Evidence map›Paper›PMID 38590837›Full record

ArticleJournal of the American Statistical Association2024

An Empirical Bayes Approach to Shrinkage Estimation on the Manifold of Symmetric Positive-Definite Matrices.

Chun-Hao Yang, Hani Doss, Baba C Vemuri

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the American Statistical Association, 2024. 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

3 authors.

Chun-Hao YangInstitute of Applied Mathematical Sciences, National Taiwan University, Taipei, Taiwan.ORCID 0000-0002-2522-5957
Hani DossDepartment of Statistics, University of Florida, Gainesville, FL.
Baba C VemuriDepartment of CISE, University of Florida, Gainesville, FL.ORCID 0000-0002-1400-5844

Funding

Higher Order Convolutional Neural Network for Classification of Lewy-body Diseases and Alzheimers DiseaseR01NS121099 · NINDS · UNIVERSITY OF FLORIDA · PI VEMURI, BABA C · 2024 to 2025
$735k
Higher Order Convolutional Neural Network for Classification of Lewy-body Diseases and Alzheimers DiseaseRF1NS121099 · NINDS · UNIVERSITY OF FLORIDA · PI VEMURI, BABA C · 2022 to 2022
$702k
NINDS NIH HHS R01 NS121099NINDS NIH HHS RF1 NS121099
6 · The paper itself

Abstract

The James-Stein estimator is an estimator of the multivariate normal mean and dominates the maximum likelihood estimator (MLE) under squared error loss. The original work inspired great interest in developing shrinkage estimators for a variety of problems. Nonetheless, research on shrinkage estimation for manifold-valued data is scarce. In this article, we propose shrinkage estimators for the parameters of the Log-Normal distribution defined on the manifold of

Indexed as

Fréchet mean;Stein’sTweedie’s estimatorunbiased risk estimate;

Identifiers

PMID38590837
PMCPMC11000275

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Registered trials

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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.