4.4 Quadratic forms and a global constrained formula
If and , then . Consequently is positive definite exactly when every eigenvalue is positive. Negative eigenvalues produce negative directions, and zero eigenvalues produce nontrivial flat directions. This general-size criterion extends Chapter 2's two-variable determinant test.
Worked example 2: diagonalize a quadratic criterion. For , eigenvectors and have eigenvalues six and one. Dividing by gives an orthogonal matrix . In its coordinates,
proving positive definiteness and exposing unequal curvature in perpendicular directions.
For a symmetric positive-definite and constraint , multiplier equations yield
The denominator is positive because the inverse is positive definite. To prove global optimality, write another feasible vector as with . The cross term vanishes since is a multiple of , leaving for . Nonnegative-weight constraints, if present, still need checking separately; the equality-only formula can produce negative components in other examples.
Exercises
P06. Verify the eigenvectors and diagonal quadratic expression for in Worked example 2.
P09. Use the equality-constrained formula for and calculate the minimizing two weights and value. Verify directly by substituting .
Full solutions
P06. and . The normalized vectors are orthogonal, so and the quadratic becomes .
P09. has sum , so weights are and value . Directly, , proving the same unique global minimum.