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SUMMARY:Efficient non-parametric estimation of compound Poisson processes.
  - Alberto Coca Cabrero (CCA)
DTSTART:20141126T160000Z
DTEND:20141126T170000Z
UID:TALK55516@talks.cam.ac.uk
CONTACT:Eavan Gleeson
DESCRIPTION:Compound Poisson processes are the building blocks of models f
 or occurrence of random events at random times. They are used in a myriad 
 of applications ranging from queueing theory and seismology to insurance a
 nd finance\, so efficient estimation of their characteristics is of great 
 importance. We will speak of our recent developments in this area\, includ
 ing a Donsker theorem for the distribution of the size of the events. The 
 talk is aimed at students with undergraduate level of probability but no n
 ecessarily any exposure to the topics below\, as this talk will serve as a
  quick introduction to them. We are planning to:\n\ni) introduce the CPP a
 nd its applications\;\nii) describe the non-parametric estimation problem 
 and its relationship to non-linear inverse problems\;\niii) construct an e
 stimator of the aforementioned distribution and state some basic results t
 o build intuition\;\niv) introduce the classical Glivenko-Cantelli and Don
 sker theorems from empirical process theory\;\nv) state our Donsker theore
 m and its applications and mention extensions and related literature\;
LOCATION:MR14\, Centre for Mathematical Sciences
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