kdest determines the difference in estimated K
functions for a set of cases and controls. Tolerance
envelopes can also be produced.
kdest(x, case = 2, nsim = 0, level = 0.95, r = NULL, rmax = 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$marks). The default is 2.
x$marks is assumed to be a factor. Automatic
conversion is attempted if it is not.
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. These will be used to construct
the tolerance envelopes.
Level of tolerance envelopes.
Ignored if nsim is 0.
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. If necessary, specify rmax.
Optional. Maximum desired value of the argument \(r\).
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", "rigid",
"none", "good" or "best".
It specifies the edge correction(s) to be applied.
Alternatively correction="all" selects all options.
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 of
Kest.
Logical. If TRUE, the approximate
variance of \(\hat K(r)\) 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 a kdenv object. See documentation
for spatstat::Kest.
This function relies internally on the
Kest and
eval.fv functions from the
spatstat package. The arguments are essentially
the same as the Kest function,
and the user is referred there for more details about
the various arguments.
Waller, L.A. and Gotway, C.A. (2005). Applied Spatial Statistics for Public Health Data. Hoboken, NJ: Wiley.
# NOT RUN {
data(grave)
kd1 = kdest(grave)
plot(kd1, iso ~ r, ylab = "difference", legend = FALSE, main = "")
kd2 = kdest(grave, nsim = 9, level = 0.8)
plot(kd2)
# }
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