Large deviations of branching process in a random environment

2021 ◽  
Vol 31 (4) ◽  
pp. 281-291
Author(s):  
Aleksandr V. Shklyaev
Keyword(s):  
Difference Equation ◽  
Large Deviations ◽  
Random Environment ◽  
Branching Process ◽  
Branching Processes ◽  
Random Variables ◽  
Asymptotic Formulas ◽  
Random Difference Equation ◽  
Random Difference ◽  
Independent Identically Distributed

Abstract In this first part of the paper we find the asymptotic formulas for the probabilities of large deviations of the sequence defined by the random difference equation Y n+1=A n Y n + B n , where A 1, A 2, … are independent identically distributed random variables and B n may depend on { ( A k , B k ) , 0 ⩽ k < n } $ \{(A_k,B_k),0\leqslant k \lt n\} $ for any n≥1. In the second part of the paper this results are applied to the large deviations of branching processes in a random environment.

A characterization of the gamma distribution from a random difference equation

1988 ◽  
Vol 25 (1) ◽  
pp. 142-149 ◽  
Author(s):  
Eric S. Tollar
Keyword(s):  
Difference Equation ◽  
Gamma Distribution ◽  
Random Variables ◽  
Independent Random Variables ◽  
Characteristic Functions ◽  
Random Difference Equation ◽  
Random Difference

A characterization of the gamma distribution is considered which arises from a random difference equation. A proof without characteristic functions is given that if V and Y are independent random variables, then the independence of V · Y and (1 – V) · Y results in a characterization of the gamma distribution (after excluding the trivial cases).

A characterization of the gamma distribution from a random difference equation

1988 ◽  
Vol 25 (01) ◽  
pp. 142-149 ◽  
Author(s):  
Eric S. Tollar
Keyword(s):  
Difference Equation ◽  
Gamma Distribution ◽  
Random Variables ◽  
Independent Random Variables ◽  
Characteristic Functions ◽  
Random Difference Equation ◽  
Random Difference

A characterization of the gamma distribution is considered which arises from a random difference equation. A proof without characteristic functions is given that if V and Y are independent random variables, then the independence of V · Y and (1 – V) · Y results in a characterization of the gamma distribution (after excluding the trivial cases).

scholarly journals On the extinction times of varying and random environment branching processes

1975 ◽  
Vol 12 (01) ◽  
pp. 39-46 ◽  
Author(s):  
Alan Agresti
Keyword(s):  
Random Environment ◽  
Branching Process ◽  
Branching Processes ◽  
Sufficient Conditions ◽  
Random Variables ◽  
Extinction Time ◽  
Probability Of Extinction ◽  
Stochastically Bounded ◽  
Necessary And Sufficient ◽  
Varying Environment

Bounds are derived for the probability of extinction by the nth generation for a branching process in a varying environment. From these bounds, necessary and sufficient conditions are established for such a process to become extinct with probability one. The extinction time of a random environment branching process in which the environmental random variables are independent but not necessarily identically distributed is stochastically bounded by the extinction times of two varying environment processes.

Multitype weakly subcritical branching processes in random environment

2021 ◽  
Vol 31 (3) ◽  
pp. 207-222
Author(s):  
Vladimir A. Vatutin ◽  
Elena E. Dyakonova
Keyword(s):  
Random Walk ◽  
Random Environment ◽  
Survival Probability ◽  
Branching Process ◽  
Branching Processes ◽  
Left Eigenvector ◽  
Mean Values ◽  
Long Time ◽  
The Mean ◽  
Independent Identically Distributed

Abstract A multi-type branching process evolving in a random environment generated by a sequence of independent identically distributed random variables is considered. The asymptotics of the survival probability of the process for a long time is found under the assumption that the matrices of the mean values of direct descendants have a common left eigenvector and the increment X of the associated random walk generated by the logarithms of the Perron roots of these matrices satisfies conditions E X < 0 and E XeX > 0.

scholarly journals On the extinction times of varying and random environment branching processes

1975 ◽  
Vol 12 (1) ◽  
pp. 39-46 ◽  
Author(s):  
Alan Agresti
Keyword(s):  
Random Environment ◽  
Branching Process ◽  
Branching Processes ◽  
Sufficient Conditions ◽  
Random Variables ◽  
Extinction Time ◽  
Probability Of Extinction ◽  
Stochastically Bounded ◽  
Necessary And Sufficient ◽  
Varying Environment

Bounds are derived for the probability of extinction by the nth generation for a branching process in a varying environment. From these bounds, necessary and sufficient conditions are established for such a process to become extinct with probability one. The extinction time of a random environment branching process in which the environmental random variables are independent but not necessarily identically distributed is stochastically bounded by the extinction times of two varying environment processes.

