Select a common bandwidth for kernel regression estimation of type-specific probabilities of a multivariate Poisson point process with independent component processes of each categorical type by maximizing the cross-validate log-likelihood function.
cvloglk(pts, marks, t = NULL, h)matrix containing the x,y-coordinates of the point
locations.
numeric/character vector of the marked labels of the type of each point.
numeric vector of the associated time-periods, default NULL
for pure spatial data.
numeric vector of the kernel smoothing bandwidths at which to calculate the cross-validated log-likelihood function.
A list with components
vector of the values of the cross-validated Log-likelihood function.
numeric value which maximizing the cross-validate log-likelihood function
copy of the arguments pts, marks, h.
Select a common bandwidth for kernel regression of type-specific
probabilities for all time-periods when the argument t is not
NULL, in which case the data is of a multivariate spatial-temporal
point process, with t the values of associated time-periods.
Diggle, P.J., Zheng, P. and Durr, P. A. (2005) Nonparametric estimation of spatial segregation in a multivariate point process: bovine tuberculosis in Cornwall, UK. J. R. Stat. Soc. C, 54, 3, 645--658.
phat, mcseg.test, and
mcpat.test