kd determines the difference in estimated K functions for a set of cases and controls.
kd(x, case = 2, r = NULL, breaks = NULL, correction = c("border",
"isotropic", "Ripley", "translate"), nlarge = 3000, domain = NULL,
var.approx = FALSE, ratio = FALSE)A ppp object from the spatstat package with marks for the case and control groups.
The position of the name of the "case" group in levels(x$marks). The default is 2.
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.
This argument is for internal use only.
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.
Optional. Efficiency threshold. If the number of points exceeds nlarge, then only the border correction will be computed (by default), using a fast algorithm.
Optional. Calculations will be restricted to this subset of the window. See Details.
Logical. If TRUE, the approximate variance of Kest(r) under CSR will also be computed.
Logical. If TRUE, the numerator and denominator of each edge-corrected estimate will also be saved, for use in analysing replicated point patterns.
Returns an fv object. See documentation for spatstat::Kest.
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.
# NOT RUN {
data(grave)
# kd = kd(grave)
# plot(kd)
# }
Run the code above in your browser using DataLab