Smooth a Signed or Vector-Valued Measure
Apply kernel smoothing to a signed measure or vector-valued measure.
## S3 method for class 'msr' Smooth(X, ..., drop=TRUE)
X |
Object of class |
... |
Arguments passed to |
drop |
Logical. If |
This function applies kernel smoothing to a signed measure or
vector-valued measure X. The Gaussian kernel is used.
The object X would typically have been created by
residuals.ppm or msr.
A pixel image or a list of pixel images.
For scalar-valued measures, a pixel image (object of class
"im") provided drop=TRUE.
For vector-valued 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.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au
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, 617–666.
Baddeley, A., Moller, J. and Pakes, A.G. (2008) Properties of residuals for spatial point processes. Annals of the Institute of Statistical Mathematics 60, 627–649.
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))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.