densityVoronoi.tpp {stlnpp}

Intensity estimate of temporal point patterns using Voronoi-Dirichlet tessellation

Description

This function performs 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 compute 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.

IF f<1, then nrep independent sub-samples of X are obtained using the function rthin.stlpp. Then for each of the obtained sub-samples, we calculate the Voronoi estimate. The final estimation is the sum of all obtained estimated intensities divided by (f*nrep).

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, density.stlpp

Examples

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