Approximations for weighted Kolmogorov–Smirnov distributions via boundary crossing probabilities - Université Grenoble Alpes
Article Dans Une Revue Statistics and Computing Année : 2017

Approximations for weighted Kolmogorov–Smirnov distributions via boundary crossing probabilities

Résumé

A statistical application to Gene Set Enrichment Analysis implies calculating the distribution of the maximum of a certain Gaussian process, which is a modification of the standard Brownian bridge. Using the transformation into a boundary crossing problem for the Brownian motion and a piecewise linear boundary, it is proved that the desired distribution can be approximated by an n-dimensional Gaussian integral. Fast approximations are defined and validated by Monte Carlo simulation. The performance of the method for the genomics application is discussed.

Dates et versions

hal-01879590 , version 1 (24-09-2018)

Identifiants

Citer

Nino Kordzakhia, Alexander Novikov, Bernard Ycart. Approximations for weighted Kolmogorov–Smirnov distributions via boundary crossing probabilities. Statistics and Computing, 2017, 27 (6), pp.1513-1523. ⟨10.1007/s11222-016-9701-y⟩. ⟨hal-01879590⟩
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