Pith. sign in

REVIEW

Tensors in algebraic statistics

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2411.14080 v1 pith:GC343GUS submitted 2024-11-21 math.ST math.AGmath.HOstat.TH

classification math.STmath.AGmath.HOstat.TH
keywords statisticsalgebraicdatatensortensorstheoryadditionallyalgebra
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

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.

Discussion (0). Sign in to comment.

Pith tools