Let X1, X2,… be independent variables, each having a normal distribution with negative mean -ßn = X1 + ??? + Xn, with S0 = 0as the Gaussian random walk. This paper is concerned with the cumulants of the maximum Mß=max{Sn:n=0}. We express all cumulants of Mß in terms of Taylor series about ß at 0 with coefficients that involve the Riemann zeta function. Building upon the work of Chang and Peres [J.T. Chang, Y. Peres, Ladder heights, Gaussian random walks and the Riemann zeta function, Ann. Probab. 25 (1997) 787–802] on and Bateman’s formulas on Lerch’s transcendent, expressions of this type for the first and second cumulants of Mß have been previously obtained by the authors [A.J.E.M. Janssen, J.S.H. van Leeuwaarden, On Lerch’s transcendent ...
AbstractLet F be a distribution function with negative mean and regularly varying right tail. Under ...
AbstractLet Sn, n ⩾ 1, be the partial sums of i.i.d. random variables with negative mean value. Many...
Let I(F) be the distribution function (d.f.) of the maximum of a random walk whose i.i.d. increments...
Let X1, X2,… be independent variables, each having a normal distribution with negative mean -ßn = X1...
AbstractLet X1,X2,… be independent variables, each having a normal distribution with negative mean −...
Abstract. Let X1, X2,... be independent variables, each having a normal distributio
Let X1,¿X2,¿… be independent variables, each having a normal distribution with negative mean -
This paper deals with the problem of obtaining methods to compute the distribution of the maximum of...
In this paper we present an analytical proof of the fact that the maximum of gaussian random walks e...
Abstract. We study the maximum of a Gaussian field on [0, 1]d (d ≥ 1) whose correlations decay loga-...
Let (xi(i), i >= 1) be a sequence of independent standard normal random variables and let S-k = Sigm...
AbstractLet {Xn} be a stationary Gaussian sequence with E{X0} = 0, {X20} = 1 and E{X0Xn} = rn n Let ...
This paper uses the Rice method [18] to give bounds to the distribution of the maximum of a smooth...
Consider a random walk S = (Sn: n ≥ 0) that is “perturbed ” by a stationary sequence (ξn: n ≥ 0) to ...
Let $\{X_n\}_{n\geq1}$ be a sequence of i.i.d. standard Gaussian random variables, let $S_n=\sum_{i=...
AbstractLet F be a distribution function with negative mean and regularly varying right tail. Under ...
AbstractLet Sn, n ⩾ 1, be the partial sums of i.i.d. random variables with negative mean value. Many...
Let I(F) be the distribution function (d.f.) of the maximum of a random walk whose i.i.d. increments...
Let X1, X2,… be independent variables, each having a normal distribution with negative mean -ßn = X1...
AbstractLet X1,X2,… be independent variables, each having a normal distribution with negative mean −...
Abstract. Let X1, X2,... be independent variables, each having a normal distributio
Let X1,¿X2,¿… be independent variables, each having a normal distribution with negative mean -
This paper deals with the problem of obtaining methods to compute the distribution of the maximum of...
In this paper we present an analytical proof of the fact that the maximum of gaussian random walks e...
Abstract. We study the maximum of a Gaussian field on [0, 1]d (d ≥ 1) whose correlations decay loga-...
Let (xi(i), i >= 1) be a sequence of independent standard normal random variables and let S-k = Sigm...
AbstractLet {Xn} be a stationary Gaussian sequence with E{X0} = 0, {X20} = 1 and E{X0Xn} = rn n Let ...
This paper uses the Rice method [18] to give bounds to the distribution of the maximum of a smooth...
Consider a random walk S = (Sn: n ≥ 0) that is “perturbed ” by a stationary sequence (ξn: n ≥ 0) to ...
Let $\{X_n\}_{n\geq1}$ be a sequence of i.i.d. standard Gaussian random variables, let $S_n=\sum_{i=...
AbstractLet F be a distribution function with negative mean and regularly varying right tail. Under ...
AbstractLet Sn, n ⩾ 1, be the partial sums of i.i.d. random variables with negative mean value. Many...
Let I(F) be the distribution function (d.f.) of the maximum of a random walk whose i.i.d. increments...