Showing 1 - 7 of 7
We consider the extreme values of fractional Brownian motions, self-similar Gaussian processes and more general Gaussian processes which have a trend -ct[beta] for some constants c,[beta]0 and a variance t2H. We derive the tail behaviour of these extremes and show that they occur mainly in the...
Persistent link: https://www.econbiz.de/10008874557
It is known that the partial maximum of nonstationary Gaussian sequences converges in distribution and that the number of exceedances of a boundary is asymptotically a Poisson random variable, under certain restrictions. We investigate the rate of Poisson approximation for the number of...
Persistent link: https://www.econbiz.de/10008874717
We deal with the distribution of the first zero Rn of the real part of the empirical characteristic function related to a random variable X. Depending on the behaviour of the theoretical real part of the underlying characteristic function, several cases have to be considered. For most of the...
Persistent link: https://www.econbiz.de/10008875201
Any multivariate distribution can occur as the limit of extreme values in a sequence of independent, non-identically distributed random vectors. Under a reasonable uniform negligibility condition the class of such limit distribution can be totally characterized, which extends the known...
Persistent link: https://www.econbiz.de/10008875681
We consider general nonstationary max-autoregressive sequences Xi, i [greater-or-equal, slanted] 1, with Xi = Zimax(Xi - 1, Yi) where Yi, i [greater-or-equal, slanted] 1 is a sequence of i.i.d. random variables and Zi, i [greater-or-equal, slanted] 1 is a sequence of independent random variables...
Persistent link: https://www.econbiz.de/10008875849
We derive the exact asymptotic behavior of the ruin probability P{X(t)x for some t0} for the process , with respect to level x which tends to infinity. We assume that the underlying process [xi](t) is a.s. continuous stationary Gaussian with mean zero and correlation function regularly varying...
Persistent link: https://www.econbiz.de/10008872658
Let {Xk, k[epsilon]Z} be a stationary Gaussian sequence with EX1 - 0, EX2k = 1 and EX0Xk = rk. Define [tau]x = inf{k: Xk - [beta]k} the first crossing point of the Gaussian sequence with the function - [beta]t ([beta] 0). We consider limit distributions of [tau]x as [beta]--0, depending on the...
Persistent link: https://www.econbiz.de/10008873736