Bandwidth Selection for Diffusion Smoother by Likelihood Cross-Validation
Selects an optimal bandwidth for diffusion smoothing by point process likelihood cross-validation.
bw.pplHeat(X, ..., srange=NULL, ns=16, sigma=NULL,
leaveoneout=TRUE, verbose = TRUE)X |
Point pattern (object of class |
... |
Arguments passed to |
srange |
Numeric vector of length 2 specifying a range of bandwidths to be considered. |
ns |
Integer. Number of candidate bandwidths to be considered. |
sigma |
Maximum smoothing bandwidth.
A numeric value, or a pixel image, or a |
leaveoneout |
Logical value specifying whether intensity values at data points should be estimated using the leave-one-out rule. |
verbose |
Logical value specifying whether to print progress reports. |
This algorithm selects the optimal global bandwidth for
kernel estimation of intensity for the dataset X
using diffusion smoothing densityHeat.ppp.
If sigma is a numeric value, the algorithm finds the
optimal bandwidth tau <= sigma.
If sigma is a pixel image or function, the algorithm
finds the optimal fraction 0 < f <= 1 such that
smoothing with f * sigma would be optimal.
A numerical value giving the selected bandwidth
(if sigma was a numeric value)
or the selected fraction of the maximum bandwidth
(if sigma was a pixel image or function).
The result also belongs to the class "bw.optim" which can be
plotted.
Adrian Baddeley and Tilman Davies.
bw.CvLHeat for an alternative method.
online <- interactive()
if(!online) op <- spatstat.options(npixel=32)
f <- function(x,y) { dnorm(x, 2.3, 0.1) * dnorm(y, 2.0, 0.2) }
X <- rpoint(15, f, win=letterR)
plot(X)
b <- bw.pplHeat(X, sigma=0.25)
b
plot(b)
if(!online) spatstat.options(op)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.