Brownian excursion

In probability theory a Brownian excursion process is a stochastic process that is closely related to a Wiener process (or Brownian motion). Realisations of Brownian excursion processes are essentially just realizations of a Wiener process selected to satisfy certain conditions. In particular, a Brownian excursion process is a Wiener process conditioned to be positive and to take the value 0 at time 1. Alternatively, it is a Brownian bridge process conditioned to be positive. BEPs are important because, among other reasons, they naturally arise as the limit process of a number of conditional functional central limit theorems.^[1]

Definition[]

A Brownian excursion process, ${\displaystyle e}$, is a Wiener process (or Brownian motion) conditioned to be positive and to take the value 0 at time 1. Alternatively, it is a Brownian bridge process conditioned to be positive.

Another representation of a Brownian excursion ${\displaystyle e}$ in terms of a Brownian motion process W (due to Paul Lévy and noted by Kiyosi Itô and Henry P. McKean, Jr.^[2]) is in terms of the last time ${\displaystyle \tau _{-}}$ that W hits zero before time 1 and the first time ${\displaystyle \tau _{+}}$ that Brownian motion ${\displaystyle W}$ hits zero after time 1:^[2]

${\displaystyle \{e(t):\ {0\leq t\leq 1}\}\ {\stackrel {d}{=}}\ \left\{{\frac {|W((1-t)\tau _{-}+t\tau _{+})|}{\sqrt {\tau _{+}-\tau _{-}}}}:\ 0\leq t\leq 1\right\}.}$

Let ${\displaystyle \tau _{m}}$ be the time that a Brownian bridge process ${\displaystyle W_{0}}$ achieves its minimum on [0, 1]. Vervaat (1979) shows that

${\displaystyle \{e(t):\ {0\leq t\leq 1}\}\ {\stackrel {d}{=}}\ \left\{W_{0}(\tau _{m}+t{\bmod {1}})-W_{0}(\tau _{m}):\ 0\leq t\leq 1\right\}.}$

Properties[]

Vervaat's representation of a Brownian excursion has several consequences for various functions of ${\displaystyle e}$. In particular:

${\displaystyle M_{+}\equiv \sup _{0\leq t\leq 1}e(t)\ {\stackrel {d}{=}}\ \sup _{0\leq t\leq 1}W_{0}(t)-\inf _{0\leq t\leq 1}W_{0}(t),}$

(this can also be derived by explicit calculations^[3][4]) and

${\displaystyle \int _{0}^{1}e(t)\,dt\ {\stackrel {d}{=}}\ \int _{0}^{1}W_{0}(t)\,dt-\inf _{0\leq t\leq 1}W_{0}(t).}$

The following result holds:^[5]

${\displaystyle EM_{+}={\sqrt {\pi /2}}\approx 1.25331\ldots ,\,}$

and the following values for the second moment and variance can be calculated by the exact form of the distribution and density:^[5]

${\displaystyle EM_{+}^{2}\approx 1.64493\ldots \ ,\ \ \operatorname {Var} (M_{+})\approx 0.0741337\ldots .}$

Groeneboom (1989), Lemma 4.2 gives an expression for the Laplace transform of (the density) of ${\displaystyle \int _{0}^{1}e(t)\,dt}$. A formula for a certain double transform of the distribution of this area integral is given by Louchard (1984).

Groeneboom (1983) and Pitman (1983) give decompositions of Brownian motion ${\displaystyle W}$ in terms of i.i.d Brownian excursions and the least concave majorant (or greatest convex minorant) of ${\displaystyle W}$.

For an introduction to Itô's general theory of Brownian excursions and the Itô Poisson process of excursions, see Revuz and Yor (1994), chapter XII.

Connections and applications[]

The Brownian excursion area

${\displaystyle A_{+}\equiv \int _{0}^{1}e(t)\,dt}$

arises in connection with the enumeration of connected graphs, many other problems in combinatorial theory; see e.g.^{[6][7][8][9][10]} and the limit distribution of the Betti numbers of certain varieties in cohomology theory.^[11] Takacs (1991a) shows that ${\displaystyle A_{+}}$ has density

${\displaystyle f_{A_{+}}(x)={\frac {2{\sqrt {6}}}{x^{2}}}\sum _{j=1}^{\infty }v_{j}^{2/3}e^{-v_{j}}U\left(-{\frac {5}{6}},{\frac {4}{3}};v_{j}\right)\ \ {\text{ with }}\ \ v_{j}={\frac {2|a_{j}|^{3}}{27x^{2}}}}$

where ${\displaystyle a_{j}}$ are the zeros of the Airy function and ${\displaystyle U}$ is the confluent hypergeometric function. Janson and Louchard (2007) show that

${\displaystyle f_{A_{+}}(x)\sim {\frac {72{\sqrt {6}}}{\sqrt {\pi }}}x^{2}e^{-6x^{2}}\ \ {\text{ as }}\ \ x\rightarrow \infty ,}$

and

${\displaystyle P(A_{+}>x)\sim {\frac {6{\sqrt {6}}}{\sqrt {\pi }}}xe^{-6x^{2}}\ \ {\text{ as }}\ \ x\rightarrow \infty .}$

They also give higher-order expansions in both cases.