Large deviations of branching processes with immigration in random environment

2017 ◽  
Vol 27 (6) ◽  
Author(s):  
Dmitriy V. Dmitruschenkov ◽  
Alexander V. Shklyaev
Keyword(s):  
Large Deviations ◽  
Random Environment ◽  
Branching Process ◽  
Branching Processes

AbstractWe consider branching process

scholarly journals On subcritical multi-type branching process in random environment

2008 ◽  
Vol DMTCS Proceedings vol. AI,... (Proceedings) ◽  
Author(s):  
Elena Dyakonova
Keyword(s):  
Random Walk ◽  
Random Environment ◽  
Survival Probability ◽  
Branching Process ◽  
Random Variables ◽  
International Audience ◽  
Watson Process ◽  
Independent Identically Distributed

International audience We investigate a multi-type Galton-Watson process in a random environment generated by a sequence of independent identically distributed random variables. Suppose that the associated random walk constructed by the logarithms of the Perron roots of the reproduction mean matrices has negative mean and assuming some additional conditions, we find the asymptotics of the survival probability at time $n$ as $n \to \infty$.

Large deviations of generalized renewal process

2020 ◽  
Vol 30 (4) ◽  
pp. 215-241
Author(s):  
Gavriil A. Bakay ◽  
Aleksandr V. Shklyaev
Keyword(s):  
Large Deviations ◽  
Renewal Process ◽  
Limit Theorems ◽  
Local Limit ◽  
Asymptotic Formulas ◽  
Additive Functionals ◽  
Wide Range ◽  
Finite Markov Chains ◽  
Independent Identically Distributed ◽  
Local Limit Theorems

AbstractLet (ξ(i), η(i)) ∈ ℝd+1, 1 ≤ i < ∞, be independent identically distributed random vectors, η(i) be nonnegative random variables, the vector (ξ(1), η(1)) satisfy the Cramer condition. On the base of renewal process, NT = max{k : η(1) + … + η(k) ≤ T} we define the generalized renewal process ZT = $\begin{array}{} \sum_{i=1}^{N_T} \end{array}$ξ(i). Put IΔT(x) = {y ∈ ℝd : xj ≤ yj < xj + ΔT, j = 1, …, d}. We find asymptotic formulas for the probabilities P(ZT ∈ IΔT(x)) as ΔT → 0 and P(ZT = x) in non-lattice and arithmetic cases, respectively, in a wide range of x values, including normal, moderate, and large deviations. The analogous results were obtained for a process with delay in which the distribution of (ξ(1), η(1)) differs from the distribution on the other steps. Using these results, we prove local limit theorems for processes with regeneration and for additive functionals of finite Markov chains, including normal, moderate, and large deviations.

Continuity for multi-type branching processes with varying environments

1999 ◽  
Vol 36 (01) ◽  
pp. 139-145 ◽  
Author(s):  
Owen Dafydd Jones
Keyword(s):  
Linear Combination ◽  
Branching Process ◽  
Branching Processes ◽  
Random Variables ◽  
Main Tool ◽  
Concentration Function ◽  
Independent Random Variables ◽  
Varying Environments

Conditions are derived for the components of the normed limit of a multi-type branching process with varying environments, to be continuous on (0, ∞). The main tool is an inequality for the concentration function of sums of independent random variables, due originally to Petrov. Using this, we show that if there is a discontinuity present, then a particular linear combination of the population types must converge to a non-random constant (Equation (1)). Ensuring this can not happen provides the desired continuity conditions.

Integer-valued branching processes with immigration

1983 ◽  
Vol 15 (04) ◽  
pp. 713-725 ◽  
Author(s):  
F. W. Steutel ◽  
W. Vervaat ◽  
S. J. Wolfe
Keyword(s):  
Difference Equation ◽  
Continuous Time ◽  
Queueing Theory ◽  
Branching Processes ◽  
Random Variables ◽  
Discrete State ◽  
Limiting Behaviour ◽  
Supercritical Branching Processes

The notion of self-decomposability for -valued random variables as introduced by Steutel and van Harn [10] and its generalization by van Harn, Steutel and Vervaat [5], are used to study the limiting behaviour of continuous-time Markov branching processes with immigration. This behaviour provides analogues to the behaviour of sequences of random variables obeying a certain difference equation as studied by Vervaat [12] and their continuous-time counterpart considered by Wolfe [13]. An application in queueing theory is indicated. Furthermore, discrete-state analogues are given for results on stability in the processes studied by Wolfe, and for results on self-decomposability in supercritical branching processes by Yamazato [14].

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