Linear regression
General linear models

The general linear model considers the situation when the response variable is not a scalar (for each observation) but a vector, y. Conditional linearity of E (y ∣ x i) = x i T B {\displaystyle E(\mathbf {y} \mid \mathbf {x} _{i})=\mathbf {x} _{i}^{\mathsf {T}}B} is still assumed, with a matrix B replacing the vector β of the classical linear regression model. Multivariate analogues of ordinary least squares (OLS) and generalized least squares (GLS) have been developed. "General linear models" are also called "multivariate linear models". These are not the same as multivariable linear models (also called "multiple linear models").
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