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Solving the Likelihood Equations

Published: 01 November 2005 Publication History

Abstract

Given a model in algebraic statistics and data, the likelihood function is a rational function on a projective variety. Algebraic algorithms are presented for computing all critical points of this function, with the aim of identifying the local maxima in the probability simplex. Applications include models specified by rank conditions on matrices and the Jukes---Cantor models of phylogenetics. The maximum likelihood degree of a generic complete intersection is also determined.

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  • (2020)Algebraic optimization degreeACM Communications in Computer Algebra10.1145/3427218.342722254:2(44-48)Online publication date: 29-Sep-2020
  • (2019)A New Method for Computing Elimination Ideals of Likelihood EquationsProceedings of the 2019 International Symposium on Symbolic and Algebraic Computation10.1145/3326229.3326241(339-346)Online publication date: 8-Jul-2019
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    Published In

    cover image Foundations of Computational Mathematics
    Foundations of Computational Mathematics  Volume 5, Issue 4
    November 2005
    139 pages
    ISSN:1615-3375
    EISSN:1615-3383
    Issue’s Table of Contents

    Publisher

    Springer-Verlag

    Berlin, Heidelberg

    Publication History

    Published: 01 November 2005

    Author Tags

    1. Maximum likelihood
    2. Maximum likelihood degree
    3. Phylogenetic trees
    4. Syzygies

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    • (2024)A Maximum Likelihood Estimator for Quartets under the Cavender-Farris-Neyman ModelACM Communications in Computer Algebra10.1145/3712023.371202858:2(35-38)Online publication date: 1-Jun-2024
    • (2020)Algebraic optimization degreeACM Communications in Computer Algebra10.1145/3427218.342722254:2(44-48)Online publication date: 29-Sep-2020
    • (2019)A New Method for Computing Elimination Ideals of Likelihood EquationsProceedings of the 2019 International Symposium on Symbolic and Algebraic Computation10.1145/3326229.3326241(339-346)Online publication date: 8-Jul-2019
    • (2018)Numerical Computation of Galois GroupsFoundations of Computational Mathematics10.5555/3269376.326942418:4(867-890)Online publication date: 1-Aug-2018
    • (2017)The maximum likelihood data singular locusJournal of Symbolic Computation10.1016/j.jsc.2016.08.00779:P1(99-107)Online publication date: 1-Mar-2017
    • (2017)Critical points via monodromy and local methodsJournal of Symbolic Computation10.1016/j.jsc.2016.07.01979:P3(559-574)Online publication date: 1-Mar-2017
    • (2016)The Euclidean Distance Degree of an Algebraic VarietyFoundations of Computational Mathematics10.1007/s10208-014-9240-x16:1(99-149)Online publication date: 1-Feb-2016
    • (2015)Optimizing a Parametric Linear Function over a Non-compact Real Algebraic VarietyProceedings of the 2015 ACM International Symposium on Symbolic and Algebraic Computation10.1145/2755996.2756666(205-212)Online publication date: 24-Jun-2015
    • (2015)Data-Discriminants of Likelihood EquationsProceedings of the 2015 ACM International Symposium on Symbolic and Algebraic Computation10.1145/2755996.2756649(307-314)Online publication date: 24-Jun-2015
    • (2014)Maximum likelihood for dual varietiesProceedings of the 2014 Symposium on Symbolic-Numeric Computation10.1145/2631948.2631959(43-49)Online publication date: 28-Jul-2014
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