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Forecasting performance of machine learning, time series, and hybrid methods for low‐ and high‐frequency time series

Overview of attention for article published in Statistica Neerlandica, November 2023
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  • Above-average Attention Score compared to outputs of the same age (59th percentile)

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Title
Forecasting performance of machine learning, time series, and hybrid methods for low‐ and high‐frequency time series
Published in
Statistica Neerlandica, November 2023
DOI 10.1111/stan.12326
Authors

Ozancan Ozdemir, Ceylan Yozgatligil

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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 03 October 2023.
All research outputs
#14,934,810
of 25,611,630 outputs
Outputs from Statistica Neerlandica
#78
of 160 outputs
Outputs of similar age
#142,714
of 362,244 outputs
Outputs of similar age from Statistica Neerlandica
#1
of 1 outputs
Altmetric has tracked 25,611,630 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 160 research outputs from this source. They receive a mean Attention Score of 2.7. This one has gotten more attention than average, scoring higher than 51% 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 362,244 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.
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