Algebraic Methods for Polynomial Statistical Models

Authors:
I. H. Dinwoodie
Affiliations:
Department of Mathematics, Tulane University, New Orleans, LA 70118, USA
Venue:
Statistics and Computing
Year:
2002

Citing 2
Cited 0

Ideals, Varieties, and Algorithms: An Introduction to Computational Algebraic Geometry and Commutative Algebra, 3/e (Undergraduate Texts in Mathematics)

Ideals, Varieties, and Algorithms: An Introduction to Computational Algebraic Geometry and Commutative Algebra, 3/e (Undergraduate Texts in Mathematics)
Multicast-based inference of network-internal loss characteristics

IEEE Transactions on Information Theory

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Abstract

We describe applications of computational algebra to statistical problems of parameter identifiability, sufficiency, and estimation. The methods work for a family of statistical models that includes Poisson and binomial examples in network tomography.