On the limiting distribution of a supercritical branching process in a random environment

1992 ◽  
Vol 29 (03) ◽  
pp. 499-518 ◽  
Author(s):  
Ben Hambly
Keyword(s):  
Distribution Function ◽  
Laplace Transform ◽  
Family Size ◽  
Random Environment ◽  
Branching Process ◽  
Random Variable ◽  
Limiting Distribution ◽  
The Laplace Transform

We consider an increasing supercritical branching process in a random environment and obtain bounds on the Laplace transform and distribution function of the limiting random variable. There are two possibilities that can be distinguished depending on the nature of the component distributions of the environment. If the minimum family size of each is 1, the growth will be as a power depending on a parameter α. If the minimum family sizes of some are greater than 1, it will be exponential, depending on a parameter γ. We obtain bounds on the distribution function analogous to those found for the simple Galton-Watson case. It is not possible to obtain exact estimates and we are only able to obtain bounds to within ε of the parameters.

On the limiting distribution of a supercritical branching process in a random environment

1992 ◽  
Vol 29 (3) ◽  
pp. 499-518 ◽  
Author(s):  
Ben Hambly
Keyword(s):  
Distribution Function ◽  
Laplace Transform ◽  
Family Size ◽  
Random Environment ◽  
Branching Process ◽  
Random Variable ◽  
Limiting Distribution ◽  
The Laplace Transform

We consider an increasing supercritical branching process in a random environment and obtain bounds on the Laplace transform and distribution function of the limiting random variable. There are two possibilities that can be distinguished depending on the nature of the component distributions of the environment. If the minimum family size of each is 1, the growth will be as a power depending on a parameter α. If the minimum family sizes of some are greater than 1, it will be exponential, depending on a parameter γ. We obtain bounds on the distribution function analogous to those found for the simple Galton-Watson case. It is not possible to obtain exact estimates and we are only able to obtain bounds to within ε of the parameters.

scholarly journals A Technique for Computing the PDFs and CDFs of Nonnegative Infinitely Divisible Random Variables

2011 ◽  
Vol 48 (01) ◽  
pp. 217-237 ◽  
Author(s):  
Mark S. Veillette ◽  
Murad S. Taqqu
Keyword(s):  
Distribution Function ◽  
Laplace Transform ◽  
Cumulative Distribution Function ◽  
Stable Distribution ◽  
Random Variable ◽  
Cumulative Distribution ◽  
Infinitely Divisible ◽  
The Laplace Transform ◽  
Laplace Transform Inversion ◽  
Probability Density Function Pdf

We present a method for computing the probability density function (PDF) and the cumulative distribution function (CDF) of a nonnegative infinitely divisible random variable X. Our method uses the Lévy-Khintchine representation of the Laplace transform Ee-λX = e-ϕ(λ), where ϕ is the Laplace exponent. We apply the Post-Widder method for Laplace transform inversion combined with a sequence convergence accelerator to obtain accurate results. We demonstrate this technique on several examples, including the stable distribution, mixtures thereof, and integrals with respect to nonnegative Lévy processes.

scholarly journals A Technique for Computing the PDFs and CDFs of Nonnegative Infinitely Divisible Random Variables

2011 ◽  
Vol 48 (1) ◽  
pp. 217-237 ◽  
Author(s):  
Mark S. Veillette ◽  
Murad S. Taqqu
Keyword(s):  
Distribution Function ◽  
Laplace Transform ◽  
Cumulative Distribution Function ◽  
Stable Distribution ◽  
Random Variable ◽  
Cumulative Distribution ◽  
Infinitely Divisible ◽  
The Laplace Transform ◽  
Laplace Transform Inversion ◽  
Probability Density Function Pdf

We present a method for computing the probability density function (PDF) and the cumulative distribution function (CDF) of a nonnegative infinitely divisible random variable X. Our method uses the Lévy-Khintchine representation of the Laplace transform Ee-λX = e-ϕ(λ), where ϕ is the Laplace exponent. We apply the Post-Widder method for Laplace transform inversion combined with a sequence convergence accelerator to obtain accurate results. We demonstrate this technique on several examples, including the stable distribution, mixtures thereof, and integrals with respect to nonnegative Lévy processes.

scholarly journals A note on Markov branching processes

1985 ◽  
Vol 17 (02) ◽  
pp. 463-464
Author(s):  
Fred M. Hoppe
Keyword(s):  
Laplace Transform ◽  
Simple Proof ◽  
Branching Process ◽  
Branching Processes ◽  
Markov Branching Process ◽  
The Laplace Transform

We present a simple proof of Zolotarev’s representation for the Laplace transform of the normalized limit of a Markov branching process and relate it to the Harris representation.

scholarly journals Exponential Growth of Bifurcating Processes with Ancestral Dependence

