Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

Search 250 million research papers

Read the abstract, see who wrote it and who cites it, and get the citation in APA, MLA, Chicago or Harvard.

About 10,000 papers for “Poisson process”

Poisson process

Erhan Çınlar · Encyclopedia of Environmetrics · 2006

Abstract Point processes are used as models for the configurations formed by the random positions of some species of particles in some space; the terms ‘particle’ and ‘position’ take different meanings in different applications. If the particles can be treated as indistinguishable, it is convenient to represent the point process by a random measure N , letting N(A) denote the number of particles in the set A , with A ranging over a suitable collection of subsets of the space involved. Poisson random measures (PRMs) (or processes) are the point processes par excellence: they are mathematically tractable and are applicable in a wide range of situations, either directly or after some transformations.

Cited by 0

Poisson process

Juan Pablo Rincón–zapatero · 2011

We study the asset allocation of defined benefit pension plans of the type designed and sponsored by firms with the aim of providing a lifetime pension to the employees at the age of retirement. Benefits are stochastic, combining Poisson jumps with Brownian uncertainty. The sponsor dynamically forms portfolios where the risky asset is also subjected to Poisson jumps and Brownian uncertainty, possibly correlated with the evolution of benefits. The objective is to assure future benefits, while controlling the contribution made to the fund reserves. The problem is solved analytically using dynamic programming techniques.

Cited by 0

Poisson Process

Sivaprasad Madhira, Shailaja Deshmukh · RePEc: Research Papers in Economics

Abstract The Poisson process is simple yet the most widely used continuous time Markov chain. It serves as a model for time epochs at which specific events, such as arrivals into a system, occur. In Sect. 2, the Poisson process is defined as a process with stationary and independent increments and it is established that the sojourn times are independent and identically distributed, each having exponential distribution. In Sect. 3, the Poisson process is defined as a point process in which inter-occurrence times are independent and identically distributed, each having exponential distribution. Equivalence of the two definitions is established. Non-homogeneous Poisson processes are studied in Sect. 4. Superposition and decomposition (thinning) of Poisson processes are discussed in Sect. 5. Section 6 deals with compound Poisson processes. The R codes used for numerical examples in the chapter are given in Sect. 7.

Cited by 0

Poisson Process

Ji Hwan Cha, Maxim Finkelstein · RePEc: Research Papers in Economics

Abstract This chapter is devoted to some basic properties of Poisson processes that will be intensively used in the rest of the book.

Cited by 0

Poisson Process

Lawrence A. J, Montwter California, A. J. Lawrence et al. · 1974

Cited by 0

Poisson process

Veronika Kralova · Digital Repository (National Repository of Grey Literature) · 2013

Poisson process is a random set, which analyses an occurrence of the independent random points in a certain set. An object of study are probabilistic properties of this random set. Basic definitions and properties are formulated for the Euclidean spaces of arbitrary dimension and used to simulate different types of Poisson processes. We provide the algoritm procedures and source codes for each simulation. Statistical test of complete spatial randomness (CSR) verifies in conclusion, if the simulated processes are really homogeneous Poisson processes with specific properties.

Cited by 0

Fuzzy Random Homogeneous Poisson Process and Compound Poisson Process

Shunqin Li, Ruiqing Zhao, Wansheng Tang · 2005

Abstract. By dealing with interarrival times as exponentially distributed fuzzy random variables, a fuzzy random homogeneous Poisson process and a fuzzy random compound Poisson process are respectively defined. Several theorems on the two processes are provided, respectively.

Cited by 2

BI-POISSON PROCESS

Jacek Weso̷lowski · 2004

Abstract. We study a two parameter family of processes with linear regressions and linear conditional variances. We give conditions for the unique solution of this problem, and point out the connection between the resulting Markov processes and the generalized convolutions introduced by Bo˙zejko and Speicher [2]. 1.

Cited by 0

The poisson process

Kozlowski, Andrzej · Acervo Digital da Universidade Estadual Paulista (Universidade Estadual Paulista) · 2013

This Demonstration shows sample trajectories of a Poisson process—a fundamental example of a stochastic process with discontinuous trajectories, which is used as a building block for constructing jump processes that play an important role in modern financial modeling. You can vary the intensity of the jumps, the duration, whether the trajectories should be connected, and whether an ordinary Poisson process or a "compensated" one should be displayed

Cited by 0

BI-POISSON PROCESS

WŁODZIMIERZ BRYC, JACEK WESOŁOWSKI · Infinite Dimensional Analysis Quantum Probability and Related Topics · 2007

Bi-Poisson processes are defined as a two-parameter family of processes with linear regressions and linear conditional variances. We give conditions for the existence and uniqueness of such processes. We point out that one-dimensional distributions of the bi-Poisson process are closed under a generalized free convolution introduced by Bożejko and Speicher. 7 .

Cited by 17Open access