general linear model

The general linear model (GLM) is a statistical linear model. It may be written as where Y is a matrix with series of multivariate measurements, X is a matrix that might be a design matrix, B is a matrix containing parameters that are usually to be estimated and U is a matrix containing errors or noise. The residual is usually assumed to follow a multivariate normal distribution. If the residual is not a multivariate normal distribution, generalized linear models may be used to relax assumptions about Y and U.
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The general linear model is a generalization of the linear regression model, such that effects can be tested (1) for categorical predictor variables , as well as for effects for continuous predictor variables and (2) in designs with multiple dependent variables as well as in designs with a single dependent variable.
For an overview of the general linear model see the General Linear Models chapter.