Toric invariant theory for maximum likelihood estimation in log-linear models
| Autor: | Carlos Améndola, Kathlén Kohn, Philipp Reichenbach, Anna Seigal |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
010102 general mathematics
14L24 14P05 20G45 62F10 62H22 62R01 Pharmaceutical Science Mathematics - Statistics Theory Statistics Theory (math.ST) 16. Peace & justice 01 natural sciences 010104 statistics & probability Mathematics - Algebraic Geometry Complementary and alternative medicine FOS: Mathematics Pharmacology (medical) 0101 mathematics Algebraic Geometry (math.AG) |
| Popis: | We establish connections between invariant theory and maximum likelihood estimation for discrete statistical models. We show that norm minimization over a torus orbit is equivalent to maximum likelihood estimation in log-linear models. We use notions of stability under a torus action to characterize the existence of the maximum likelihood estimate, and discuss connections to scaling algorithms. This is a companion paper to arXiv:2003.13662. v2: referee comments worked in, added appendices A and B |
| Databáze: | OpenAIRE |
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