P. BREMAUD, CEREMADE, Universite de Paris IX (Dauphine). Abstract Optimal stochastic control of point processes (and more generally of marked. Increas- ingly, spatial-temporal point processes are used to describe environmental process. This sort of definition is used by Jacod (), Brémaud (). Authors; Authors and affiliations. P. Bremaud Point Process Counting Process Jump Process Stochastic Integration Local Martingale. These keywords were.
You do not currently have access to this article. All poknt results are employed in probability and statistics with a particular importance in the theory of point processes  and queueing theory  as well as the related fields stochastic geometry continuum percolation theory and spatial statistics. Stochastic geometry and its applicationsvolume 2.
If the positioning of the interfering transmitters are assumed to form some point process, then shot noise can be used to model the sum of their interfering signals, which has led to stochastic geometry models of wireless networks. University of California, Berkeley- Martingales Mathematics – pages.
A crash course in stochastic geometry. Related articles in Google Scholar. Probability and random processes. If you originally registered with a username please use that to sign in. Most users should sign in with their email address. Citing articles via Google Scholar. This equation naturally holds for the homogeneous Poisson point processes, which is an example of a stationary stochastic process.
The name of both theorems stems from the work   by Norman R. A Martingale Approach to Point Processes. From this theorem some expectation results for the Poisson point process follow, including its Laplace functional.
Facebook Twitter Advertising and Corporate Services. Account Options Sign in. Palm Martingale calculus and stochastic recurrences. Common terms and phrases absolutely continuous adapted to Fe,t basic measurable space bounded bounded variation Brownian motion continuous with respect corrupted by white Definition ii dispatching equation exp iu F,Fe family Fe filtering function Girsanov theorem innovation theorem jumps Kunita and Watanabe L2 martingale left continuous Lemma Let Q Markov chain Markov process martingale characterization martingale theory measurable process adapted Meyer Meyer’s decomposition modulating mutual information natural increasing process p,Fe paragraph probability measure probability space problem process with rate proof random rate random variable right continuous paths right continuous step self-exciting point process Snyder space of point space Q square integrable martingale standard Poisson process step process Stieltjes integral stochastic differential equations stochastic integral Stochastic Processes Theorem B.
Close mobile search navigation Article navigation. For other uses, see Campbell’s theorem geometry.
Lower bounds for the height in Galois extensions: Foundations and Trends in Networking. Retrieved from brsmaud https: These random sums over point processes have applications in many areas where they are used as mathematical models.
One version of the theorem,  also known as Campbell’s formula: Sign in via your Institution Sign in. Issues About Advertising and Corporate Services. Oxford University Press is a department of the University of Oxford.
Article PDF first page preview. In probability theory and statisticsProcessse theorem or the Campbell—Hardy theorem is either a particular equation or set of results relating to the expectation of a function summed over a point process to an integral involving the mean measure of the point process, which allows for the calculation of expected value and variance of the random sum.
Don’t have an account? Hardywhich has inspired the result to be sometimes called the Campbell—Hardy theorem. My library Help Advanced Book Search.
This article is about random point processes. To calculate the sum of a function of a single point as well as the entire point process, then generalized Campbell’s theorems are required using the Palm distribution processs the point process, which is based on the branch of probability known as Palm theory or Palm calculus.