On Graphical Models and Convex Geometry.

Haim Bar, Martin T Wells

Abstract read

In one paragraph

Article in Computational statistics & data analysis, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Haim BarDepartment of Statistics, University of Connecticut, Room 315, Philip E. Austin Building, Storrs, 06269-4120, CT, USA.

Martin T WellsDepartment of Statistics and Data Science, Cornell University, 1190 Comstock Hall, Ithaca, 14853, NY, USA.

Funding

Learning Dynamics of Biological Processes from Time Course Omics DatasetsR01GM135926 · NIGMS · CORNELL UNIVERSITY · PI BASU, SUMANTA · 2019 to 2022

$1.4M

NIGMS NIH HHS R01 GM135926

6 · The paper itself

Abstract

A mixture-model of beta distributions framework is introduced to identify significant correlations among

Indexed as

Convex geometryCorrelation matrix estimationExpectation Maximization (EM) algorithmGraphical modelsGrassmann manifoldHigh-dimensional inferenceNetwork modelsPhase transitionQuasi-orthogonalityTwo-group model

Identifiers

PMID37396752

DOI10.1016/j.csda.2023.107800

PMCPMC10310290

What OpenQuestion holds

Textmetadata

LicenceTDM

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.