Estimating Extremal Processes

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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.

Extreme Value Theory: Maxima and Exceedances

Delves into Extreme Value Theory, discussing maxima, exceedances, and their statistical implications.

Precipitation and Hydrologic Design

Covers methods to define the design storm, empirical distribution of rainfall maxima, Gumbel distribution, and intensity-duration-frequency relationships.

Optimization and Simulation

Introduces discrete event simulation through the example of Rico at Satellite, emphasizing the importance of statistical analysis.

Poisson Process: Density Theory and Applications

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

Extreme Value Theory: Statistical Applications

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

Elements of Statistics: Estimation & Distributions

Covers fundamental statistics concepts, including estimation theory, distributions, and the law of large numbers, with practical examples.

Quantitative Risk Management: Copulas and Generative Adversarial Networks

Explores copulas, simulation algorithms, fitting data with rank correlations, and GANs for image generation.

Weather Events and Climate Change: Understanding the Impact

Explores the impact of weather events on climate change, emphasizing human influence and statistical analysis.

Gaussian Process: Covariance and Correlation Functions

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