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Dive into the research topics where Alexander Iksanov is active.

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Featured researches published by Alexander Iksanov.


Advances in Applied Probability | 2008

On the number of jumps of random walks with a barrier

Alexander Iksanov; Martin Möhle

Let S 0 := 0 and Sk := ξ 1 + ··· + ξk for k ∈ ℕ := {1, 2, …}, where {ξk : k ∈ ℕ} are independent copies of a random variable ξ with values in ℕ and distribution pk := P{ξ = k}, k ∈ ℕ. We interpret the random walk {Sk : k = 0, 1, 2, …} as a particle jumping to the right through integer positions. Fix n ∈ ℕ and modify the process by requiring that the particle is bumped back to its current state each time a jump would bring the particle to a state larger than or equal to n. This constraint defines an increasing Markov chain {Rk (n) : k = 0, 1, 2, …} which never reaches the state n. We call this process a random walk with barrier n. Let Mn denote the number of jumps of the random walk with barrier n. This paper focuses on the asymptotics of Mn as n tends to ∞. A key observation is that, under p 1 > 0, {Mn : n ∈ ℕ} satisfies the distributional recursion M 1 = 0 and for n = 2, 3, …, where In is independent of M 2, …, M n−1 with distribution P{In = k} = pk / (p 1 + ··· + p n−1), k ∈ {1, …, n − 1}. Depending on the tail behavior of the distribution of ξ, several scalings for Mn and corresponding limiting distributions come into play, including stable distributions and distributions of exponential integrals of subordinators. The methods used in this paper are mainly probabilistic. The key tool is to compare (couple) the number of jumps, Mn , with the first time, Nn , when the unrestricted random walk {Sk : k = 0, 1, …} reaches a state larger than or equal to n. The results are applied to derive the asymptotics of the number of collision events (that take place until there is just a single block) for β(a, b)-coalescent processes with parameters 0 < a < 2 and b = 1.


Theory of Probability and Its Applications | 2015

Weak Convergence of Finite-Dimensional Distributions of the Number of Empty Boxes in the Bernoulli Sieve

Alexander Iksanov; Alexander Marynych; Vladimir Vatutin

The Bernoulli sieve is a random allocation scheme obtained by placing independent points with the uniform


Electronic Journal of Probability | 2016

Local universality for real roots of random trigonometric polynomials

Alexander Iksanov; Zakhar Kabluchko; Alexander Marynych

[0,1]


Bernoulli | 2017

Asymptotics of random processes with immigration II: Convergence to stationarity

Alexander Iksanov; Alexander Marynych; Matthias Meiners

law into the intervals made up by successive positions of a multiplicative random walk with factors taking values in the interval


Journal of Applied Probability | 2016

A central limit theorem and a law of the iterated logarithm for the Biggins martingale of the supercritical branching random walk

Alexander Iksanov; Zakhar Kabluchko

(0,1)


Stochastic Processes and their Applications | 2015

Rate of convergence in the law of large numbers for supercritical general multi-type branching processes

Alexander Iksanov; Matthias Meiners

. Assuming that the number of points is equal to


Journal of Applied Probability | 2018

Functional limit theorems for the number of busy servers in a G/G/∞ queue

Alexander Iksanov; Wissem Jedidi; Fethi Bouzeffour

n


Journal of Applied Probability | 2018

On perpetuities with gamma-like tails

Dariusz Buraczewski; Piotr Dyszewski; Alexander Iksanov; Alexander Marynych

we investigate weak convergence, as


Statistics & Probability Letters | 2017

A law of the iterated logarithm for the number of occupied boxes in the Bernoulli sieve

Alexander Iksanov; Wissem Jedidi; Fethi Bouzeffour

n\to\infty


Journal of Applied Probability | 2017

Null recurrence and transience of random difference equations in the contractive case

Gerold Alsmeyer; Dariusz Buraczewski; Alexander Iksanov

, of finite-dimensional distributions of the number of empty intervals within the occupancy range. A new argument enables us to relax the constraints imposed in previous papers on the distribution of the factor of the multiplicative random walk.

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Alexander Marynych

Taras Shevchenko National University of Kyiv

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Matthias Meiners

Technische Universität Darmstadt

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Andrey Pilipenko

National Academy of Sciences

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