Maximum Likelihood

In Chapter 2, we discussed the problem of minimizing the Euclidean distance from a data point u to a model X in \(\mathbb{R}^{n}\) that is described by polynomial equations. In Chapter 5, we studied the analogous problem in the setting of algebraic statistics [167], where the model X represents a family of probability distributions, and we used the Wasserstein metric to measure the distance from u to X. Finally, in Chapter 9, we considered the distance from a polynomial system u to the discriminant in the context of numerical analysis.