not moving. Does not work well will shaded data!
Usage
find.stationary.location(
Proc.data,
calibration.start,
calibration.stop,
plot = TRUE,
initial.coords = NULL,
print.optimization = TRUE,
reltol = 1e-04
)
Arguments
Proc.data |
processed data object generated by |
calibration.start |
POSIXct time when stationary period started |
calibration.stop |
POSIXct time when stationary period ended |
plot |
plots every iteration |
initial.coords |
location vector with initial values for location (longitude and latitude). Should be close (+-2000 km from the real location) |
print.optimization |
do you want every optimization iteration to be printed? If TRUE - Lon, Lat, calibration mean and calibration sd are being printed. Optimization tries to minimize the latter. |
reltol |
tolerance for optimization, see |
Details
The idea behind the function is that it tries to minimize variance between slopes for the whole period by optimizing location. It can be seen as an extension of Hill-Ekstrom calibration idea.
Value
vector with coordinates - longitude and latitude.
Author(s)
Eldar Rakhimberdiev
Examples
#this example takes about 15 minutes to run
File<-system.file("extdata", "Godwit_TAGS_format.csv", package = "FLightR")
Proc.data<-get.tags.data(File)
plot_slopes_by_location(Proc.data=Proc.data, location=c(5.43, 52.93))
abline(v=as.POSIXct("2013-08-20", tz='GMT')) # end of first calibration period
abline(v=as.POSIXct("2014-05-05", tz='GMT')) # start of the second calibration period
Location<-find.stationary.location(Proc.data, '2013-07-20', '2013-08-20', initial.coords=c(10, 50))