Naive Bayes: Gaussian Discriminant Analysis

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

Covers the likelihood ratio test for detection and estimation in statistical analysis.

Explores maximum likelihood inference, comparing models based on likelihood ratios and demonstrating with a coin example.

Introduces Maximum Likelihood Estimation in econometrics, covering principles, properties, applications, and specification tests.

Discusses estimation methods in probability and statistics, focusing on maximum likelihood estimation and confidence intervals.

Explores the Cramér-Rao bound, hypothesis testing, and optimality in statistical theory.

Explores maximum likelihood inference, model selection, and comparing models using likelihood ratios.

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

Covers the concepts of spin glasses and Bayesian estimation, focusing on observing and inferring information from a system closely.

Covers bias, variance, mean squared error, consistency, and maximum likelihood estimation in the Poisson model.