Bayesian Parameter Estimation

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Explores Gaussian classifiers, texture classification, parameter estimation, supervised learning, and deep neural networks in image processing.

Covers market-based instruments for emission reductions and their efficiency in minimizing costs across different sources of emissions.

Explores binary response interpretation, link functions, logistic regression, and model selection using deviances and information criteria.

Covers Factor Models, including PCA, asset pricing, factor investing, GMM, and Fama-McBeth estimation.

Covers linear regression basics, closed-form solutions, singularity, and regularizing techniques.

Covers the concept of geometric ergodicity in the context of convergence diagnostics for Markov chains.

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