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Serik Sagitov

Publications and source records attributed to Serik Sagitov.

At least 19 recordsLinked to original sources

The Multinomial Allocation Model and the Random Box Load

We revisit the random allocation model in which $n$ balls are independently placed into $N$ boxes with probabilities $q_1,\ldots,q_N$. A classical asymptotic result due to Kolchin, Sevastyanov, and Chistyakov for the expectations, variances, and covariances of the occupancy counts is reformulated in a compact and transparent form in terms of the load of a randomly selected box. We further derive explicit two-sided bounds for the associated remainder terms, obtained under weaker assumptions than those previously required.

math.PR

Theta-positive branching in varying environment

Branching processes in a varying environment encompass a wide range of stochastic demographic models, and their complete understanding in terms of limit behaviour poses a formidable research challenge. In this paper, we conduct a thorough investigation of such processes within a continuous-time framework, assuming that the reproduction law of individuals adheres to a specific parametric form for the probability generating function. Our six clear-cut limit theorems support the notion of recognizing five distinct asymptotical regimes for branching in varying environments: supercritical, asymptotically degenerate, critical, strictly subcritical, and loosely subcritical.

math.PR

A multitype Galton-Watson model for rejuvenating cells

We employ the framework of multitype Galton-Watson processes to model a population of dividing cells. The cellular type is represented by its biological age, defined as the count of harmful proteins hosted by the cell. The stochastic evolution of the biological age of a cell is modeled as a discrete Markov chain with a finite state space $\{0,1,\ldots,n\}$, where $n$ signifies the absorbing state corresponding to the senescent state of the cell. Consequently, the set of individual types in the multitype Galton-Watson process becomes $\{0,\ldots,n-1\}$. In our setting, a dividing cell may undergo rejuvenation meaning that its biological ages reduces due to transfer of harmful proteins to the daughter cell. For the proposed model, we define and study several biologically meaningful features, such as rejuvenation states, expected replicative lifespan, population growth rate, stable biological age distribution, and the population average of the biological age.

math.PR

Galton-Watson theta-processes in a varying environment

We consider a special class of Galton-Watson theta-processes in a varying environment fully defined by four parameters, with two of them $(θ,r)$ being fixed over time $n$, and the other two $(a_n,c_n)$ characterizing the altering reproduction laws. We establish a sequence of transparent limit theorems for the theta-processes with possibly defective reproduction laws. These results may serve as a stepping stone towards incisive general results for the Galton-Watson processes in a varying environment.

math.PR

Counting unique molecular identifiers in sequencing using a multitype branching process with immigration

Detection of extremely rare variant alleles, such as tumour DNA, within a complex mixture of DNA molecules is experimentally challenging due to sequencing errors. Barcoding of target DNA molecules in library construction for next-generation sequencing provides a way to identify and bioinformatically remove polymerase induced errors. During the barcoding procedure involving $t$ consecutive PCR cycles, the DNA molecules become barcoded by unique molecular identifiers (UMI). Different library construction protocols utilise different values of $t$. The effect of a larger $t$ and imperfect PCR amplifications is poorly described. This paper proposes a branching process with growing immigration as a model describing the random outcome of $t$ cycles of PCR barcoding. Our model discriminates between five different amplification rates $r_1$, $r_2$, $r_3$, $r_4$, $r$ for different types of molecules associated with the PCR barcoding procedure. We study this model by focussing on $C_t$, the number of clusters of molecules sharing the same UMI, as well as $C_t(m)$, the number of UMI clusters of size $m$. Our main finding is a remarkable asymptotic pattern valid for moderately large $t$. It turns out that $E(C_t(m))/E(C_t)\approx 2^{-m}$ for $m=1,2,\ldots$, regardless of the underlying parameters $(r_1,r_2,r_3,r_4,r)$. The knowledge of the quantities $C_t$ and $C_t(m)$ as functions of the experimental parameters $t$ and $(r_1,r_2,r_3,r_4,r)$ will help the users to draw more adequate conclusions from the outcomes of different sequencing protocols.

q-bio.QM

Critical branching as a pure death process coming down from infinity

We consider the critical Galton-Watson process with overlapping generations stemming from a single founder. Assuming that both the variance of the offspring number and the average generation length are finite, we establish the convergence of the finite-dimensional distributions, conditioned on non-extinction at a remote time of observation. The limiting process is identified as a pure death process coming down from infinity. This result brings a new perspective on Vatutin's dichotomy claiming that in the critical regime of age-dependent reproduction, an extant population either contains a large number of short-living individuals or consists of few long-living individuals.

