RMSE is not enough: Guidelines to robust data-model comparisons for magnetospheric physics
نویسندگان
چکیده
The magnetospheric physics research community uses a broad array of quantitative data-model comparison methods (metrics) when conducting their investigations. It is often the case, though, that any particular study will only use one or two metrics, with most common being Pearson correlation coefficient and root mean square error (RMSE). Because metrics are designed to test specific aspect relationship, limiting reduces physical insights can be gleaned from analysis, restricting possible findings modeling studies. Additional obtained many types applied. We organize into primary groups: 1) fit performance based on value difference; 2) event detection which discrete classification data model values determined by specified threshold. In addition these groups, there several major categories relationship metric assesses: accuracy; bias; 3) precision; 4) association; 5) extremes. Another category skill, measure against reference model. These applied subset either values, known as reliability discrimination assessments. context examples, we discuss best practices for choosing
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ژورنال
عنوان ژورنال: Journal of Atmospheric and Solar-Terrestrial Physics
سال: 2021
ISSN: ['1879-1824', '1364-6826']
DOI: https://doi.org/10.1016/j.jastp.2021.105624