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Record W4391349967 · doi:10.1111/sjos.12707

On the expectations of equivariant matrix‐valued functions of Wishart and inverse Wishart matrices

2024· article· en· W4391349967 on OpenAlexaff
Grant Hillier, Raymond Kan

Bibliographic record

VenueScandinavian Journal of Statistics · 2024
Typearticle
Languageen
FieldMathematics
TopicRandom Matrices and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsWishart distributionMathematicsEquivariant mapInverse-Wishart distributionMatrix (chemical analysis)Pure mathematicsInverseAction (physics)Group (periodic table)Symmetric matrixCombinatoricsAlgebra over a fieldEigenvalues and eigenvectorsStatisticsMultivariate statistics

Abstract

fetched live from OpenAlex

Abstract Many matrix‐valued functions of an Wishart matrix , , say, are homogeneous of degree in , and are equivariant under the conjugate action of the orthogonal group , that is, , . It is easy to see that the expectation of such a function is itself homogeneous of degree in , the covariance matrix, and are also equivariant under the action of on . The space of such homogeneous, equivariant, matrix‐valued functions is spanned by elements of the type , where and, for each , varies over the partitions of , and denotes the power‐sum symmetric function indexed by . In the analogous case where is replaced by , these elements are replaced by . In this paper, we derive recurrence relations and analytical expressions for the expectations of such functions. Our results provide highly efficient methods for the computation of all such moments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.038
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.038
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.004
Scholarly communication0.0020.005
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.324
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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