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Engelbert–Schmidt zero–one law

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TheEngelbert–Schmidt zero–one law is a theorem that gives a mathematical criterion for an event associated with a continuous, non-decreasing additive functional of Brownian motion to have probability either 0 or 1, without the possibility of an intermediate value. This zero-one law is used in the study of questions of finiteness and asymptotic behavior forstochastic differential equations.[1] (AWiener process is a mathematical formalization of Brownian motion used in the statement of the theorem.) This 0-1 law, published in 1981, is named after Hans-Jürgen Engelbert[2] and the probabilist Wolfgang Schmidt[3] (not to be confused with the number theoristWolfgang M. Schmidt).

Engelbert–Schmidt 0–1 law

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LetF{\displaystyle {\mathcal {F}}} be aσ-algebra and letF=(Ft)t0{\displaystyle F=({\mathcal {F}}_{t})_{t\geq 0}} be an increasing family of sub-σ-algebras ofF{\displaystyle {\mathcal {F}}}. Let(W,F){\displaystyle (W,F)} be aWiener process on theprobability space(Ω,F,P){\displaystyle (\Omega ,{\mathcal {F}},P)}.Suppose thatf{\displaystyle f} is aBorel measurable function of the real line into [0,∞].Then the following three assertions are equivalent:

(i)P(0tf(Ws)ds< for all t0)>0{\displaystyle P{\Big (}\int _{0}^{t}f(W_{s})\,\mathrm {d} s<\infty {\text{ for all }}t\geq 0{\Big )}>0}.

(ii)P(0tf(Ws)ds< for all t0)=1{\displaystyle P{\Big (}\int _{0}^{t}f(W_{s})\,\mathrm {d} s<\infty {\text{ for all }}t\geq 0{\Big )}=1}.

(iii)Kf(y)dy<{\displaystyle \int _{K}f(y)\,\mathrm {d} y<\infty \,} for all compact subsetsK{\displaystyle K} of the real line.[4]

Extension to stable processes

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In 1997 Pio Andrea Zanzotto proved the following extension of the Engelbert–Schmidt zero-one law. It contains Engelbert and Schmidt's result as a special case, since the Wiener process is a real-valuedstable process of indexα=2{\displaystyle \alpha =2}.

LetX{\displaystyle X} be aR{\displaystyle \mathbb {R} }-valuedstable process of indexα(1,2]{\displaystyle \alpha \in (1,2]} on the filteredprobability space(Ω,F,(Ft),P){\displaystyle (\Omega ,{\mathcal {F}},({\mathcal {F}}_{t}),P)}.Suppose thatf:R[0,]{\displaystyle f:\mathbb {R} \to [0,\infty ]} is aBorel measurable function.Then the following three assertions are equivalent:

(i)P(0tf(Xs)ds< for all t0)>0{\displaystyle P{\Big (}\int _{0}^{t}f(X_{s})\,\mathrm {d} s<\infty {\text{ for all }}t\geq 0{\Big )}>0}.

(ii)P(0tf(Xs)ds< for all t0)=1{\displaystyle P{\Big (}\int _{0}^{t}f(X_{s})\,\mathrm {d} s<\infty {\text{ for all }}t\geq 0{\Big )}=1}.

(iii)Kf(y)dy<{\displaystyle \int _{K}f(y)\,\mathrm {d} y<\infty \,} for all compact subsetsK{\displaystyle K} of the real line.[5]

The proof of Zanzotto's result is almost identical to that of the Engelbert–Schmidt zero-one law. The key object in the proof is thelocal time process associated with stable processes of indexα(1,2]{\displaystyle \alpha \in (1,2]}, which is known to be jointly continuous.[6]

See also

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References

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  1. ^Karatzas, Ioannis; Shreve, Steven (2012).Brownian motion and stochastic calculus. Springer. p. 215.ISBN 978-0-387-97655-6.
  2. ^Hans-Jürgen Engelbert at theMathematics Genealogy Project
  3. ^Wolfgang Schmidt at theMathematics Genealogy Project
  4. ^Engelbert, H. J.; Schmidt, W. (1981). "On the behavior of certain functionals of the Wiener process and applications to stochastic differential equations". In Arató, M.; Vermes, D.; Balakrishnan, A. V. (eds.).Stochastic Differential Systems. Lectures Notes in Control and Information Sciences. Vol. 36. Berlin; Heidelberg: Springer. pp. 47–55.doi:10.1007/BFb0006406.ISBN 3-540-11038-0.
  5. ^Zanzotto, P. A. (1997)."On solutions of one-dimensional stochastic differential equations driven by stable Lévy motion"(PDF).Stochastic Processes and Their Applications.68:209–228.doi:10.1214/aop/1023481008.
  6. ^Bertoin, J. (1996).Lévy Processes, Theorems V.1, V.15. Cambridge University Press.
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