Smooth.msr
From spatstat v1.480
by Adrian Baddeley
Smooth a Signed or VectorValued Measure
Apply kernel smoothing to a signed measure or vectorvalued measure.
Usage
"Smooth"(X, ..., drop=TRUE)
Arguments
 X

Object of class
"msr"
representing a signed measure or vectorvalued measure.  ...

Arguments passed to
density.ppp
controlling the smoothing bandwidth and the pixel resolution.  drop

Logical. If
TRUE
(the default), the result of smoothing a scalarvalued measure is a pixel image. IfFALSE
, the result of smoothing a scalarvalued measure is a list containing one pixel image.
Details
This function applies kernel smoothing to a signed measure or
vectorvalued measure X
. The Gaussian kernel is used.
The object X
would typically have been created by
residuals.ppm
or msr
.
Value

A pixel image or a list of pixel images.
For scalarvalued measures, a pixel image (object of class
"im"
) provided drop=TRUE
.
For vectorvalued measures (or if drop=FALSE
),
a list of pixel images; the list also
belongs to the class "solist"
so that it can be printed and plotted.
References
Baddeley, A., Turner, R., Moller, J. and Hazelton, M. (2005) Residual analysis for spatial point processes. Journal of the Royal Statistical Society, Series B 67, 617666.
Baddeley, A., Moller, J. and Pakes, A.G. (2008) Properties of residuals for spatial point processes. Annals of the Institute of Statistical Mathematics 60, 627649.
See Also
Examples
X < rpoispp(function(x,y) { exp(3+3*x) })
fit < ppm(X, ~x+y)
rp < residuals(fit, type="pearson")
rs < residuals(fit, type="score")
plot(Smooth(rp))
plot(Smooth(rs))
Community examples
Looks like there are no examples yet.