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Error and anomaly detection for intra-participant time-series data
Identification of errors or anomalous values, collectively considered outliers, assists in exploring data or through removing outliers improves statistical analysis. In biomechanics, outlier detection methods have explored the ‘shape’ of the entire cycles, although exploring fewer points using a ‘mo...
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| Pubblicato in: | Int Biomech |
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| Autori principali: | , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Taylor & Francis
2017
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7857460/ https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/23335432.2017.1348913 |
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