Abstract
Consider events of the form {Zs ≥ ζ (s),s ∈ S}, where Z is a continuous Gaussian process with stationary increments, ζ is a function that belongs to the reproducing kernel Hilbert space R of process Z, and S ⊂ R is compact. The main problem considered in this paper is identifying the function β∗ ∈ R satisfying β
∗(s) ≥ ζ (s) on S and having minimal R-norm. The smoothness (mean square differentiability) of Z turns out to have a crucial impact on the structure of the solution. As examples, we obtain the explicit solutions when ζ (s) = s for s ∈ [0, 1] and Z is either a fractional Brownian motion or an integrated Ornstein–Uhlenbeck process.
∗(s) ≥ ζ (s) on S and having minimal R-norm. The smoothness (mean square differentiability) of Z turns out to have a crucial impact on the structure of the solution. As examples, we obtain the explicit solutions when ζ (s) = s for s ∈ [0, 1] and Z is either a fractional Brownian motion or an integrated Ornstein–Uhlenbeck process.
Original language | English |
---|---|
Pages (from-to) | 1269-1293 |
Number of pages | 25 |
Journal | Stochastic Processes and their Applications |
Volume | 116 |
Issue number | 9 |
DOIs | |
Publication status | Published - 2006 |
MoE publication type | A1 Journal article-refereed |
Keywords
- sample-path large deviations
- dominating point
- kernel Hilbert space
- minimum norm problem
- fractional brownian motion
- busy period
- Ornstein-Uhlenbeck process
- Gaussian processes