The following outline is provided as an overview of and topical guide to regression analysis:
Regression analysis – use of statistical techniques for learning about the relationship between one or more dependent variables (Y) and one or more independent variables (X).
Overview articles
editNon-statistical articles related to regression
editBasic statistical ideas related to regression
editVisualization
editLinear regression based on least squares
editGeneralized linear models
editComputation
editInference for regression models
editChallenges to regression modeling
editDiagnostics for regression models
editFormal aids to model selection
editRobust regression
editTerminology
edit- Linear model — relates to meaning of "linear"
- Dependent and independent variables
- Errors and residuals in statistics
- Hat matrix
- Trend-stationary process
- Cross-sectional data
- Time series
Methods for dependent data
editNonparametric regression
editSemiparametric regression
editOther forms of regression
edit- Total least squares regression
- Deming regression
- Errors-in-variables model
- Instrumental variables regression
- Quantile regression
- Generalized additive model
- Autoregressive model
- Moving average model
- Autoregressive moving average model
- Autoregressive integrated moving average
- Autoregressive conditional heteroskedasticity