Abstract
Previous work on the joint asymptotic distribution of the sum and maxima of Gaussian processes is extended here. In particular, it is shown that for a stationary sequence of standard normal random variables with correlation function r, the condition r(n) ln n = o(1) as n → ∞ suffices to establish the asymptotic independence of the sum and maximum.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 958-971 |
| Number of pages | 14 |
| Journal | Journal of Applied Probability |
| Volume | 37 |
| Issue number | 4 |
| DOIs | |
| State | Published - Dec 2000 |
Keywords
- Gaussian process
- Maximum
- Strongly dependent
- Sum
- Weakly dependent