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Given a dataset of earthquake occurrence times, locations, and magnitudes, the time-independent total seismicity is usually estimated by some nonparametric method, such as splines (Ogata, 1998), kernel functions (Zhuang et al, 2002; Helmstetter et al., 2007), grid averaging (Tsukakoshi and Shimazaki, 2006), and Tessellation (Ogata, 2004b).
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We demonstrate the advantage of some nonparametric methods for the epistatic genetic architecture.
Areas under receiver operating characteristic curves for reaching threshold of four at the initial intervention contact were estimated by a nonparametric method.
Areas under the ROC curves between the markers were compared by a nonparametric method (14).
The data were analysed using survival analysis by the nonparametric method of Kaplan Meier and the Cox regression model to determine risk ratios (RR) of prognostic factors.
The degree of fibrosis was positively correlated with the median value of WFA+-M2BP (P < 0.001) by a nonparametric method (Kruskal-Wallis' one-way ANOVA).
Data analysis was carried out by a nonparametric method (Mann-Whitney U test, Graph Pad Prism version 4.03) to establish statistical differences between groups.
The area under the ROC curves for each index was calculated by the nonparametric method of Hanley and McNeil [ 19] and compared through a technique developed by the same authors [ 19].
An ROC curve was then generated for the combination of relevant genes derived from the regression model, and its area was compared with that of every single virulence marker by a nonparametric method adapted to paired data (12).
An ROC curve was then generated for the combination derived from the regression model, and its area was compared with that of every single virulence marker by a nonparametric method adapted to paired data (15).
Secondly, input variables are transformed into higher correlated data space by virtue of nonparametric method so-called alternating conditional expectation (ACE).
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