Maximum Likelihood Estimation for Nets of Conics

11/17/2020
by   Stefan Dye, et al.
0

We study the problem of maximum likelihood estimation for 3-dimensional linear spaces of 3× 3 symmetric matrices from the point of view of algebraic statistics where we view these nets of conics as linear concentration or linear covariance models of Gaussian distributions on ℝ^3. In particular, we study the reciprocal surfaces of nets of conics which are rational surfaces in ℙ^5. We show that the reciprocal surfaces are projections from the Veronese surface and determine their intersection with the polar nets. This geometry explains the maximum likelihood degrees of these linear models. We compute the reciprocal maximum likelihood degrees. This work is based on Wall's classification of nets of conics from 1977.

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