Extreme Value Theory: Limiting Distributions and Applications

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (31)

Page 2 of 4

Extreme-Value Theorems

Explores Extremal Types and Exceedance Theorems, GEV, GPD, stability, and limitations in extreme value modeling.

L-Moment Estimation: Probability-Weighted Moments

Covers L-moment estimation, probability-weighted moments, and maximum likelihood inference basics.

Stability Relationships in Distributions

Explores stability relationships, domains of attraction, and limitations in distributions for statistical modeling and analysis.

Extreme Values: Applications and Probability Framework

Explores extreme values in random variables, applications in environmental factors, reliability modeling, block maxima distribution, and the Generalized Extreme Value distribution.

Probability Distributions in Environmental Studies

Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.

Fisher Information, Cramér-Rao Inequality, MLE

Explains Fisher information, Cramér-Rao inequality, and MLE properties, including invariance and asymptotics.

Continuous Random Variables

Covers continuous random variables, probability density functions, and distributions, with practical examples.

Estimating GEV Parameters

Explores techniques for estimating GEV parameters using graphical and likelihood-based methods, illustrated with real-world examples.

Statistics for Data Science: Introduction to Statistical Methods

Covers the fundamental concepts of statistics and their application in data science.

Statistical Estimation: Properties and Distributions

Explores statistical parameter estimation, sample accuracy, and Bernoulli variables' properties.