The multivariate linear regression model is an important tool for investigating relationships
between several response variables and several predictor variables. The primary interest is
in inference about the unknown regression coefficient matrix. We propose multivariate
bootstrap techniques as a means for making inferences about the unknown regression
coefficient matrix. These bootstrapping techniques are extensions of those developed in
Freedman (1981), which are only appropriate for univariate responses. Extensions to the …