2015 ◽  
Vol 47 (02) ◽  
pp. 545-564 ◽  
Author(s):  
Sana Louhichi ◽  
Bernard Ycart
Keyword(s):  
Growth Rate ◽  
Laplace Transform ◽  
Exponential Growth ◽  
Branching Process ◽  
Cell Kinetics ◽  
Growth Models ◽  
Branching Processes ◽  
Independent Random Variables ◽  
The Laplace Transform ◽  
Ergodicity Coefficients

Branching processes are classical growth models in cell kinetics. In their construction, it is usually assumed that cell lifetimes are independent random variables, which has been proved false in experiments. Models of dependent lifetimes are considered here, in particular bifurcating Markov chains. Under the hypotheses of stationarity and multiplicative ergodicity, the corresponding branching process is proved to have the same type of asymptotics as its classic counterpart in the independent and identically distributed supercritical case: the cell population grows exponentially, the growth rate being related to the exponent of multiplicative ergodicity, in a similar way as to the Laplace transform of lifetimes in the i.i.d. case. An identifiable model for which the multiplicative ergodicity coefficients and the growth rate can be explicitly computed is proposed.

scholarly journals A note on Markov branching processes

1985 ◽  
Vol 17 (2) ◽  
pp. 463-464 ◽  
Author(s):  
Fred M. Hoppe
Keyword(s):  
Laplace Transform ◽  
Simple Proof ◽  
Branching Process ◽  
Branching Processes ◽  
Markov Branching Process ◽  
The Laplace Transform

We present a simple proof of Zolotarev’s representation for the Laplace transform of the normalized limit of a Markov branching process and relate it to the Harris representation.

Dirichlet Random Walks

2014 ◽  
Vol 51 (04) ◽  
pp. 1081-1099 ◽  
Author(s):  
Gérard Letac ◽  
Mauro Piccioni
Keyword(s):  
Random Walk ◽  
Laplace Transform ◽  
Dirichlet Process ◽  
Hypergeometric Functions ◽  
Bessel Functions ◽  
Random Variable ◽  
Infinite Divisibility ◽  
Stieltjes Transform ◽  
The Laplace Transform ◽  
Infinite Divisible Distributions

This paper provides tools for the study of the Dirichlet random walk inRd. We compute explicitly, for a number of cases, the distribution of the random variableWusing a form of Stieltjes transform ofWinstead of the Laplace transform, replacing the Bessel functions with hypergeometric functions. This enables us to simplify some existing results, in particular, some of the proofs by Le Caër (2010), (2011). We extend our results to the study of the limits of the Dirichlet random walk when the number of added terms goes to ∞, interpreting the results in terms of an integral by a Dirichlet process. We introduce the ideas of Dirichlet semigroups and Dirichlet infinite divisibility and characterize these infinite divisible distributions in the sense of Dirichlet when they are concentrated on the unit sphere ofRd.

scholarly journals The distribution and asympotic behaviour of the negative Wiener–Hopf factor for Lévy processes with rational positive jumps

2019 ◽  
Vol 56 (4) ◽  
pp. 1086-1105
Author(s):  
Ekaterina T. Kolkovska ◽  
Ehyter M. Martín-González
Keyword(s):  
Distribution Function ◽  
Laplace Transform ◽  
Probability Density ◽  
Lévy Processes ◽  
Levy Processes ◽  
Regularity Conditions ◽  
Asymptotic Results ◽  
Lévy Measure ◽  
The Laplace Transform ◽  
Additional Regularity

AbstractWe study the distribution of the negative Wiener–Hopf factor for a class of two-sided jump Lévy processes whose positive jumps have a rational Laplace transform. The positive Wiener–Hopf factor for this class of processes was studied by Lewis and Mordecki (2008). Here we obtain a formula for the Laplace transform of the negative Wiener–Hopf factor, as well as an explicit expression for its probability density in terms of sums of convolutions of known functions. Under additional regularity conditions on the Lévy measure of the studied processes, we also provide asymptotic results as $u\to-\infty$ for the distribution function F(u) of the negative Wiener–Hopf factor. We illustrate our results in some particular examples.

A Dam with seasonal input

1994 ◽  
Vol 31 (2) ◽  
pp. 526-541 ◽  
Author(s):  
Robert B. Lund
Keyword(s):  
Laplace Transform ◽  
Convergence Rates ◽  
Sufficient Conditions ◽  
Limiting Distribution ◽  
Stochastic Monotonicity ◽  
The Laplace Transform ◽  
Monotonicity Result ◽  
The Mean ◽  
The Moment ◽  
Necessary And Sufficient

This paper examines the infinitely high dam with seasonal (periodic) Lévy input under the unit release rule. We show that a periodic limiting distribution of dam content exists whenever the mean input over a seasonal cycle is less than 1. The Laplace transform of dam content at a finite time and the Laplace transform of the periodic limiting distribution are derived in terms of the probability of an empty dam. Necessary and sufficient conditions for the periodic limiting distribution to have finite moments are given. Convergence rates to the periodic limiting distribution are obtained from the moment results. Our methods of analysis lean heavily on the coupling method and a stochastic monotonicity result.

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