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Azam Imomov

Publications and source records attributed to Azam Imomov.

5 recordsLinked to original sources

Second--order renewal asymptotics in the finite--variance regularly varying regime

We develop a refined asymptotic theory for renewal processes with regularly varying inter-arrival distributions in the finite-variance regime. Assuming that $1-F(t)=t^{-\alpha}L(t)$ with $\alpha\in(2,3)$ and $L$ slowly varying, we establish second-order asymptotic expansions for both the renewal convolution and the renewal function. The results reveal a two-scale structure: the equilibrium tail $Q_F(t)$ governs the local renewal correction, while the integrated tail $\rho(t)=\int_t^\infty Q_F(u)\,du$ determines the global deviation from equilibrium. A particular emphasis is placed on the critical threshold $\alpha=2$, where the asymptotic behaviour undergoes a structural transition. In this borderline case, the power-law hierarchy collapses and the dominant correction is governed by an integrated slowly varying tail. Nevertheless, the local renewal correction mechanism persists, and the correction term remains asymptotically proportional to the equilibrium tail. The analysis is based on a systematic use of Laplace-transform techniques and Tauberian transfer principles, which allow us to relate singular behaviour in the Laplace domain to precise time-domain asymptotics. The results provide a unified description of second-order renewal asymptotics across the entire range $2\leq\alpha<3$, and point to possible extensions to renewal equations and to age-dependent branching processes.

math.PR

On estimation of the convergence rate to invariant measures in markov branching processes with possibly infinite variance and allowing immigration

The paper discusses the continuous-time Markov Branching Process allowing Immigration. We are considering a critical case for which the second moment of offspring law and the first moment of immigration law are possibly infinite. Assuming that the nonlinear parts of the appropriate generating functions are regularly varying in the sense of Karamata, we prove theorems on convergence of transition functions of the process to invariant measures. We deduce the speed rate of these convergence providing that slowly varying factors are with the remainder.

math.PR

On explicit form of the Kolmogorov constant in the theory of Galton-Watson Branching Processes

The paper considers the well-known Galton-Watson stochastic branching process. We are dealing with a non-critical case. In the subcritical case, when the mean of the direct descendants of one particle per generation of the time step is less than 1, the population mean of the number of particles on the positive trajectories of the process stabilizes and approaches 1/K, where K is the so-called Kolmogorov constant. The paper is devoted to the search for an explicit expression of this constant depending on the structural parameters of the process. Our reasoning is essentially based on the Basic Lemma, which describes the asymptotic expansion of the generating function of the distribution of the number of particles. An important role is also played by the asymptotic properties of the transition probabilities of the so-called Q-process and their property convergence to invariant measures.

math.PR

On structural parameter estimation of the Markov Q-process

In the paper we consider a stochastic model which called Markov Q-processes that forms a continuous-time Markov population system. Markov Q-processes are defined as stochastic Markov branching processes with trajectories continuing in the remote future. Estimation of the structural parameter of the Markov Q-process is the main goal of this paper. To estimate this parameter, an unbiased estimator of the Lotka-Nagaev type is proposed. An asymptotic expansion of the variance of this estimator is found.

math.ST

On conditioned limit structure of the Markov branching process without finite second moment

Consider the continuous-time Markov Branching Process. In critical case we consider a situation when the generating function of intensity of transformation of particles has the infinite second moment, but its tail regularly varies in sense of Karamata. First we discuss limit properties of transition functions of the process. We prove local limit theorems and investigate ergodic properties of the process. Further we investigate limiting probability function conditioned to be never extinct. Hereupon we obtain a new stochastic population process as a continuous-time Markov chain called the Markov Q-Process. We study main properties of Markov Q-Process.

math.PR