↓ Skip to main content

Optimal dichotomization of bimodal Gaussian mixtures

Overview of attention for article published in Statistical Papers, January 2024
Altmetric Badge

About this Attention Score

  • Among the highest-scoring outputs from this source (#47 of 160)
  • Above-average Attention Score compared to outputs of the same age (63rd percentile)

Mentioned by

twitter
6 X users

Readers on

mendeley
1 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Optimal dichotomization of bimodal Gaussian mixtures
Published in
Statistical Papers, January 2024
DOI 10.1007/s00362-023-01521-1
Authors

Yan-ni Jhan, Wan-cen Li, Shin-hui Ruan, Jia-jyun Sie, Iebin Lian

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 100%
Readers by discipline Count As %
Engineering 1 100%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 January 2024.
All research outputs
#14,581,171
of 25,342,911 outputs
Outputs from Statistical Papers
#47
of 160 outputs
Outputs of similar age
#105,866
of 293,209 outputs
Outputs of similar age from Statistical Papers
#2
of 2 outputs
Altmetric has tracked 25,342,911 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 160 research outputs from this source. They receive a mean Attention Score of 1.9. This one has gotten more attention than average, scoring higher than 69% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 293,209 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.