Kalman Filtering: State Estimation and Prediction

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Time-Varying Kalman Filter: Properties and Applications

Explores the time-varying Kalman filter, state estimation, challenges in conditioning on measured outputs, and the importance of affine transformations.

Multivariate Statistics: Wishart and Hotelling T²

Explores the Wishart distribution, properties of Wishart matrices, and the Hotelling T² distribution, including the two-sample Hotelling T² statistic.

Multivariable Control

Covers Gaussian random variables, affine transformations, and linear systems driven by Gaussian noise in multivariable control.

Multivariable Control: Gaussian Processes and Linear Systems

Explores Gaussian processes, linear systems, transformations, and noise properties in multivariable control applications.

Multivariate Statistics: Introduction and Methods

Introduces multivariate statistics, focusing on uncovering associations between components in data in vector form.

Maximum Likelihood Theory & Applications

Covers maximum likelihood theory, applications, and hypothesis testing principles in econometrics.

Multivariate Statistics: Normal Distribution

Covers the multivariate normal distribution, properties, and sampling methods.

Dependence in Random Vectors

Explores dependence in random vectors, covering joint density, conditional independence, covariance, and moment generating functions.

Multivariate Statistics: Normal Distribution

Introduces multivariate statistics, covering normal distribution properties and characteristic functions.

Gaussian Random Vectors

Explores Gaussian vectors, moment generating functions, independence, density functions, affine transformations, and quadratic forms.