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- W57482455 abstract "A strong link between information geometry and algebraic statistics is made by investigating statistical manifolds which are algebraic varieties. In particular it it shown how first and second order efficiency estimators can be constructed, such as bias corrected Maximum Likelihood Estimators and more general estimators, but for which the estimating equations are purely algebraic. In addition it is shown how Grobner basis technology, which is at the heart of algebraic statistics, can be used to reduce the degrees of the terms in the estimating equations. This points the way to the feasible use, to find the estimators, of special methods for solving polynomial equations, such are homotopy methods." @default.
- W57482455 created "2016-06-24" @default.
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- W57482455 date "2013-01-01" @default.
- W57482455 modified "2023-10-18" @default.
- W57482455 title "Asymptotically Efficient Estimators for Algebraic Statistical Manifolds" @default.
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- W57482455 doi "https://doi.org/10.1007/978-3-642-40020-9_80" @default.
- W57482455 hasPublicationYear "2013" @default.
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