A nonparametric technique for estimating the cumulative intensity function of a nonhomogeneous Poisson process from one or more realizations on an interval is extended here to include realizations that overlap. This technique does not require any arbitrary parameters from the modeler, and the estimated cumulative intensity function can be used to generate a point process for simulation by inversion.
Arkin, Bradford L. and Leemis, Lawrence, Nonparametric Estimation of the Cumulative Intensity Function for a Nonhomogeneous Poisson Process from Overlapping Realizations (2000). Management Science, 46(7), 875-1012.
This version is the accepted (post-print) version of the manuscript.