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Semiparametric estimation of mean and variance functions for non-Gaussian data

Overview of attention for article published in Computational Statistics, November 2006
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About this Attention Score

  • Among the highest-scoring outputs from this source (#49 of 165)

Mentioned by

wikipedia
1 Wikipedia page

Citations

dimensions_citation
19 Dimensions

Readers on

mendeley
6 Mendeley
Title
Semiparametric estimation of mean and variance functions for non-Gaussian data
Published in
Computational Statistics, November 2006
DOI 10.1007/s00180-006-0017-9
Authors

David Nott

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 17%
Unknown 5 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 50%
Researcher 2 33%
Unknown 1 17%
Readers by discipline Count As %
Mathematics 3 50%
Agricultural and Biological Sciences 2 33%
Unknown 1 17%
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 17 January 2016.
All research outputs
#7,471,048
of 22,840,638 outputs
Outputs from Computational Statistics
#49
of 165 outputs
Outputs of similar age
#24,240
of 69,715 outputs
Outputs of similar age from Computational Statistics
#1
of 1 outputs
Altmetric has tracked 22,840,638 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 165 research outputs from this source. They receive a mean Attention Score of 3.3. This one has gotten more attention than average, scoring higher than 54% 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 69,715 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% 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