initialize.x: Diagnose and initialize light level estimation.

Description

Primarily for the purposes of initializing the estimation, these functions can also be used for diagnostic purposes. position.logp produces grids of simplistic position likelihood for each twilight and uses those to initialize positions for running estimations.

Usage

position.logp(model, x1, x2, xrest = NULL, subset = 1:model$n,
initialize.x = TRUE, start = NULL, end = NULL, prob = 0.8, winoffset = 5)
initialize.x(model, x1, x2, xrest = NULL)
light.quantile(model, chain, day, seg, probl = c(0.025, 0.5, 0.975))
show.segment(model, chain, segment, day, light, k, n = 50, ...)

Value

initialize.x returns a matrix with 3 columns, lon,lat,attenuation

position.logp returns a list with model running components

show.segment is used for its side effect, a plot of light level for a twilight segment

light.quantile returns a numeric vector

Arguments

model: estimation model object
x1: vector of x-coordinates defining the prior grid
x2: vector of y-coordinates defining the prior grid
xrest: value for remaining parameters - default is light attenuation
subset: evaluate subset of segments - default uses all
initialize.x: logical - create initial points for x?
prob: probability - threshold to apply to overlapping quantiles, defaults to 0.8
winoffset: an odd-numbered window size to use when intersecting subseqent segments - defaults to 5

chain: chain object from estimation
day: POSIXct vector of date-times
seg: desired segment
probl: probability level for quantile
start: known position of release
end: known position of recapture

segment: vector of segment data
light: vector of light data
k: desired segment to show
n: length of vector to evaluate
...: additional arguments to be passed to plot

Author

Michael D. Sumner

Details

The primary function here is position.logp, for initializing the estimation for solar.model and metropolis0.