Moderate deviations for some point measures in geometric probability

Yu Baryshnikov, P. Eichelsbacher, T. Schreiber, J. E. Yukich

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


Functionals in geometric probability are often expressed as sums of bounded functions exhibiting exponential stabilization. Methods based on cumulant techniques and exponential modifications of measures show that such functionals satisfy moderate deviation principles. This leads to moderate deviation principles and laws of the iterated logarithm for random packing models as well as for statistics associated with germ-grain models and k nearest neighbor graphs.

Original languageEnglish
Pages (from-to)422-446
Number of pages25
JournalAnnales de l'institut Henri Poincare (B) Probability and Statistics
Issue number3
Publication statusPublished - Jun 1 2008
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


Dive into the research topics of 'Moderate deviations for some point measures in geometric probability'. Together they form a unique fingerprint.

Cite this