minRSE: Optimal Spacing by Simulation

In secrdesign: Sampling Design for Spatially Explicit Capture-Recapture

Optimal Spacing by Simulation

Description

A method to obtain a unique ‘optimal’ spacing from previously simulated scenaios for detector spacing.

Usage

## S3 method for class 'optimalSpacing'
minsimRSE(object, cut = 0.2, plt = FALSE, verbose = FALSE, incr = 0.1, ...)

Arguments

object	optimalSpacing object
cut	numeric maximum \Delta RSE to include
plt	logical; if TRUE a plot is generated
verbose	logical; if TRUE then output includes fitted model
incr	numeric spacing of computed points (R)
...	other arguments passed to plot.optimalSpacing

Details

A quadratic is fitted to the simulated RSE (y) vs simulationR (x), including only values of x and y for which y \le \mbox{min}(y) \times (1+\mbox{cut}). The restriction allows the user to exclude extreme x-values for which the quadratic is a poor fit.

The optimum is the minimum of the quadratic ax^2 + bx + c, given by -b/2a.

The quadratic is fitted with lm (lm(RSE.mean ~ R + I(R^2)).

Value

When verbose = FALSE, a numeric vector with optimum R (multiple of sigma) and corresponding RSE.

When verbose = TRUE, a list with components –

model	fitted model from lm
fitted	dataframe of points on fitted curve
R	optimum R
RSE	minimum RSE

See Also

optimalSpacing

Examples

grid <- make.grid(8, 8, spacing = 20, detector = 'proximity')

# method = "none" uses the shortcut variance
tmp <- optimalSpacing(D = 5, traps = grid, detectfn = "HHN", detectpar = 
    list(lambda0 = 1, sigma = 20), noccasions = 1, nx = 32, 
    fit.function = "secr.fit", method = "none", simulationR = seq(1.2,2.2,0.2))
minsimRSE(tmp, plt = TRUE)

secrdesign documentation built on April 3, 2025, 9:28 p.m.