Estimation & Bayesian Inference

Related lectures (51)

Explores the average time for a Brownian motion to leave an interval and the maximum distribution.

Covers amplitude shift keying and various data analysis techniques using Jupyter Notebooks.

Explores the joint equidistribution of CM points and their properties in ergodic theory and homogeneous dynamics.

Covers the definitions and properties of queueing systems, focusing on the M/M/s/K model.

Covers Lipschitz maps, compact domains, changing variables, counting problems, and probability of ideals.

Covers the basic concepts of probability, including sample space, events, intersections, and independence.

Explores scoring, strategies, and guidelines for multiple-choice exams.

Explains message passing in networks, emphasizing probabilities and average edges between communities.

Discusses Boltzmann, Bose-Einstein, and Fermi-Dirac statistics in statistical mechanics.

Explores decision rules based on likelihood ratios and the maximum a posteriori decision.

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

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