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Advanced Regression Analysis: Course Outline

Regression is used to test the effects of n independent (predictor) variables on a single dependent (criterion) variable.

Course Outline

  • Generalized Linear Models (GLM),
  • Least Squares and Unbiased Estimation,
  • Best Linear Unbiased Estimation (BLUE),
  • Multiple Regression Analysis,
  • Hetroscedasticity,
  • Autocorrelation,
  • Multicollinearity,
  • Ridge Regression,
  • Properties of the Ridge Estimator,
  • Outlier Diagnostics,
  • Recent Developments,
  • High-Breakdown Diagnostics,
  • Motivation for Shrinkage,
  • Stein-Rule in the Regression Context,
  • Properties of the Stein-Rule Estimator and its Extensions,
  • Testing a Nonlinear Specification,
  • Measures of Nonlinearity,
  • Orthogonality,
  • Jackknifing,
  • Bootstrapping.

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