math.PR

Critical Galton-Watson processes with overlapping generations

A properly scaled critical Galton-Watson process converges to a continuous state critical branching process $ξ(\cdot)$ as the number of initial individuals tends to infinity. We extend this classical result by allowing for overlapping generations and considering a wide class of population counts. The main result of the paper establishes a convergence of the finite dimensional distributions for a scaled vector of multiple population counts. The set of the limiting distributions is conveniently represented in terms of integrals $(\int_0^yξ(y-u)du^γ, y\ge0)$ with a pertinent $γ\ge0$.

math.PR

Optimal preventive maintenance scheduling for wind turbines under condition monitoring

We suggest a mathematical model for computing and regularly updating the next preventive maintenance plan for a wind farm. Our optimization criterium takes into account the current ages of the key components, the major maintenance costs including eventual energy production losses as well as the available data monitoring the condition of the wind turbines. We illustrate our approach with a case study based on data collected from several wind farms located in Sweden. Our results show that preventive maintenance planning gives some effect, if the wind turbine components in question live significantly shorter than the turbine itself.

math.OC

Optimal maintenance schedule for a wind turbine with aging components

Wind power is one of the most important sources of renewable energy. A large part of the wind energy cost is due to the cost of maintaining the wind power equipment. To further reduce the maintenance cost, one can improve the design of the wind turbine components. One can also reduce the maintenance costs by optimal scheduling of the component replacements. The latter task is the main motivation for this paper. When a wind turbine component fails to function, it might need to be replaced under less than ideal circumstances. This is known as corrective maintenance. To minimize the unnecessary costs, a more active maintenance policy based on the life expectancy of the key components is preferred. Optimal scheduling of preventive maintenance activities requires advanced mathematical modeling. In this paper, an optimization model is developed using the renewal-reward theorem. In the multi-component setting, our approach involves a new idea of virtual maintenance which allows us to treat each replacement event as a renewal event even if some components are not replaced by new ones. The proposed optimization algorithm is applied to a four-component model of a wind turbine and the optimal maintenance plans are computed for various initial conditions. The modeling results showed clearly the benefit of PM planning compared to pure CM strategy (about 8.5% lower maintenance cost). When we compare it with another state-of-art optimization model, it shows similar scheduling with a much faster CPU time. The comparison demonstrated that our model is both fast and accurate.

math.OC

Optimal scheduling of the next preventive maintenance activity for a wind farm

A large part of the operational cost for a wind power farm is due to the cost of equipment maintenance, especially for offshore wind farms. How to reduce the maintenance cost, and hence increase profitability, is this article's focus. It presents a binary linear optimization model whose solution may suggest the wind turbine owners which components, and when, should undergo the next preventive maintenance (PM) replacements. The suggested short-term scheduling strategy takes into account eventual failure events of the multi-component system, in that after the failed system is repaired, the previously scheduled PM plan should be updated, assuming that the restored components are as good as new. The optimization algorithm of this paper, NextPM, is tested through numerical case studies applied to a four component model of a wind turbine. The first study addresses the important case of a single component system, used for parameter calibration purposes. The second study analyses the case of seasonal variations of mobilization costs, as compared to the constant mobilization cost setting. Among other things, this analysis reveals a 35% cost reduction achieved by the NextPM model, as compared to the pure corrective maintenance (CM) strategy. %In these two case studies, the costs are reduced by around. The third case study compares the NextPM model with another optimization model - the preventive maintenance scheduling problem with interval costs (PMSPIC), which was the major source of inspiration for this article. This comparison demonstrates that the NextPM model is accurate and much faster in terms of computational time.

math.OC

Perron-Frobenius theory for kernels and Crump-Mode-Jagers processes with macro-individuals

Perron-Frobenius theory developed for irreducible non-negative kernels deals with so-called $R$-positive recurrent kernels. If kernel $M$ is $R$-positive recurrent, then the main result determines the limit of the scaled kernel iterations $R^nM^n$ as $n\to\infty$. In the Nummelin's monograph this important result is proven using a regeneration method whose major focus is on $M$ having an atom. In the special case when $M=P$ is a stochastic kernel with an atom, the regeneration method has an elegant explaination in terms of an associated split chain. In this paper we give a new probabilistic interpretation of the general regeneration method in terms of multi-type Galton-Watson processes producing clusters of particles. Treating clusters as macro-individuals, we arrive at a single-type Crump-Mode-Jagers process with a naturally embedded renewal structure.

