Lectures related to Point Processes: Extremal Limit Theorems

Estimating R: Theory of Poisson Processes

Covers the theory of Poisson processes and the estimation of the intensity parameter R.

Simulation & Optimization: Poisson Process & Random Numbers

Explores simulation pitfalls, random numbers, discrete & continuous distributions, and Monte-Carlo integration.

Multivariate Extremes: Applications and Dependence

Explores multivariate extremes, including overwhelming sea defenses and heat waves.

Poisson Process: Density Theory and Applications

Explores Poisson processes, joint density, independence of events, and likelihood estimation.

Extreme Value Analysis: Applications and Consequences

Explores extremal limit theorems and statistical analysis for analyzing extreme events like Venezuela rainfall and Venice data.

Extreme Statistics: Threshold Models

Covers the theory and applications of extreme statistics, focusing on threshold models for analyzing extremes of time series.

Asymptotic Independence Models

Explores extremal limit theorems, statistical analysis, and asymptotic independence models for rare events.

Statistical Analysis of Multivariate Extremes

Covers the statistical analysis of multivariate extremes, including extremal limit theorems and models for extremes of time series.

Estimating Extremal Processes

Explores extremal limit theorems, statistical analysis, and applications of extremal processes in various fields, focusing on modeling extreme events and fitting suitable models.

Estimating R: Marking and Convergence

Covers the estimation of R in Poisson processes, focusing on marking points and convergence.

Gaussian Process: Covariance and Correlation Functions

Explores Gaussian processes, covariance functions, intrinsic stationarity, and extreme applications in statistics.

Statistics of Multivariate Extremes: Inference and Models

Explores theory and applications of multivariate extremes, emphasizing fitting marginal and dependence models together for accurate estimation.

Extreme Value Theory: Point Processes

Covers the application of extreme value theory to point processes and the estimation of extreme events from equally-spaced time series.

Stochastic Models for Communications

Covers stochastic models for communications, focusing on random variables, Markov chains, Poisson processes, and probability calculations.

Rainfall Models: Deterministic vs Stochastic

Covers deterministic and stochastic rainfall models in water resources engineering, including generation, calibration, and spatially explicit models.

Mapping Theorems: Poisson Processes and Intensity Functions

Explores mapping theorems for Poisson processes and their intensity functions.

Mapping and Colouring: Poisson Processes

Covers the theorems of superposition and colouring for Poisson processes.

Point Processes: Extreme Value Theory

Explores point processes in extreme value theory, focusing on modeling exceedances and the theory behind point patterns.

Point Processes: Spatial Analysis

Explores point processes in spatial analysis, focusing on spatial object dissemination and pattern detection.

Extreme Value Theory: Statistical Applications

Explores statistical applications of threshold exceedances and GPD modeling in extreme value theory.