In some overparameterized linear models it can be difficult to determine which parametric functions are estimable. Students in linear models courses and data analysts usually rely upon intuition and/or trial and error methods to determine estimability. We suggest reducing the design matrix to row echelon form as a means of finding the structure of all estimable functions. We illustrate the procedure with two examples.
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- General Mathematics
- Statistics, Probability and Uncertainty