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Cort J. Willmott Kenji Matsuura Scott M. Robeson 《Atmospheric environment (Oxford, England : 1994)》2009,43(3):749-752
Commonly used sums-of-squares-based error or deviation statistics—like the standard deviation, the standard error, the coefficient of variation, and the root-mean-square error—often are misleading indicators of average error or variability. Sums-of-squares-based statistics are functions of at least two dissimilar patterns that occur within data. Both the mean of a set of error or deviation magnitudes (the average of their absolute values) and their variability influence the value of a sum-of-squares-based error measure, which confounds clear assessment of its meaning. Interpretation problems arise, according to Paul Mielke, because sums-of-squares-based statistics do not satisfy the triangle inequality. We illustrate the difficulties in interpreting and comparing these statistics using hypothetical data, and recommend the use of alternate statistics that are based on sums of error or deviation magnitudes. 相似文献
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Kennedy Rebekah C. Fling Russell R. Robeson Michael S. Saxton Arnold M. Schneider Liesel G. Darcy John L. Bemis David A. Zhao Ling Chen Jiangang 《Environmental science and pollution research international》2018,25(15):14743-14751
Environmental Science and Pollution Research - Widely used as an antimicrobial in antibacterial bar soaps, triclocarban (3,4,4′-trichlorocarbanilide; TCC) is effective against Gram-positive... 相似文献
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