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Efficient and fast spline-backfitted kernel smoothing of additive models

Overview of attention for article published in Annals of the Institute of Statistical Mathematics, October 2007
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About this Attention Score

  • Among the highest-scoring outputs from this source (#23 of 110)

Mentioned by

policy
1 policy source

Citations

dimensions_citation
45 Dimensions

Readers on

mendeley
13 Mendeley
Title
Efficient and fast spline-backfitted kernel smoothing of additive models
Published in
Annals of the Institute of Statistical Mathematics, October 2007
DOI 10.1007/s10463-007-0157-x
Authors

Jing Wang, Lijian Yang

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Other 2 15%
Researcher 2 15%
Professor > Associate Professor 2 15%
Student > Master 1 8%
Professor 1 8%
Other 2 15%
Unknown 3 23%
Readers by discipline Count As %
Mathematics 2 15%
Engineering 2 15%
Economics, Econometrics and Finance 2 15%
Computer Science 1 8%
Decision Sciences 1 8%
Other 1 8%
Unknown 4 31%
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 02 July 2015.
All research outputs
#7,485,442
of 22,879,161 outputs
Outputs from Annals of the Institute of Statistical Mathematics
#23
of 110 outputs
Outputs of similar age
#25,327
of 71,950 outputs
Outputs of similar age from Annals of the Institute of Statistical Mathematics
#2
of 3 outputs
Altmetric has tracked 22,879,161 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 110 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 47th percentile – i.e., 47% 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 71,950 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.