Dmitrii Zholud's repositories
Human-life-is-unlimited---but-short
We study IDL data on human mortality at extreme age. Our conclusion is that the upper limit to the human lifespan is infinite. Data, remarkably, shows no difference in mortality after age 110 between sexes, between ages, or between different lifestyles or genetic backgrounds.
Efficient-estimation-of-the-number-of-false-positives-in-high-throughput-screening
This paper develops new methods to handle false positives in High-Throughput Screening experiments.
Extreme-value-analysis-of-huge-datasets
PhD Thesis. Some results in Extreme Value Theory with applications to High-Throughput Screening and Bioinformatics.
Extremes-of-Shepp-statistics-for-Gaussian-random-walk
We derive asymptotic behavior of the probability of high-level excursion for the maximal increment of a Gaussian random walk.
Extremes-of-Shepp-statistics-for-the-Wiener-process
We derive asymptotic behavior of the probability of high-level excursion for the maximal increment of the Wiener process.
Human-mortality-at-extreme-age
Human mortality at extreme age
Is-there-a-cap-on-longevity
Is there a cap on longevity - a statistical review
On-the-limit-distribution-of-multiscale-test-statistics-for-nonparametric-curve-estimation
We prove continuity of the limit distribution function of certain multiscale test statistics which are used in nonparametric curve estimation.
Rejoinder-to-discussion-of-the-paper-Human-life-is-unlimited---but-short
What can be learned from data about human survival at extreme age? In this rejoinder we give our views on some of the issues raised in the discussion of our paper Rootzén and Zholud (2017).
Tail-approximations-for-the-Student-t--F--and-Welch-statistics
We present a detailed study of the asymptotic behavior of the distribution of the tails of these, perhaps, most commonly used statistical tests under non-standard conditions, that is, releasing the underlying assumptions of normality, independence and identical distribution and considering a more general case where one only assumes that the vector of data has a continuous joint density.
Tail-estimation-for-window-censored-processes
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 methods are applied to the 100-car study, a big naturalistic driving experiment.