Evidence map›Paper›PMID 27617051›Full record

ArticleElectronic journal of statistics

Statistical properties of convex clustering.

Kean Ming Tan, Daniela Witten

Abstract read
In one paragraph

Article in Electronic journal of statistics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Simple and Scalable Algorithms for Cluster-Aware Precision Medicine.Proceedings of machine learning research · 2024
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Provable Convex Co-clustering of Tensors.Journal of machine learning research : JMLR · 2020
    Article
  8. Dynamic Visualization and Fast Computation for Convex Clustering via Algorithmic Regularization.Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2020
    Article
  9. Article
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.

Kean Ming TanDepartment of Biostatistics, University of Washington, Seattle, WA 98195, U.S.A., keanming@uw.edu.
Daniela WittenDepartments of Statistics and Biostatistics, University of Washington, Seattle, WA 98195, U.S.A., dwitten@uw.edu.

Funding

High-dimensional unsupervised learning, with applications to genomicsDP5OD009145 · OD · UNIVERSITY OF WASHINGTON · PI WITTEN, DANIELA · 2011 to 2015
$1.8M
NIH HHS DP5 OD009145
6 · The paper itself

Abstract

In this manuscript, we study the statistical properties of

Indexed as

Degrees of freedomfusion penaltyhierarchical clusteringk-meansprediction errorsingle linkage

Identifiers

PMID27617051
PMCPMC5014420

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.