make.prerun.object: combines data, calibration and sets up priors

In FLightR: Reconstruct Animal Paths from Solar Geolocation Loggers Data

combines data, calibration and sets up priors

Description

This function is one step before run.particle.filter. It combines data, calibration, spatial extent and movement priors and estimates spatial likelihoods that used later in the particle filter.

Usage

make.prerun.object(
  Proc.data,
  Grid,
  start,
  end = start,
  Calibration,
  threads = -1,
  Decision = 0.05,
  Direction = 0,
  Kappa = 0,
  M.mean = 300,
  M.sd = 500,
  likelihood.correction = TRUE
)

Arguments

Proc.data	Processed data object created by get.tags.data.
Grid	Spatial grid created by make.grid.
start	release location (lat, lon).
end	end of the track location. Will use start by default. Use NA in case of unknown end point.
Calibration	Calibration object created by make.calibration.
threads	number of parallel threads to use. default is -1, which means FLightR will use all available threads except 1. Value 1 will force sequential evaluation
Decision	prior for migration probability values from 0 to 1 are allowed
Direction	Direction prior for direction of migration (in degrees) with 0 pointing to the North
Kappa	concentration parameter for vonMises distribution, 0 means uniform or even distribution. Will set some prior for direction for all the track, so is not recommended to be changed
M.mean	Prior for mean distance travelled between consecutive twilights, km
M.sd	Prior for sd of distance travelled between consecutive twilights, the higher the value is the wider is the the distribution
likelihood.correction	Should likelihood correction estimated during make.calibration run be used?

Value

Object to be uses in the run.particle.filter

Author(s)

Eldar Rakhimberdiev

Examples

File<-system.file("extdata", "Godwit_TAGS_format.csv", package = "FLightR")
# to run example fast we will cut the real data file by 2013 Aug 20
Proc.data<-get.tags.data(File, end.date=as.POSIXct('2013-07-02', tz='GMT'))
Calibration.periods<-data.frame(
       calibration.start=NA,
       calibration.stop=as.POSIXct("2013-08-20", tz='GMT'),
       lon=5.43, lat=52.93) 
       #use c() also for the geographic coordinates, if you have more than one calibration location
       # (e. g.,  lon=c(5.43, 6.00), lat=c(52.93,52.94))
print(Calibration.periods)

# NB Below likelihood.correction is set to FALSE for fast run! 
# Leave it as default TRUE for real examples
Calibration<-make.calibration(Proc.data, Calibration.periods, likelihood.correction=FALSE)

Grid<-make.grid(left=0, bottom=50, right=10, top=56,
  distance.from.land.allowed.to.use=c(-Inf, Inf),
  distance.from.land.allowed.to.stay=c(-Inf, Inf))

all.in<-make.prerun.object(Proc.data, Grid, start=c(5.43, 52.93),
                             Calibration=Calibration, threads=2)

FLightR documentation built on Oct. 3, 2023, 1:07 a.m.