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Modeling a nonlinear process using the exponential autoregressive time series model

Overview of attention for article published in Nonlinear Dynamics, December 2018
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

peer_reviews
1 peer review site

Citations

dimensions_citation
39 Dimensions

Readers on

mendeley
11 Mendeley
Title
Modeling a nonlinear process using the exponential autoregressive time series model
Published in
Nonlinear Dynamics, December 2018
DOI 10.1007/s11071-018-4677-0
Authors

Huan Xu, Feng Ding, Erfu Yang

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 18%
Other 1 9%
Professor 1 9%
Student > Doctoral Student 1 9%
Student > Master 1 9%
Other 1 9%
Unknown 4 36%
Readers by discipline Count As %
Engineering 3 27%
Environmental Science 1 9%
Business, Management and Accounting 1 9%
Mathematics 1 9%
Unknown 5 45%
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 07 February 2019.
All research outputs
#15,560,927
of 23,128,387 outputs
Outputs from Nonlinear Dynamics
#247
of 552 outputs
Outputs of similar age
#264,678
of 437,113 outputs
Outputs of similar age from Nonlinear Dynamics
#4
of 7 outputs
Altmetric has tracked 23,128,387 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 552 research outputs from this source. They receive a mean Attention Score of 2.2. This one is in the 37th percentile – i.e., 37% 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 437,113 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.