Ldot.inhom(X, i, ...)
X
from which distances are measured.
A character string (or something that will be converted to a
character string).
Defaults to the first level of marks(X)
.Kdot.inhom
."fv"
(see fv.object
).Essentially a data frame containing numeric columns
"border"
, "bord.modif"
,
"iso"
and/or "trans"
,
according to the selected edge corrections. These columns contain
estimates of the function $L_{i\bullet}(r)$
obtained by the edge corrections named.Ldot
to include an adjustment for spatially inhomogeneous intensity,
in a manner similar to the function Linhom
. All the arguments are passed to Kdot.inhom
, which
estimates the inhomogeneous multitype K function
$K_{i\bullet}(r)$ for the point pattern.
The resulting values are then
transformed by taking $L(r) = \sqrt{K(r)/\pi}$.
i
is interpreted as
a level of the factor X$marks
. It is converted to a character
string if it is not already a character string.
The value i=1
does not
refer to the first level of the factor.
}
Ldot
,
Linhom
,
Kdot.inhom
,
Lcross.inhom
.# Estimate intensities by nonparametric smoothing lambdaM <- density.ppp(ma, sigma=0.15, at="points") lambdadot <- density.ppp(lg, sigma=0.15, at="points") L <- Ldot.inhom(lansing, "maple", lambdaI=lambdaM, lambdadot=lambdadot)
# synthetic example: type A points have intensity 50, # type B points have intensity 50 + 100 * x lamB <- as.im(function(x,y){50 + 100 * x}, owin()) lamdot <- as.im(function(x,y) { 100 + 100 * x}, owin()) X <- superimpose(A=runifpoispp(50), B=rpoispp(lamB)) L <- Ldot.inhom(X, "B", lambdaI=lamB, lambdadot=lamdot)