Regression Reloaded: Synthetic Dataset Construction and Parameter Estimation

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Linear Regression

Covers linear regression for estimating train speed using least squares and regularization.

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Explores linear regression analysis of ozone data using statistical models.

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Explores supervised learning in financial econometrics, covering linear regression, model fitting, potential problems, basis functions, subset selection, cross-validation, regularization, and random forests.

Linear Regression: Concepts and Applications

Introduces linear regression concepts, from X-bands creation to slope estimator properties and tests.

Theoretical Properties of Linear Regression Estimator

Covers the theoretical properties of the linear regression estimator, including the hat matrix and the Gauss-Markov theorem.

Linear and Weighted Regression: Optimal Parameters and Local Solutions

Covers linear and weighted regression, optimal parameters, local solutions, SVR application, and regression techniques' sensitivity.

Linear and Ridge Regression

Covers linear and ridge regression, overfitting, hyperparameters, and test sets.

Linear Regression: Maximum Likelihood Estimation

Explores linear regression with a focus on maximum likelihood estimation.

Linear Regression: Fundamentals and Applications

Explores linear regression fundamentals, model training, evaluation, and performance metrics, emphasizing the importance of R², MSE, and MAE.