Outline of regression analysis
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[]
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- Least squares
- Linear least squares (mathematics)
- Non-linear least squares
- Least absolute deviations
- Curve fitting
- Smoothing
- Cross-sectional study
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- Conditional expectation
- Correlation
- Correlation coefficient
- Mean square error
- Residual sum of squares
- Explained sum of squares
- Total sum of squares
Visualization[]
- Scatterplot
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
- Multinomial logit
- Ordered logit
- 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 process
- Cross-sectional data
- Time series
Methods for dependent data[]
- Mixed model
- Random effects model
- Hierarchical linear models
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
Categories:
- Outlines of mathematics and logic
- Wikipedia outlines
- Regression analysis
- Statistics-related lists