Statistical Analysis of Multivariate Extremes

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Related lectures (32)

Page 2 of 4

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

Simulation & Optimization: Poisson Process & Random Numbers

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

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.

Extreme Value Theory: Statistical Applications

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

Information Theory: Review and Mutual Information

Reviews information measures like entropy and introduces mutual information as a measure of information between random variables.

Extreme Value Theory: Applications to Time Series

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

Estimating R: Theory of Poisson Processes

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

Gaussian Process: Covariance and Correlation Functions

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

Stochastic Models for Communications

Covers mathematical tools for communication systems and data science, including information theory and signal processing.

Mutual Information and Entropy

Explores mutual information and entropy calculation between random variables.