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1992 | Buch

Excursions of Markov Processes

verfasst von: Robert M. Blumenthal

Verlag: Birkhäuser Boston

Buchreihe : Probability and its Applications

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Über dieses Buch

Let {Xti t ~ O} be a Markov process in Rl, and break up the path X t into (random) component pieces consisting of the zero set ({ tlX = O}) and t the "excursions away from 0," that is pieces of path X. : T ::5 s ::5 t, with Xr- = X = 0, but X. 1= 0 for T < s < t. When one measures the time in t the zero set appropriately (in terms of the local time) the excursions acquire a measure theoretic structure practically identical to that of processes with stationary independent increments, except the values of the process are paths rather than real numbers. And there is a measure on path space that helps describe the measure theoretic properties of the excursions in the same way that the Levy measure describes the jumps of a process with independent increments. The entire circle of ideas is called excursion theory. There are many attractive things about the subject: it is an area where one can use to advantage general probabilistic potential theory to make quite specific calculations, it provides a natural setting for apply­ ing esoteric things like David Williams' path decomposition, it provides a method for constructing processes whose description in terms of an in­ finitesimal generator or some such analytic object would be complicated. And the ideas seem to be closely related to a good deal of current research in probability.

Inhaltsverzeichnis

Frontmatter
I. Markov Processes
Abstract
We will assume the reader is familiar with the concepts of a probability triple (Ω, F, P) and conditional expectation relative to a sub σ-algebra G of F. If (E,ε) is a measurable space and {X t ;tϵT} is an indexed family of functions from Ω to E such that X t -1 (AF for each Aϵε we say that {X t ;tϵT} is a stochastic process (defined over Ω) with state space E. We call Ω the sample space.
Robert M. Blumenthal
II. Examples
Abstract
In this chapter we will give examples of various kinds of Markov processes. Also we will construct Brownian motion and use it to construct some other processes that are particularly important in excursion theory.
Robert M. Blumenthal
III. Point Processes of Excursions
Abstract
In this chapter we will develop the theory of Poisson point processes, and give Itô’s theory of the analysis of a Markov process in terms of its excursions away from a fixed point in the state space.
Robert M. Blumenthal
IV. Brownian Excursion
Abstract
In this chapter we will give various descriptions of Brownian excursion measure; that is the measure Pˆ one obtains when the basic process X is Brownian motion in R1 and the distinguished point b is the origin. Also we will describe the excursion structure of some processes closely related to Brownian motion.
Robert M. Blumenthal
V. Itô’s Synthesis Theorem
Abstract
In this chapter we will prove Itô’s synthesis theorem to the effect that under certain hypotheses the paths of a Poisson point process of excursions can be linked together to make up a Markov process.
Robert M. Blumenthal
VI. Excursions and Local Time
Abstract
For many processes each point in the state space is regular for itself, and so for each point x we have the notions of local time at x and of excursions away from x. Brownian motion in R and most one dimensional diffusion processes are important examples. There has been a great deal of attention focused on the question of how in such cases the local time {L(t, x); t ≥ 0} at x varies with x and on the use of excursion theory, not only to study this question but also to make other important constructions. In this chapter we will give some applications of excursion theory to such matters. We will be considering local time and excursions at several points simultaneously, but the basic notion is still excursions away from a single point, so that no new notions appear. This should be contrasted with the situation in the next chapter. There we will be considering processes essentially in higher dimensional state spaces, where the relevant notion is that of excursions of the path away from a rather general set and where much less is known about specific formulas and constructions.
Robert M. Blumenthal
VII. Excursions Away From a Set
Abstract
Part of the theory of excursions away from a point can be generalized as follows. Let {X t ; t ≥ 0} be a standard process and let V be a subset of the state space E. We will assume that V is closed and that every point of V is regular for V, that is P x (σ = 0) = 1 for all x in V where σ = σ v = inf{t > 0|X t V}. As in Chapter III let G = G(ω) denote the strictly positive left ends of the open intervals making up the complement of the closure of {t|X t (ω) ∈ V}.
Robert M. Blumenthal
Backmatter
Metadaten
Titel
Excursions of Markov Processes
verfasst von
Robert M. Blumenthal
Copyright-Jahr
1992
Verlag
Birkhäuser Boston
Electronic ISBN
978-1-4684-9412-9
Print ISBN
978-1-4684-9414-3
DOI
https://doi.org/10.1007/978-1-4684-9412-9