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Regularized nonlinear regression with dependent errors and its application to a biomechanical model

Overview of attention for article published in Annals of the Institute of Statistical Mathematics, February 2024
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2 Mendeley
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Title
Regularized nonlinear regression with dependent errors and its application to a biomechanical model
Published in
Annals of the Institute of Statistical Mathematics, February 2024
DOI 10.1007/s10463-023-00895-1
Authors

Hojun You, Kyubaek Yoon, Wei-Ying Wu, Jongeun Choi, Chae Young Lim

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 50%
Unknown 1 50%
Readers by discipline Count As %
Computer Science 1 50%
Engineering 1 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 26 October 2022.
All research outputs
#22,777,327
of 25,394,764 outputs
Outputs from Annals of the Institute of Statistical Mathematics
#112
of 126 outputs
Outputs of similar age
#184,938
of 228,109 outputs
Outputs of similar age from Annals of the Institute of Statistical Mathematics
#1
of 1 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 126 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 228,109 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them