Willkommen, schön sind Sie da!
Logo Ex Libris

Gaussian Random Functions

  • Fester Einband
  • 337 Seiten
(0) Erste Bewertung abgeben
Alle Bewertungen ansehen
It is well known that the normal distribution is the most pleasant, one can even say, an exemplary object in the probability theor... Weiterlesen
CHF 283.00
Print on demand - Exemplar wird für Sie besorgt.
Kein Rückgaberecht!
Bestellung & Lieferung in eine Filiale möglich


It is well known that the normal distribution is the most pleasant, one can even say, an exemplary object in the probability theory. It combines almost all conceivable nice properties that a distribution may ever have: symmetry, stability, indecomposability, a regular tail behavior, etc. Gaussian measures (the distributions of Gaussian random functions), as infinite-dimensional analogues of tht classical normal distribution, go to work as such exemplary objects in the theory of Gaussian random functions. When one switches to the infinite dimension, some "one-dimensional" properties are extended almost literally, while some others should be profoundly justified, or even must be reconsidered. What is more, the infinite-dimensional situation reveals important links and structures, which either have looked trivial or have not played an independent role in the classical case. The complex of concepts and problems emerging here has become a subject of the theory of Gaussian random functions and their distributions, one of the most advanced fields of the probability science. Although the basic elements in this field were formed in the sixties-seventies, it has been still until recently when a substantial part of the corresponding material has either existed in the form of odd articles in various journals, or has served only as a background for considering some special issues in monographs.


Preface. 1: Gaussian distributions and random variables. 2: Multi-dimensional Gaussian distributions. 3: Covariances. 4: Random functions. 5: Examples of Gaussian random functions. 6: Modelling the covariances. 7: Oscillations. 8: Infinite-dimensional Gaussian distributions. 9: Linear functionals, admissible shifts, and the kernel. 10: The most important Gaussian distributions. 11: Convexity and the isoperimetric inequality. 12: The large deviations principle. 13: Exact asymptotics of large deviations. 14: Metric entropy and the comparison principle. 15: Continuity and boundedness. 16: Majorizing measures. 17: The functional law of the iterated logarithm. 18: Small deviations. 19: Several open problems. Comments. References. Subject index. List of basic notations.


Titel: Gaussian Random Functions
EAN: 9780792333852
ISBN: 978-0-7923-3385-2
Format: Fester Einband
Herausgeber: Springer Netherlands
Genre: Mathematik
Anzahl Seiten: 337
Gewicht: 671g
Größe: H24mm x B241mm x T170mm
Jahr: 1995
Auflage: 1995

Weitere Produkte aus der Reihe "Mathematics and Its Applications"