Tensors in algebraic statistics

Fuente: arXiv
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Bibliographic Details
Main Authors: Casanellas, Marta, Sierra, Luis, Zwiernik, Piotr
Format: Preprint
Published: 2024
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author Casanellas, Marta
Sierra, Luis
Zwiernik, Piotr
author_facet Casanellas, Marta
Sierra, Luis
Zwiernik, Piotr
contents Tensors are ubiquitous in statistics and data analysis. The central object that links data science to tensor theory and algebra is that of a model with latent variables. We provide an overview of tensor theory, with a particular emphasis on its applications in algebraic statistics. This high-level treatment is supported by numerous examples to illustrate key concepts. Additionally, an extensive literature review is included to guide readers toward more detailed studies on the subject.
format Preprint
id arxiv_https___arxiv_org_abs_2411_14080
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Tensors in algebraic statistics
Casanellas, Marta
Sierra, Luis
Zwiernik, Piotr
Statistics Theory
Algebraic Geometry
History and Overview
62R01, 15A69
Tensors are ubiquitous in statistics and data analysis. The central object that links data science to tensor theory and algebra is that of a model with latent variables. We provide an overview of tensor theory, with a particular emphasis on its applications in algebraic statistics. This high-level treatment is supported by numerous examples to illustrate key concepts. Additionally, an extensive literature review is included to guide readers toward more detailed studies on the subject.
title Tensors in algebraic statistics
topic Statistics Theory
Algebraic Geometry
History and Overview
62R01, 15A69
url https://arxiv.org/abs/2411.14080