Günter Last is Professor of Stochastics at the Karlsruhe Institute of Technology, Germany. He is a distinguished probabilist with particular expertise in stochastic geometry, point processes, and random measures. He coauthored a research monograph on marked point processes on the line as well as two textbooks on general mathematics. He has given many invited talks on his research worldwide. Mathew Penrose is Professor of Probability at the University of Bath. He is an internationally leading researcher in stochastic geometry and applied probability and is the author of the influential monograph Random Geometric Graphs (2003). He received the Friedrich Wilhelm Bessel Research Award from the Humboldt Foundation in 2008, and has held visiting positions as guest lecturer in New Delhi, Karlsruhe, San Diego, Birmingham, and Lille.

'An understanding of the remarkable properties of the Poisson process is essential for anyone interested in the mathematical theory of probability or in its many fields of application. This book is a lucid and thorough account, rigorous but not pedantic, and accessible to any reader familiar with modern mathematics at first degree level. Its publication is most welcome.' J. F. C. Kingman, University of Bristol

• Preface; List of symbols; 1. Poisson and other discrete distributions; 2. Point processes; 3. Poisson processes; 4. The Mecke equation and factorial measures; 5. Mappings, markings and thinnings; 6. Characterisations of the Poisson process; 7. Poisson processes on the real line; 8. Stationary point processes; 9. The Palm distribution; 10. Extra heads and balanced allocations; 11. Stable allocations; 12. Poisson integrals; 13. Random measures and Cox processes; 14. Permanental processes; 15. Compound Poisson processes; 16. The Boolean model and the Gilbert graph; 17. The Boolean model with general grains; 18. Fock space and chaos expansion; 19. Perturbation analysis; 20. Covariance identities; 21. Normal approximation; 22. Normal approximation in the Boolean model; Appendix A. Some measure theory; Appendix B. Some probability theory; Appendix C. Historical notes; References; Index.