Extended Kalman Filter

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Related lectures (30)

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Kalman Filtering: State Estimation and Prediction

Explores the Kalman filter for state estimation and prediction in a linear Gaussian setting, emphasizing the optimality of the predictor and filter.

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.

Shrinkage Estimation of Large Covariance Matrices

Explores shrinkage estimation of high-dimensional covariance matrices, comparing linear and nonlinear approaches for improved accuracy.

Structural Modelling and the Kalman Filter: Time Series

Explores structural modelling in time series and introduces the Kalman filter for prediction and estimation.

Kalman Filter: Time Series

Covers structural modeling, state space models, and the Kalman filter in time series analysis.

Principal Components: Properties & Applications

Explores principal components, covariance, correlation, choice, and applications in data analysis.

Multivariate Statistics: Introduction and Methods

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

Non-Negative Definite Matrices and Covariance Matrices

Covers non-negative definite matrices, covariance matrices, and Principal Component Analysis for optimal dimension reduction.

ARCH and GARCH Models

Explores ARCH and GARCH models, volatility clustering, time series, estimation, and filtering steps in financial and macroeconomic contexts.

Market Response Functions

Explores market response functions, flash crashes, correlation estimation, and noise filtering in finance.