math.PR

Rank-dependent Galton-Watson processes and their pathwise duals

We introduce a modified Galton-Watson process using the framework of an infinite system of particles labeled by $(x,t)$, where $x$ is the rank of the particle born at time $t$. The key assumption concerning the offspring numbers of different particles is that they are independent, but their distributions may depend on the particle label $(x,t)$. For the associated system of coupled monotone Markov chains, we address the issue of pathwise duality elucidated by a remarkable graphical representation, with the trajectories of the primary Markov chains and their duals coalescing together to form forest graphs on a two-dimensional grid.

math.PR

Defective Galton-Watson processes

The Galton-Watson process is a Markov chain modeling the population size of independently reproducing particles giving birth to $k$ offspring with probability $p_k$, $k\ge0$. In this paper we consider {\it defective} Galton-Watson processes having defective reproduction laws, so that $\sum_{k\ge0}p_k=1-\eps$ for some $\eps\in(0,1)$. In this setting, each particle may send the process to a graveyard state $Δ$ with probability $\eps$. Such a Markov chain, having an enhanced state space $\{0,1,\ldots\}\cup\{Δ\}$, gets eventually absorbed either at $0$ or at $Δ$. Assuming that the process has avoided absorption until the observation time $t$, we are interested in its trajectories as $t\to\infty$ and $\eps\to0$.

math.PR

Limit theorems for pure death processes coming down from infinity

We consider a pure death process $(Z(t), t\ge0)$ with death rates $λ_n$ satisfying the condition $\sum_{n=2}^\infty λ_n^{-1}<\infty$ of coming from infinity, $Z(0)=\infty$, down to an absorbing state $n=1$. We establish limit theorems for $Z(t)$ as $t\to0$, which strengthen the results that can be extracted from [1]. We also prove a large deviation theorem assuming that $λ_n$ regularly vary as $n\to\infty$ with an index $ β>1$. It generalises a similar statement with $β=2$ obtained in [4] for $λ_n={n\choose 2}$.

math.PR

General linear-fractional branching processes with discrete time

We study a linear-fractional Bienaymé-Galton-Watson process with a general type space. The corresponding tree contour process is described by an alternating random walk with the downward jumps having a geometric distribution. This leads to the linear-fractional distribution formula for an arbitrary observation time, which allows us to establish transparent limit theorems for the subcritical, critical and supercritical cases. Our results extend recent findings for the linear-fractional branching processes with countably many types.

math.PR

A special family of Galton-Watson processes with explosions

The linear-fractional Galton-Watson processes is a well known case when many characteristics of a branching process can be computed explicitly. In this paper we extend the two-parameter linear-fractional family to a much richer four-parameter family of reproduction laws. The corresponding Galton-Watson processes also allow for explicit calculations, now with possibility for infinite mean, or even infinite number of offspring. We study the properties of this special family of branching processes, and show, in particular, that in some explosive cases the time to explosion can be approximated by the Gumbel distribution.

math.PR

Tail generating functions for extendable branching processes

We study branching processes of independently splitting particles in the continuous time setting. If time is calibrated such that particles live on average one unit of time, the corresponding transition rates are fully determined by the generating function $f$ for the offspring number of a single particle. We are interested in the defective case $f(1)=1-ε$, where each splitting particle with probability $ε$ is able to terminate the whole branching process. A branching process $\{Z_t\}_{t\ge0}$ will be called extendable if $f(q)=q$ and $f(r)=r$ for some $0\le q<r<\infty$. Specializing on the extendable case we derive an integral equation for $F_t(s)={\rm E} s^{Z_t}$. This equation is expressed in terms of what we call, tail generating functions. With help of this equation, we obtain limit theorems for the time to termination as $ε\to0$. We find that conditioned on non-extinction, the typical values of the termination time follow an exponential distribution in the nearly subcritical case, and require different scalings depending on whether the reproduction regime is asymptotically critical or supercritical. Using the tail generating function approach we also obtain new refined asymptotic results for the regular branching processes with $f(1)=1$.

math.PR