Abstract
A notion of the positive spatial association is introduced in this paper to analyze spatial dependence of Boolean models with the focus on estimating the long-range spatial dependence. The explicit tail estimates for probabilities of simultaneous damage to two distant spatial regions are obtained using the regular variation method, and the long-range spatial covariance for the Boolean models with heavy-tailed grains is shown to decay at the power-law rate that is smaller than the tail decay rate of grains. Examples and applications to spatial reliability modeling are also discussed. © 2013 Springer Science+Business Media New York.
| Original language | English |
|---|---|
| Pages (from-to) | 139-154 |
| Journal | Annals of Operations Research |
| Volume | 212 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 2014 |
Research Keywords
- Boolean model
- Heavy-tailed grains
- Positive association
- Power-law decay
- Regular variation
- Spatial extremes
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