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A Tool to Explore Discrete-Time Data: The Time Series Response Analyser.
International Journal of Sport Nutrition and Exercise Metabolism ( IF 2.5 ) Pub Date : 2020-07-29 , DOI: 10.1123/ijsnem.2020-0150
Benjamin J Narang 1 , Greg Atkinson 2 , Javier T Gonzalez 1 , James A Betts 1
Affiliation  

The analysis of time series data is common in nutrition and metabolism research for quantifying the physiological responses to various stimuli. The reduction of many data from a time series into a summary statistic(s) can help quantify and communicate the overall response in a more straightforward way and in line with a specific hypothesis. Nevertheless, many summary statistics have been selected by various researchers, and some approaches are still complex. The time-intensive nature of such calculations can be a burden for especially large data sets and may, therefore, introduce computational errors, which are difficult to recognize and correct. In this short commentary, the authors introduce a newly developed tool that automates many of the processes commonly used by researchers for discrete time series analysis, with particular emphasis on how the tool may be implemented within nutrition and exercise science research.



中文翻译:

探索离散时间数据的工具:时间序列响应分析器。

时间序列数据的分析在营养和代谢研究中很常见,用于量化对各种刺激的生理反应。将时间序列中的许多数据减少为汇总统计数据有助于以更直接的方式量化和传达整体响应,并符合特定假设。尽管如此,各种研究人员已经选择了许多汇总统计数据,有些方法仍然很复杂。这种计算的时间密集型特性对于特别大的数据集可能是一种负担,因此可能会引入难以识别和纠正的计算错误。在这篇简短的评论中,作者介绍了一种新开发的工具,该工具可以自动化研究人员常用的离散时间序列分析的许多过程,

更新日期:2020-08-25
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