kdest: Difference of estimated K functions

In smacpod: Statistical Methods for the Analysis of Case-Control Point Data

Description

kdest determines the difference in estimated K functions for a set of cases and controls.

Usage

kdest(x, case = 2, nsim = 0, level = 0.95, r = NULL, breaks = NULL,
  correction = c("border", "isotropic", "Ripley", "translate"),
  nlarge = 3000, domain = NULL, var.approx = FALSE, ratio = FALSE)

Arguments

x	A ppp object from the spatstat package with marks for the case and control groups.
case	The position of the name of the "case" group in levels(x$marks). The default is 2.
nsim	An non-negative integer. Default is 0. The difference in estimated K functions will be calculated for nsim data sets generated under the random labeling hypothesis.
level	Confidence level of confidence envelopes. Ignoried if nsim is 0.
r	Optional. Vector of values for the argument r at which K(r) should be evaluated. Users are advised not to specify this argument; there is a sensible default.
breaks	This argument is for internal use only.
correction	Optional. A character vector containing any selection of the options "none", "border", "bord.modif", "isotropic", "Ripley", "translate", "translation", "none", "good" or "best". It specifies the edge correction(s) to be applied.
nlarge	Optional. Efficiency threshold. If the number of points exceeds nlarge, then only the border correction will be computed (by default), using a fast algorithm.
domain	Optional. Calculations will be restricted to this subset of the window. See Details.
var.approx	Logical. If TRUE, the approximate variance of Kest(r) under CSR will also be computed.
ratio	Logical. If TRUE, the numerator and denominator of each edge-corrected estimate will also be saved, for use in analysing replicated point patterns.

Details

This function relies internally on the Kest and eval.fv functions from the spatstat package. So the arguments are essentially the same as the Kest function. See the documentation of the Kdest for more details about the various arguments.

Value

Returns an fv object. See documentation for spatstat::Kest.

Author(s)

Joshua French

References

Waller, L.A. and Gotway, C.A. (2005). Applied Spatial Statistics for Public Health Data. Hoboken, NJ: Wiley. Kulldorff, M. (1997) A spatial scan statistic. Communications in Statistics – Theory and Methods 26, 1481-1496.

See Also

Kest

Examples

data(grave)
kd1 = kdest(grave)
plot(kd1, iso ~ r, ylab = "difference", legend = FALSE, main = "")
kd2 = kdest(grave, nsim = 9, level = 0.8)
plot(kd2)

smacpod documentation built on May 30, 2017, 4:45 a.m.

Difference of estimated K functions

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Global test of clustering using difference in K functions