Concept

Outline of regression analysis

Résumé
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). Regression analysis Linear regression Least squares Linear least squares (mathematics) Non-linear least squares Least absolute deviations Curve fitting Smoothing Cross-sectional study Conditional expectation Correlation Correlation coefficient Mean square error Residual sum of squares Explained sum of squares Total sum of squares Scatterplot 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 Logistic regression Multinomial logit Ordered logit Probit model Multinomial probit Ordered probit Poisson regression Maximum likelihood Cochrane–Orcutt estimation Numerical methods for linear least squares F-test t-test Lack-of-fit sum of squares Confidence band Coefficient of determination Multiple correlation Scheffé's method Autocorrelation Cointegration Multicollinearity Homoscedasticity and heteroscedasticity Lack of fit Non-normality of errors Outliers Regression model validation Studentized residual Cook's distance Variance inflation factor DFFITS Partial residual plot Partial regression plot Leverage Durbin–Watson statistic Condition number Model selection Mallows's Cp Akaike information criterion Bayesian information criterion Hannan–Quinn information criterion Cross validation Robust regression 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 Mixed model Random effects model Hierarchical linear models Nonparametric regression Isotonic regression Semiparametric regression Local regression Total least squares regression Deming regression Errors-in-varia
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