Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Quizes
Exercises
Publications
Startups
Units
Show all results for
Home
Lecture
Modeling Extremal Processes
Graph Chatbot
Related lectures (34)
Probabilistic Models for Linear Regression
Covers the probabilistic model for linear regression and its applications in nuclear magnetic resonance and X-ray imaging.
Linear Combinations: Moment-Generating Functions
Explores moment-generating functions, linear combinations, and normality of random variables.
Simulation & Optimization: Poisson Process & Random Numbers
Explores simulation pitfalls, random numbers, discrete & continuous distributions, and Monte-Carlo integration.
Testing: t-tests
Covers t-tests, p-values calculation, and comparison of coefficients.
Probabilistic Linear Regression
Explores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.
Statistical Inference and Machine Learning
Covers statistical inference, machine learning, SVMs for spam classification, email preprocessing, and feature extraction.
Bayesian Estimation: Unsupervised Learning & MCMC
Explores Bayesian estimation for unsupervised learning and MCMC, using a Spin Glass Card game example.
Statistical Inference: Model Selection and Nuisance Parameters
Covers model selection, nuisance parameters, and higher-order inference methods in statistical inference.
Exponential Family
Covers the properties of the exponential family and the estimation of parameters.
Assumption-lean Inference: Generalised Linear Model Parameters
Explores assumption-lean inference for statistical estimands in generalised linear models, emphasizing robust and generic approaches.
Probabilities and Statistics: Key Theorems and Applications
Discusses key statistical concepts, including sampling dangers, inequalities, and the Central Limit Theorem, with practical examples and applications.
Statistical Inference: Approximate Critical Values and Confidence Intervals
Covers the construction of confidence intervals and approximate critical values in statistical inference.
Untitled
Decision Theory: Risk and Inference
Explores decision theory, risk functions, and inference in statistical analysis.
Statistical Finite Element Method
Covers the Statistical Finite Element Method, focusing on the construction of a prior measure, dealing with model misspecification, and combining sensor data with FEM models.
Extreme Statistics: Threshold Models
Log in to Mediaspace to watch this video
Covers the theory and applications of extreme statistics, focusing on threshold models for analyzing extremes of time series.
Statistics of Multivariate Extremes: Inference and Models
Log in to Mediaspace to watch this video
Explores theory and applications of multivariate extremes, emphasizing fitting marginal and dependence models together for accurate estimation.
Multivariate Extremes: Applications and Dependence
Log in to Mediaspace to watch this video
Explores multivariate extremes, including overwhelming sea defenses and heat waves.
Extreme Value Analysis: Applications and Consequences
Log in to Mediaspace to watch this video
Explores extremal limit theorems and statistical analysis for analyzing extreme events like Venezuela rainfall and Venice data.
Extreme Value Theory: Point Processes
Log in to Mediaspace to watch this video
Covers the application of extreme value theory to point processes and the estimation of extreme events from equally-spaced time series.
Previous
Page 1 of 2
Next
