Category
Regression analysis
Related lectures (969)
Linear Regression: Estimation and Inference
Explores linear regression estimation, linearity assumptions, and statistical tests in the context of model comparison.
Supervised Learning in Financial Econometrics
Explores supervised learning in financial econometrics, covering linear regression, model fitting, potential problems, basis functions, subset selection, cross-validation, regularization, and random forests.
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 Regression and Logistic Regression
Covers linear and logistic regression for regression and classification tasks, focusing on loss functions and model training.
Linear Regression: Statistical Inference and Regularization
Covers the probabilistic model for linear regression and the importance of regularization techniques.
Regression Analysis: Disentangling Data
Covers regression analysis for disentangling data using linear regression modeling, transformations, interpretations of coefficients, and generalized linear models.
Regression Diagnostics
Covers regression diagnostics for linear models, emphasizing the importance of checking assumptions and identifying outliers and influential observations.
Heteroskedasticity: Ch. 4a
Explores heteroskedasticity in econometrics, discussing its impact on standard errors, alternative estimators, testing methods, and implications for hypothesis testing.
Geometry and Least Squares
Discusses the geometry of least squares, exploring row and column perspectives, hyperplanes, projections, residuals, and unique vectors.
Ordinary Least Squares Regression Analysis
Covers Ordinary Least Squares Regression analysis and regression model restrictions.