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Distribution Fitting 2. Pearson-Fisher, Kolmogorov-Smirnov, Anderson-Darling, Wilks-Shapiro, Cramer-von-Misses and Jarque-Bera statistics | | Lorentz Jantschi
; Sorana D. Bolboaca
; | | Date: |
16 Jul 2009 | | Abstract: | The methods measuring the departure between observation and the model were
reviewed. The following statistics were applied on two experimental data sets:
Chi-Squared, Kolmogorov-Smirnov, Anderson-Darling, Wilks-Shapiro, and
Jarque-Bera. Both investigated sets proved not to be normal distributed. The
Grubbs test identified one outlier and after its removal the normality of the
set of 205 chemical active compounds was accepted. The second data set proved
not to have any outliers. Kolmogorov-Smirnov statistic is less affected by the
existence of outliers (positive variation expressed as percentage smaller than
2). The outliers bring to Kolmogorov-Smirnov statistic errors of type II and to
the Anderson-Darling statistic errors of type I. | | Source: | arXiv, 0907.2832 | | Services: | Forum | Review | PDF | Favorites | |
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