A modified version of the Kolmogorov-Smirnov (KS) test is presented as a tool to assess whether a specified, although arbitrary, probability model is unsuitable to describe the underlying distribution of a set of observations. The KS test computes distances between points of the sample cumulative distribution function and the hypothetical one as absolute differences between them, and then consi...

A new approach of parameterization is proposed to construct a general goodnessof-fit test. It can not only generate traditional tests (including the Kolmogorov–Smirnov, Cramér– von Mises and Anderson–Darling tests) but also produce new types of omnibus tests, which are generally much more powerful than the old ones.

This paper describes a simple, non-parametric and generic test of the equivalence of Receiver Operating Characteristic (ROC) curves based on a modified Kolmogorov-Smirnov (KS) test. The test is described in relation to the commonly used techniques such as the Area Under the ROC curve (AUC) and the Neyman-Pearson method. We first review how the KS test is used to test the null hypotheses that th...

A new method for the determination of electric signal time-shifts is introduced. As the Kolmogorov-Smirnov test, it is based on the comparison of the cumulative distribution functions of the reference signal with the test signal. This method is very fast and thus well suited for on-line applications. It is robust to noise and its performances in terms of precision are excellent for shift times ...

After several years of frantic development, the dream of an "ideal" library remains elusive. Traditionally, combinatorial chemistry has been used primarily for lead generation, and molecular diversity has been the method of choice for designing and prioritizing experiments. One aspect that often has been overlooked is the drug likeness of the resulting collections. Recently, there have been sev...

A novel method for computing exact p-values of one-sided statistics from the Kolmogorov-Smirnov family is presented. It covers Higher Criticism statistic, weighted statistics, and Berk-Jones statistics. In addition to p-values, can also be used power analysis, finding alpha-level thresholds, construction confidence bands empirical distribution function. With its quadratic runtime numerical stab...

Model assessment is a fundamental problem in science and engineering and it addresses the question of the validity of a model in the light of empirical evidence. In this paper, we propose a method for the assessment of dynamic nonlinear models based on empirical and predictive cumulative distributions of data and the Kolmogorov–Smirnov statistics. The technique is based on the generation of dis...

The algorithm takes as input a vector of data values which contains an initial segment of noise followed by the arrival of a signal. The algorithm returns an estimate of the time of arrival of the signal along with a binary random variable conf indicating the credibility of the estimate: conf = 1 indicating a level of confidence, conf = 0 indicating no confidence in the estimate. For the purpos...