Outline of regression analysis
The following outline is provided as an overview of and topical guide to regression analysis, which involves any of several statistical techniques for learning about the relationship between one or more dependent variables (Y) and one or more independent variables (X).
Overview articles
Non-statistical articles related to regression
- Least squares
- Linear least squares (mathematics)
- Non-linear least squares
- Least absolute deviations
- Curve fitting
- Smoothing
- Cross-sectional study
Basic statistical ideas related to regression
- Conditional expectation
- Correlation
- Correlation coefficient
- Mean square error
- Residual sum of squares
- Explained sum of squares
- Total sum of squares
Visualization
Linear regression based on least squares
- General linear model
- Ordinary least squares
- Generalized least squares
- Simple linear regression
- Trend estimation
- Ridge regression
- Polynomial regression
- Segmented regression
- Nonlinear regression
Generalized linear models
- Generalized linear models
- Logistic regression
- Probit model
- Poisson regression
- Maximum likelihood
- Cochrane–Orcutt estimation
Computation
Inference for regression models
- F-test
- t-test
- Lack-of-fit sum of squares
- Confidence band
- Coefficient of determination
- Multiple correlation
- Scheffé's method
Challenges to regression modeling
- Autocorrelation
- Cointegration
- Multicollinearity
- Homoscedasticity and heteroscedasticity
- Lack of fit
- Non-normality of errors
- Outliers
Diagnostics for regression models
- Regression model validation
- Studentized residual
- Cook's distance
- Variance inflation factor
- DFFITS
- Partial residual plot
- Partial regression plot
- Leverage
- Durbin–Watson statistic
- Condition number
Formal aids to model selection
- Model selection
- Mallows's Cp
- Akaike information criterion
- Bayesian information criterion
- Hannan–Quinn information criterion
- Cross validation
Robust regression
Terminology
- Linear model — relates to meaning of "linear"
- Dependent and independent variables
- Errors and residuals in statistics
- Hat matrix
- Trend stationary
- Cross-sectional data
- Time series
Methods for dependent data
Nonparametric regression
Semiparametric regression
Other forms of regression
- 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
See also
- Prediction
- Design of experiments
- Data transformation
- Box–Cox transformation
- Machine learning
- Analysis of variance
- Causal inference
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