Regression analysis is the statistical processes for estimating the relationships between a dependent variable (response, outcome) and one or more independent variables (predictors, covariates, explanatory variables, features). #### Models - Linear Regression - Simple Regression - Polynomial Regression - General Linear Model - Generalized Linear Model - Vector Generalized Model - Discrete Choice - Binomial Regression - Binary Regression - Logistic Regression - Multinomial Logistic Regression - Mixed Logit - Probit - Multinomial Probit - Ordered Logit - Ordered Probit - Poisson Multilevel Model - Fixed Effects - Random Effects - Linear Mixed Effects Model - Nonlinear Mixed Effects Model - Non-Linear Regression - Non-Parametric Regression - Semi-Parametric Regression - Robust Regression - Quantile Regression - Isotonic Regression #### Estimation - Least Squares Estimation - Linear Least Squares Estimation - Non-Linear Least Squares Estimation - Ordinary Least Squares Estimation - Weighted Least Squares Estimation
Back to top