Multivariate t-distribution

Related lectures (31)

Page 3 of 4

Covers distributions and techniques in Quantitative Risk Management for financial modeling.

Explores maximum likelihood estimation and multivariate hypothesis testing, including challenges and strategies for testing multiple hypotheses.

Covers the fundamentals of probability theory, including notations for joint and conditional distributions.

Explores covariance, statistical dependence, education-fertility relationship, hypothesis testing, and comparison statistics for continuous outcomes.

Covers the modeling of insurance risk, discussing joint distributions and the impact of accidents.

Explores random walks on discrete spaces and their properties, including multivariate random variables and Poisson distributions.

Explores the application of linear algebra in data science, covering variance reduction, model distribution theory, and maximum likelihood estimates.

Covers the statistical consequences of clustering and the complexities of return level estimation in extreme events.

Explores convergence in probability, concentration inequalities, laws of large numbers, and properties of distributions.

Explores the technical derivation and properties of Multivariate Extreme Value models.