Multivariate Extremes: Applications and Dependence

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Extreme Value Theory: Applications to Time Series

Explores Extreme Value Theory applications to time series, discussing extremogram, moving maxima, and rare event threshold sequences.

Statistics of Multivariate Extremes: Inference and Models

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

Gaussian Process: Covariance and Correlation Functions

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

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.

Estimating R: Theory of Poisson Processes

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

Statistics of Multivariate Extremes

Covers extremal limit theorems, basic statistical analysis, and applications to multivariate extremes, emphasizing the importance of understanding the distribution of maxima.

Modeling Extremal Processes

Explores extremal limit theorems, Gaussian processes, and modeling rare events in spatial problems and time series.

Extreme Value Theory: Statistical Applications

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

Size Distribution of Drops and Ice Crystals

Explores the statistical summary of drop properties and the significance of drop size distribution in cloud and precipitation formation.

Mapping and Colouring: Poisson Processes

Covers the theorems of superposition and colouring for Poisson processes.