plugincvc: Plug-in moment covariance estimator

In lacunaritycovariance: Gliding Box Lacunarity and Other Metrics for 2D Random Closed Sets

Plug-in moment covariance estimator

Description

This function computes the plug-in moment covariance estimate of a stationary RACS from a binary map. For a stationary RACS, \Xi, the covariance for a vector v is the probability of two points separated by a vector v are covered by \Xi

C(v) = P(\{x,x+v\}\subseteq \Xi).

Usage

plugincvc(xi, obswin = NULL, setcov_boundarythresh = NULL)

Arguments

xi	An observation of a RACS of interest as a full binary map (as an im object) or as the foreground set (as an owin object). In the latter case the observation window, obswin, must be supplied.
obswin	If xi is an owin object then obswin is an owin object that specifies the observation window.
setcov_boundarythresh	To avoid instabilities caused by dividing by very small quantities, if the set covariance of the observation window is smaller than setcov_boundarythresh, then the covariance is given a value of NA.

Details

The plug-in moment covariance estimator is (Serra, 1982)

\hat{C}(v) = \frac{\gamma_{W\cap X}(v)}{\gamma_W(v)}

where \gamma_{W}(v) is the set covariance of the observation window W and \gamma_{W\cap X}(v) is the set covariance of the foreground within W. plugincvc uses Fourier transforms to calculate the set covariance (using the setcov of the foreground and observation window. Vectors with small \gamma_W(v) are eliminated using setcov_boundarythresh as division by small values is numerically unstable.

Value

A SpatStat im object containing the estimated covariance.

Author(s)

Kassel Liam Hingee

References

Serra, J.P. (1982) Image Analysis and Mathematical Morphology. London; New York: Academic Press.

Examples

xi <- as.im(heather$coarse, na.replace = 0)
covar <- plugincvc(xi)

lacunaritycovariance documentation built on Nov. 2, 2023, 6:08 p.m.