In statistics, linear regression is a statistical model which estimates the linear relationship between a scalar response and one or more explanatory...

In statistics, simple linear regression (SLR) is a linear regression model with a single explanatory variable. That is, it concerns two-dimensional sample...

Bayesian linear regression is a type of conditional modeling in which the mean of one variable is described by a linear combination of other variables...

MANCOVA, ordinary linear regression, t-test and F-test. The general linear model is a generalization of multiple linear regression to the case of more...

an event as a linear combination of one or more independent variables. In regression analysis, logistic regression (or logit regression) is estimating...

non-linear models (e.g., nonparametric regression). Regression analysis is primarily used for two conceptually distinct purposes. First, regression analysis...

in linear regression, including variants for ordinary (unweighted), weighted, and generalized (correlated) residuals. Numerical methods for linear least...

especially in the case of a simple linear regression, in which there is a single regressor on the right side of the regression equation. The OLS estimator is...

In statistics, nonlinear regression is a form of regression analysis in which observational data are modeled by a function which is a nonlinear combination...

regression estimates the conditional median (or other quantiles) of the response variable. Quantile regression is an extension of linear regression used...