K.diff.single: K.diff.single function

In bentaylor1/lgcp: Log-Gaussian Cox Process

Description

A function to find the minimum contrast (squared discrepancy) value based on the K function, for one specific value of phi (spatial scale) and one specific value of sigma^2 (spatial variance) for the LGCP.

Usage

K.diff.single(ps, khat, useq, model, transform, power, ...)

Arguments

ps	A numeric vector of length 2 giving the values of phi and sigma^2, in that order.
khat	A numeric vector giving the nonparametric estimate of the K function at all distances specified in useq (see below)
useq	An increasing, equally spaced numeric vector giving the spatial distances at which the contrast criterion is to be evaluated.
model	A character string specifying the form of the theoretical spatial correlation function (matches 'model' argument for CovarianceFct in the RandomFields packages).
transform	A scalar-valued function which performs a numerical transformation of its argument. Used for calibration of the contrast criterion, by transforming both parametric and nonparametric forms of the K function.
power	A scalar used for calibration of the contrast criterion: the power which to raise the parametric and nonparametric forms of the K function to.
...	Additional arguments if required for definition of the correlation function as per 'model'. See ?CovarianceFct (RandomFields).

Value

A single numeric value providing the minimum contrast value for the specified value of the ps argument.

bentaylor1/lgcp documentation built on May 12, 2019, 2:09 p.m.