densityVoronoi.tpp: Intensity estimate of temporal point patterns using...

In stlnpp: Spatio-Temporal Analysis of Point Patterns on Linear Networks

Intensity estimate of temporal point patterns using Voronoi-Dirichlet tessellation

Description

adaptive intensity estimation for temporal point patterns using Voronoi-Dirichlet tessellation.

Usage

## S3 method for class 'tpp'
densityVoronoi(X, f = 1, nrep = 1,at=c("points","pixels"),
                               dimt=128,...)

Arguments

X	an object of class tpp
f	fraction (between 0 and 1 inclusive) of the data points that will be used to build a tessellation for the intensity estimate
nrep	number of independent repetitions of the randomised procedure
at	string specifying whether to return the intensity values at a grid of pixel locations and time (at="pixels") or only at the points of X (at="points"). default is to estimate the intensity at pixels
dimt	the number of equally spaced points at which the temporal density is to be estimated. see density
...	arguments passed to densityVoronoi.lpp

Details

This function computes intensity estimates for temporal point patterns using Voronoi-Dirichlet tessellation.

Value

If at="points": a vector of intensity values at the data points of X.

If at="pixels": a vector of intensity values over a grid.

Author(s)

Mehdi Moradi <[e-mail]>, and Ottmar Cronie.

References

Mateu, J., Moradi, M., & Cronie, O. (2019). Spatio-temporal point patterns on linear networks: Pseudo-separable intensity estimation. Spatial Statistics, 100400.

See Also

densityVoronoi.lpp, densityVoronoi.stlpp

Examples

X <- rpoistlpp(0.2,a=0,b=5,L=easynet)
Y <- as.tpp.stlpp(X)
densityVoronoi(Y)

stlnpp documentation built on Nov. 11, 2022, 9:11 a.m.