Multivariate Leimkuhler Curve: Properties and Applications to Analysis of Bibliometric Data
Sankhya A, ISSN: 0976-8378, Vol: 86, Issue: 2, Page: 999-1024
2024
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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Article Description
The Leimkuhler curve has established itself as an efficient tool in the analysis and comparison of concentration of bibliometric measures of productivity from different sources. Inspite of a considerable volume of literature emerging on multivariate analysis of informetric data, a multivariate version of the Leimkuhler curve does not appear to have been considered so far. In the present work we propose a multivariate Leimkuhler curve and study some of its properties. The use of our results is illustrated by analyzing multivariate informetric data.
Bibliographic Details
Springer Science and Business Media LLC
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