Template:Least squares and regression analysis

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v • d • e Least squares and regression analysis Least squares Linear least squares - Non-linear least squares - Partial least squares -Total least squares - Gauss–Newton algorithm - Levenberg–Marquardt algorithm Regression analysis Linear regression - Nonlinear regression - Linear model - Generalized linear model - Robust regression - Least-squares estimation of linear regression coefficients- Mean and predicted response - Poisson regression - Logistic regression - Isotonic regression - Ridge regression - Segmented regression - Nonparametric regression - Regression discontinuity Statistics Gauss–Markov theorem - Errors and residuals in statistics - Goodness of fit - Studentized residual - Mean squared error - R-factor (crystallography) - Mean squared prediction error - Minimum mean-square error - Root mean square deviation - Squared deviations - M-estimator Applications Curve fitting - Calibration curve - Numerical smoothing and differentiation - Least mean squares filter - Recursive least squares filter - Moving least squares - BHHH algorithm