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 variables as well as multiple independent variables. This enables, at least theoretically, for these models to take into account correlations between the dependent variables.
Under construction
Topics
- Basic Concepts
- Hypothesis Testing
- Confidence Intervals for coefficients
- Prediction Intervals
- Bootstrapping
- Partial Least Squares Regression
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