Rubinstein distance on configurations spaces
classification
🧮 math.PR
keywords
configurationsdistancemethodpoissonprocessrubinsteinabsolutelyapplication
read the original abstract
By a method inspired of the Stein's method, we derive an upper-bound of the Rubinstein distance between two absolutely continuous probability measures on configurations space. As an application, we show that the best way to approximate a Modulated Poisson Process (see below for the definition) by a Poisson process is to equate their intensity.
This paper has not been read by Pith yet.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.