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Particle filters for mixture models with an unknown number of components

Overview of attention for article published in Statistics and Computing, January 2004
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Mentioned by

patent
2 patents

Citations

dimensions_citation
84 Dimensions

Readers on

mendeley
117 Mendeley
citeulike
1 CiteULike
Title
Particle filters for mixture models with an unknown number of components
Published in
Statistics and Computing, January 2004
DOI 10.1023/b:stco.0000009418.04621.cd
Authors

Paul Fearnhead

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 117 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 6%
United Kingdom 3 3%
France 2 2%
Switzerland 1 <1%
Hungary 1 <1%
Spain 1 <1%
China 1 <1%
Unknown 101 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 48 41%
Researcher 26 22%
Student > Master 11 9%
Professor > Associate Professor 9 8%
Student > Doctoral Student 4 3%
Other 12 10%
Unknown 7 6%
Readers by discipline Count As %
Computer Science 27 23%
Mathematics 26 22%
Engineering 19 16%
Psychology 9 8%
Agricultural and Biological Sciences 5 4%
Other 23 20%
Unknown 8 7%
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 27 December 2016.
All research outputs
#8,535,684
of 25,374,917 outputs
Outputs from Statistics and Computing
#188
of 608 outputs
Outputs of similar age
#36,568
of 143,821 outputs
Outputs of similar age from Statistics and Computing
#1
of 2 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 608 research outputs from this source. They receive a mean Attention Score of 4.0. This one has gotten more attention than average, scoring higher than 57% 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 143,821 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
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. This one has scored higher than all of them