Satellite Geolocation for Animal Tracking

essieCurveModel

R Documentation

Curve Model Structures (Essie)

Description

Curve Model Structures for Essie

Usage

essieCurveModel(
  time,
  light,
  segment,
  calibration,
  alpha,
  beta,
  logp0 = function(k, x) 0,
  x0,
  fixed = FALSE,
  dt = NULL
)

Arguments

`time`	vector of sample times as POSIXct.
`light`	vector of observed (log) light levels.
`segment`	vector of integers that assign observations to twilight segments.
`calibration`	function that maps zenith angles to expected light levels.
`alpha`	parameters of the twilight model.
`beta`	parameters of the behavioural model.
`logp0`	function to evaluate any additional contribution to the log posterior from the twilight locations.
`x0`	suggested starting points for twilight locations.
`fixed`	logical vector indicating which twilight locations to hold fixed.
`dt`	time intervals for speed calculation in hours.

Details

Essie requires a model structure that describes the model being fitted. This function generates basic model structures for curve fitting metthods that should provide a suitable starting point for most analyses.

The essieCurveModel function constructs a model structure assuming that each twilight profile is associated with a single location. The errors in observed log light level are assumed to be Normally distributed about their expected value.

The properties of the twilight model are determined by alpha, which must be a vector of parameters that are to be applied to each twilight.

The initialization locations x0 are only required when specifying fixed locations.

Essie assumes that the average speed of travel between successive locations is Gamma distributed. By default, the speed of travel is calculated based on the time intervals between the twilights (in hours), but the intervals of time actually available for travel can be specified directly with the dt argument. The parameters beta[1] and beta[2] specify the shape and rate of the Gamma distribution of speeds.

Value

a list with components

`logpk`	function to evaluate the contributions to the log posterior from the k-th twilight
`logpbk`	function to evaluate contribution to the log posterior from the behavioural model for the k-th track segment.
`fixed`	a logical vector indicating which locations should remain fixed.
`x0`	an array of initial twilight locations.
`time`	the twilight times.
`rise`	the sunrise indicators.
`alpha`	the twilight model parameters.
`beta`	the behavioural model parameters.