thresholdSensitivity: Threshold Geolocation Sensitivity

Description Usage Arguments Details Value

Description

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

Usage

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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)

Arguments

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.

Details

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.

Value

a list with three components

p0

the threshold estimate

rise

the sampled sunrise locations as a two column matrix

set

the sampled sunset locations as a two column matrix


KateGoodenough/RoL-SGAT documentation built on June 11, 2019, 1:29 p.m.