Dmitrii Zholud

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We prove continuity of the limit distribution function of certain multiscale test statistics which are used in nonparametric curve estimation. A particular variant of multiscale testing was introduced in Dümbgen and Spokoiny (2001) in order to test qualitative hypotheses about an unknown regression function such as nonpositivity, monotonicity or concavity.(More)
This paper develops tail estimation methods to handle false positives in multiple testing problems where testing is done at extreme significance levels and with low degrees of freedom, and where the true null distribution may differ from the theoretical one. We show that the number of false positives, conditional on the total number of positives,(More)
This paper develops methods to estimate the tail and full distribution of the lengths of the 0-intervals in a continuous time stationary ergodic stochastic process which takes the values 0 and 1 in alternating intervals. The setting is that each of many such 0-1 processes have been observed during a short time window. Thus the observed 0-intervals could be(More)
This material contains introduction to the SmartTail software; proofs of Theorems 1, 2, and 3 in the paper; derivation of equation (10); additional results and discussion for dependent p-values; sandwich estimators for dependent p-values; additional plots for the yeast genome and salt stress screening data; and two additional examples: association mapping(More)
This thesis presents results in Extreme Value Theory with applications to High-Throughput Screening and Bioinformatics. The methods described here, however, are applicable to statistical analysis of huge datasets in general. The main results are covered in four papers. The first paper develops novel methods to handle false rejections in High-Throughput(More)
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