While performing statistical tests [7] the first question is which statistical test, parametric or non-parametric, is suitable. It is well known that parametric tests have much more power (probability that a statistical test will correctly reject a false null hypothesis, or a probability of avoiding a Type II error) than a non-parametric test. Hence, we should use parametric tests whenever allo...

We explore in depth the validity of a recently proposed scaling law for earthquake interevent time distributions in the case of the Southern California, using the waveform cross-correlation catalog of Shearer et al. Two statistical tests are used: on the one hand, the standard two-sample Kolmogorov-Smirnov test is in agreement with the scaling of the distributions. On the other hand, the one-sa...

A theory of matrix-valued functions from the matricial Smirnov class Nn (D) is systematically developed. In particular, the maximum principle of V.I.Smirnov, inner-outer factorization, the Smirnov-Beurling characterization of outer functions and an analogue of Frostman’s theorem are presented for matrix-valued functions from the Smirnov class Nn (D). We also consider a family Fλ = F − λI of fun...

Résumé. Le critère de découpage binaire de Kolmogorov-Smirnov nécessite un ordre total des valeurs prises par les variables explicatives. Nous pouvons ordonner des intervalles fermés bornés de nombres réels de différentes façons. Notre contribution dans cet article consiste à évaluer et à comparer des arbres de décision obtenus sur des données de type intervalle à l’aide du critère de découpage...

Our investigation aims at detecting network intrusions using decision tree algorithms. Large differences in prior class probabilities of intrusion data have been reported to hinder the performance of decision trees. We propose to replace the Shannon entropy used in tree induction algorithms with a Kolmogorov Smirnov splitting criterion which locates a Bayes optimal cutpoint of attributes. The K...

G08CDF also returns the standardized statistic Z 1⁄4 ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi n1 þ n2 n1n2 r D, where D may be Dn1;n2 , D þ n1;n2 or D n1;n2 depending on the choice of the alternative hypothesis. The distribution of this statistic converges asymptotically to a distribution given by Smirnov as n1 and n2 increase; see Feller (1948), Kendall and Stuart (1973), Kim and Jenri...