scholarly journals On the condensed density of the zeros of the Cauchy transform of a complex atomic random measure with Gaussian moments

2013 ◽  
Vol 83 (11) ◽  
pp. 2569-2576 ◽  
Author(s):  
P. Barone
Keyword(s):  
Random Measure ◽  
Cauchy Transform ◽  
Gaussian Moments

scholarly journals BSDEs with Logarithmic Growth Driven by Brownian Motion and Poisson Random Measure and Connection to Stochastic Control Problem

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Khalid Oufdil
Keyword(s):  
Optimal Control ◽  
Brownian Motion ◽  
Control Problem ◽  
Stochastic Optimal Control ◽  
Random Measure ◽  
Poisson Random Measure ◽  
One Dimensional ◽  
Stochastic Optimal Control Problem ◽  
Uniqueness Of The Solution ◽  
Logarithmic Growth

Abstract In this paper, we study one-dimensional backward stochastic differential equations under logarithmic growth in the 𝑧-variable ( | z | ⁢ | ln ⁡ | z | | ) (\lvert z\rvert\sqrt{\lvert\ln\lvert z\rvert\rvert}) . We show the existence and the uniqueness of the solution when the noise is driven by a Brownian motion and an independent Poisson random measure. In addition, we highlight the connection of such BSDEs with stochastic optimal control problem, where we show the existence of an optimal strategy for the control problem.

A Highway Traffic Model

1975 ◽  
Vol 12 (S1) ◽  
pp. 303-309
Author(s):  
Herbert Solomon
Keyword(s):  
Poisson Process ◽  
Poisson Distribution ◽  
Random Measure ◽  
Traffic Model ◽  
Highway Traffic ◽  
Intensity Parameter ◽  
Time Space ◽  
Random Line ◽  
Straight Line ◽  
Poisson Fields

The trajectory of a car traveling at a constant speed on an idealized infinite highway can be viewed as a straight line in the time-space plane. Entry times are governed by a Poisson process with intensity parameter A leading to all trajectories as random lines in a plane. The Poisson distribution of number of encounters of cars on the highway is developed through random line models and non-homogeneous Poisson fields, and its parameter, which depends on the specific random measure employed, is obtained explicitly.

scholarly journals On intensities of modulated Cox measures

1998 ◽  
Vol 11 (3) ◽  
pp. 411-423 ◽  
Author(s):  
Jewgeni H. Dshalalow
Keyword(s):  
Stochastic Process ◽  
Stochastic Models ◽  
Queueing Systems ◽  
Random Measure ◽  
Random Measures ◽  
Explicit Formulas ◽  
State Dependent

In this paper we introduce and study functionals of the intensities of random measures modulated by a stochastic process ξ, which occur in applications to stochastic models and telecommunications. Modulation of a random measure by ξ is specified for marked Cox measures. Particular cases of modulation by ξ as semi-Markov and semiregenerative processes enabled us to obtain explicit formulas for the named intensities. Examples in queueing (systems with state dependent parameters, Little's and Campbell's formulas) demonstrate the use of the results.

scholarly journals MCMC for Normalized Random Measure Mixture Models

2013 ◽  
Vol 28 (3) ◽  
pp. 335-359 ◽  
Author(s):  
Stefano Favaro ◽  
Yee Whye Teh
Keyword(s):  
Mixture Models ◽  
Random Measure

The steady-state distribution of spent service times present in the M/G/1 foreground–background processor-sharing queue

1988 ◽  
Vol 25 (1) ◽  
pp. 194-203 ◽  
Author(s):  
R. Schassberger
Keyword(s):  
Steady State ◽  
Random Measure ◽  
Processor Sharing ◽  
Steady State Distribution ◽  
State Distribution ◽  
Generating Functional ◽  
Service Times

The steady-state distribution of spent service times present in the M/G/1 foreground-background processor-sharing queue is described by a random measure, whose generating functional is obtained.

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