fit.twoplane: Estimation of animal density from two-plane surveys.

Description Usage Arguments Details Value References Examples

View source: R/fit-ns.r

Description

Estimates animal density (amongst other parameters) from two-plane aerial surveys. This conceptualises sighting locations as a Neyman-Scott point pattern—estimation is carried out via fit.ns().

Usage

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fit.twoplane(points, planes = NULL, d, w, b, l, tau, R,
  edge.correction = "pbc", start = NULL, bounds = NULL, trace = FALSE)

Arguments

points

A vector (or single-column matrix) containing the distance along the transect that each detection was made.

planes

An optional vector containing the plane ID (either 1 or 2) that made the corresponding detection in points.

d

The length of the transect flown (in km).

w

The distance from the transect to which detection of individuals on the surface is certain. This is equivalent to the half-width of the detection zone.

b

The distance from the transect to the edge of the area of interest. Conceptually, the distance between the transect and the furthest distance a whale could be on the passing on the first plane and plausibly move into the detection zone by the passing of the second plane.

l

The lag between planes (in seconds).

tau

Mean dive-cycle duration (in seconds).

R

Truncation distance (see fit.ns).

edge.correction

The method used for the correction of edge effects. Either "pbc" for periodic boundary conditions, or "buffer" for a buffer-zone correction.

start

A named vector of starting values for the model parameters.

bounds

A list with named components. Each component should be a vector of length two, giving the upper and lower bounds for the named parameter.

trace

Logical, if TRUE, parameter values are printed to the screen for each iteration of the optimisation procedure.

Details

This function is simply a wrapper for fit.ns, and facilitates the fitting of the model proposed by Stevenson, Borchers, and Fewster (in prep). This function presents the parameter D.2D (two-dimensional cetacean density in cetaceans per square km) rather than D for enhanced interpretability.

Value

An R6 reference class object. Extraction of the information held within is best handled by functions coef.nspp, confint.nspp, summary.nspp, and plot.nspp.

References

Stevenson, B. C., Borchers, D. L., and Fewster, R. M. (in prep) Trace-contrast methods to account for identification uncertainty on aerial surveys of cetacean populations.

Examples

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fit <- fit.twoplane(points = example.twoplane$points, planes = example.twoplane$planes,
                    d = 500, w = 0.175, b = 0.5, l = 20, tau = 110, R = 1)

b-steve/nspp documentation built on June 4, 2017, 12:10 a.m.