Dudley's theorem

In probability theory, Dudley's theorem is a result relating the expected upper bound and regularity properties of a Gaussian process to its entropy and covariance structure.

History

The result was first stated and proved by V. N. Sudakov, as pointed out in a paper by Richard M. Dudley.[1] Dudley had earlier credited Volker Strassen with making the connection between entropy and regularity.

Statement

Let (X_t)_t∈T be a Gaussian process and let d_X be the pseudometric on T defined by

d_{X}(s,t)={\sqrt {\mathbf {E} {\big [}|X_{s}-X_{t}|^{2}]}}.\,

For ε > 0, denote by N(T, d_X; ε) the entropy number, i.e. the minimal number of (open) d_X-balls of radius ε required to cover T. Then

\mathbf {E} \left[\sup _{t\in T}X_{t}\right]\leq 24\int _{0}^{+\infty }{\sqrt {\log N(T,d_{X};\varepsilon )}}\,\mathrm {d} \varepsilon .

Furthermore, if the entropy integral on the right-hand side converges, then X has a version with almost all sample path bounded and (uniformly) continuous on (T, d_X).

References

Dudley, Richard (2016). Houdré, Christian; Mason, David; Reynaud-Bouret, Patricia; Jan Rosiński, Jan (eds.). V. N. Sudakov's work on expected suprema of Gaussian processes. High Dimensional Probability. Vol. VII. pp. 37–43.

Dudley, Richard M. (1967). "The sizes of compact subsets of Hilbert space and continuity of Gaussian processes". Journal of Functional Analysis. 1 (3): 290–330. doi:10.1016/0022-1236(67)90017-1. MR 0220340.
Ledoux, Michel; Talagrand, Michel (1991). Probability in Banach spaces. Berlin: Springer-Verlag. pp. xii+480. ISBN 3-540-52013-9. MR 1102015. (See chapter 11)

This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.

[1] Dudley, Richard (2016). Houdré, Christian; Mason, David; Reynaud-Bouret, Patricia; Jan Rosiński, Jan (eds.). V. N. Sudakov's work on expected suprema of Gaussian processes. High Dimensional Probability. Vol. VII. pp. 37–43.