Satellite Geolocation for Animal Tracking

Description Usage Arguments Details Value

Estimate locations by the threshold method assuming a nonstationary observer and errors in estimated twilights

1
2
3

thresholdSensitivity(rise, set, zenith = 96, range = 100, sr.mulog,
  sr.sdlog, ss.mulog, ss.sdlog, sr.proposal, ss.proposal, n.thin = 10,
  n.iters = 1000)

`rise`	observed time of sunrise as POSIXct.
`set`	observed time of sunset as POSIXct.
`zenith`	the solar zenith angle that defines twilight.
`range`	maximum range of travel between twilights (km).
`sr.mulog`	log mean parameter for the Log Normal distribution of sunrise errors.
`sr.sdlog`	log standard deviation parameter for the Log Normal distribution of sunrise errors.
`ss.mulog`	log mean parameter for the Log Normal distribution of sunset errors.
`ss.sdlog`	log standard deviation parameter for the Log Normal distribution of sunset errors.
`sr.proposal`	function for drawing from the proposal distribution for sunrise location.
`ss.proposal`	function for drawing from the proposal distribution for sunrise location.
`n.thin`	rate at which to thin samples.
`n.iters`	total number of samples to draw.

Given the times of a single sunrise and sunset pair, thresholdSensitivity estimates the location of the tagged animal at sunrise and at sunset assuming that during this time the animal moves no further than a given maximum range, and that the observed times of sunrise and sunset contain an additive log Normally distributed error with known mean and variance. These errors are directed so that observed sunrise occurs earlier than true sunrise, and the observed sunset occurs later than true sunrise.

thresholdSensitivity implements a Metropolis sampler to draw samples from the posterior distribution for the sunrise and sunset.

a list with three components