spdensity
computes a kernel smoothed spatial
density function from a point pattern. This function is
basically a wrapper for density.ppp
.
The density.ppp
function computes
the spatial intensity of a point pattern; the spdensity
function scales the intensity to produce a true spatial density.
spdensity(
x,
sigma = NULL,
...,
weights = NULL,
edge = TRUE,
varcov = NULL,
at = "pixels",
leaveoneout = TRUE,
adjust = 1,
diggle = FALSE,
kernel = "gaussian",
scalekernel = is.character(kernel),
positive = FALSE,
verbose = TRUE
)
This function produces the spatial density of x
as an object of class im
.
Point pattern (object of class "ppp"
).
The smoothing bandwidth (the amount of smoothing).
The standard deviation of the isotropic smoothing kernel.
Either a numerical value,
or a function that computes an appropriate value of sigma
.
Additional arguments passed to pixellate.ppp
and as.mask
to determine
the pixel resolution, or passed to sigma
if it is a function.
Optional weights to be attached to the points.
A numeric vector, numeric matrix, an expression
,
or a pixel image.
Logical value indicating whether to apply edge correction.
Variance-covariance matrix of anisotropic smoothing kernel.
Incompatible with sigma
.
String specifying whether to compute the intensity values
at a grid of pixel locations (at="pixels"
) or
only at the points of x
(at="points"
).
Logical value indicating whether to compute a leave-one-out
estimator. Applicable only when at="points"
.
Optional. Adjustment factor for the smoothing parameter.
Logical. If TRUE
, use the Jones-Diggle improved edge correction,
which is more accurate but slower to compute than the default
correction.
The smoothing kernel.
A character string specifying the smoothing kernel
(current options are "gaussian"
, "epanechnikov"
,
"quartic"
or "disc"
),
or a pixel image (object of class "im"
)
containing values of the kernel, or a function(x,y)
which
yields values of the kernel.
Logical value.
If scalekernel=TRUE
, then the kernel will be rescaled
to the bandwidth determined by sigma
and varcov
:
this is the default behaviour when kernel
is a character string.
If scalekernel=FALSE
, then sigma
and varcov
will be ignored: this is the default behaviour when kernel
is a
function or a pixel image.
Logical value indicating whether to force all density values to
be positive numbers. Default is FALSE
.
Logical value indicating whether to issue warnings about numerical problems and conditions.
Joshua French
Waller, L.A. and Gotway, C.A. (2005). Applied Spatial Statistics for Public Health Data. Hoboken, NJ: Wiley.
density.ppp
data(grave)
contour(spdensity(grave))
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