Janson (2007) gives moments of ${\displaystyle A_{+}}$ and many other area functionals. In particular,

${\displaystyle E(A_{+})={\frac {1}{2}}{\sqrt {\frac {\pi }{2}}},\ \ E(A_{+}^{2})={\frac {5}{12}}\approx 0.416666\ldots ,\ \ \operatorname {Var} (A_{+})={\frac {5}{12}}-{\frac {\pi }{8}}\approx .0239675\ldots \ .}$

Brownian excursions also arise in connection with queuing problems,^[12] railway traffic,^[13][14] and the heights of random rooted binary trees.^[15]

Related processes[]

• Brownian bridge
• Brownian meander
• reflected Brownian motion
• skew Brownian motion

Notes[]

References[]

• Chung, K. L. (1975). "Maxima in Brownian excursions". Bulletin of the American Mathematical Society. 81 (4): 742–745. doi:10.1090/s0002-9904-1975-13852-3. MR 0373035.
• Chung, K. L. (1976). "Excursions in Brownian motion". Arkiv för Matematik. 14 (1): 155–177. Bibcode:1976ArM....14..155C. doi:10.1007/bf02385832. MR 0467948.
• Durrett, Richard T.; Iglehart, Donald L. (1977). "Functionals of Brownian meander and Brownian excursion". Annals of Probability. 5 (1): 130–135. doi:10.1214/aop/1176995896. JSTOR 2242808. MR 0436354.
• Groeneboom, Piet (1983). "The concave majorant of Brownian motion". Annals of Probability. 11 (4): 1016–1027. doi:10.1214/aop/1176993450. JSTOR 2243513. MR 0714964.
• Groeneboom, Piet (1989). "Brownian motion with a parabolic drift and Airy functions". Probability Theory and Related Fields. 81: 79–109. doi:10.1007/BF00343738. MR 0981568. S2CID 119980629.
• Itô, Kiyosi; McKean, Jr., Henry P. (2013) [1974]. Diffusion Processes and their Sample Paths. Classics in Mathematics (Second printing, corrected ed.). Springer-Verlag, Berlin. ISBN 978-3540606291. MR 0345224.
• Janson, Svante (2007). "Brownian excursion area, Wright's constants in graph enumeration, and other Brownian areas". Probability Surveys. 4: 80–145. arXiv:0704.2289. Bibcode:2007arXiv0704.2289J. doi:10.1214/07-ps104. MR 2318402. S2CID 14563292.
• Janson, Svante; Louchard, Guy (2007). "Tail estimates for the Brownian excursion area and other Brownian areas". Electronic Journal of Probability. 12: 1600–1632. arXiv:0707.0991. Bibcode:2007arXiv0707.0991J. doi:10.1214/ejp.v12-471. MR 2365879. S2CID 6281609.
• Kennedy, Douglas P. (1976). "The distribution of the maximum Brownian excursion". Journal of Applied Probability. 13 (2): 371–376. doi:10.2307/3212843. JSTOR 3212843. MR 0402955.
• Lévy, Paul (1948). Processus Stochastiques et Mouvement Brownien. Gauthier-Villars, Paris. MR 0029120.
• Louchard, G. (1984). "Kac's formula, Levy's local time and Brownian excursion". Journal of Applied Probability. 21 (3): 479–499. doi:10.2307/3213611. JSTOR 3213611. MR 0752014.
• Pitman, J. W. (1983). "Remarks on the convex minorant of Brownian motion". Seminar on Stochastic Processes, 1982. Progr. Probab. Statist. Vol. 5. Birkhauser, Boston. pp. 219–227. MR 0733673.
• Revuz, Daniel; Yor, Marc (2004). Continuous Martingales and Brownian Motion. Grundlehren der mathematischen Wissenschaften. Vol. 293. Springer-Verlag, Berlin. doi:10.1007/978-3-662-06400-9. ISBN 978-3-642-08400-3. MR 1725357.
• Vervaat, W. (1979). "A relation between Brownian bridge and Brownian excursion". Annals of Probability. 7 (1): 143–149. doi:10.1214/aop/1176995155. JSTOR 2242845. MR 0515820.