In Multiple Linear Regression, we describe linear regression models with multiple independent variables but one dependent variable. We now describe Multivariate Linear Regression models, which support both multiple dependent and multiple independent variables. This enables these models, at least theoretically, to take correlations between the dependent variables into account.
Topics
- Basic Concepts
- Confidence Intervals for Coefficients
- Hypothesis Testing
- Prediction Intervals
- Bootstrapping
- Partial Least Squares Regression
Links
References
Johnson, R. A., Wichern, D. W. (2007) Applied multivariate statistical analysis. 6th Ed. Pearson
https://mathematics.foi.hr/Applied%20Multivariate%20Statistical%20Analysis%20by%20Johnson%20and%20Wichern.pdf
Rencher, A.C., Christensen, W. F. (2012) Methods of multivariate analysis (3nd Ed). Wiley