Introduces continuous time Markov chains on a finite state space with exponential waiting times and jump probabilities.
Explores the Poisson process approach in extreme value analysis, emphasizing component-wise transformations and likelihood functions for extreme events.
Discusses important theorems related to Poisson processes and their applications in analyzing exceedances and likelihood.
Explores extremal limit theorems, Gaussian processes, and modeling rare events in spatial problems and time series.
