Strict monotonicity of stochastic process extreme distributions

Strict monotonicity of stochastic process extreme distributions

Strict monotonicity is proved for the distributions of extremes of processes consisting of series of bounded function with independent random coefficients, in particular for zero mean continuous Gaussian processes over compact metric space. These results have wide applications to global inference pr...

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Veröffentlicht in:Statistics & probability letters 2025-02, Vol.217, p.110292, Article 110292
1. Verfasser: Yang, Lijian
Format: Artikel
Sprache:eng
Schlagworte:
Baire measure
Itô–Nisio theorem
Karhunen–Loève expansion
Mercer series
Support of measure
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Beschreibung
Zusammenfassung:Strict monotonicity is proved for the distributions of extremes of processes consisting of series of bounded function with independent random coefficients, in particular for zero mean continuous Gaussian processes over compact metric space. These results have wide applications to global inference problems on unknown functions.
ISSN:0167-7152
DOI:10.1016/j.spl.2024.110292