Gaussian Random Functions:
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Dordrecht
Springer Netherlands
1995
|
| Series: | Mathematics and Its Applications
322 |
| Subjects: | |
| Online Access: | Volltext |
| Item Description: | 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 |
| Physical Description: | 1 Online-Ressource (XI, 337 p) |
| ISBN: | 9789401584746 9789048145287 |
| DOI: | 10.1007/978-94-015-8474-6 |
Staff View
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| spelling | Lifshits, M. A. Verfasser aut Gaussian Random Functions by M. A. Lifshits Dordrecht Springer Netherlands 1995 1 Online-Ressource (XI, 337 p) txt rdacontent c rdamedia cr rdacarrier Mathematics and Its Applications 322 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 Mathematics Functional analysis Distribution (Probability theory) Statistics Probability Theory and Stochastic Processes Statistics, general Measure and Integration Functional Analysis Mathematik Statistik Zufällige Folge (DE-588)4191092-8 gnd rswk-swf Zufallsfunktion (DE-588)4191096-5 gnd rswk-swf Maßtheorie (DE-588)4074626-4 gnd rswk-swf Normalverteilung (DE-588)4075494-7 gnd rswk-swf Konvexe Funktion (DE-588)4139679-0 gnd rswk-swf Gauß-Prozess (DE-588)4156111-9 gnd rswk-swf 1\p (DE-588)4113937-9 Hochschulschrift gnd-content Zufallsfunktion (DE-588)4191096-5 s Normalverteilung (DE-588)4075494-7 s 2\p DE-604 Gauß-Prozess (DE-588)4156111-9 s 3\p DE-604 Konvexe Funktion (DE-588)4139679-0 s 4\p DE-604 Maßtheorie (DE-588)4074626-4 s 5\p DE-604 Zufällige Folge (DE-588)4191092-8 s 6\p DE-604 https://doi.org/10.1007/978-94-015-8474-6 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 4\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 5\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 6\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Lifshits, M. A. Gaussian Random Functions Mathematics Functional analysis Distribution (Probability theory) Statistics Probability Theory and Stochastic Processes Statistics, general Measure and Integration Functional Analysis Mathematik Statistik Zufällige Folge (DE-588)4191092-8 gnd Zufallsfunktion (DE-588)4191096-5 gnd Maßtheorie (DE-588)4074626-4 gnd Normalverteilung (DE-588)4075494-7 gnd Konvexe Funktion (DE-588)4139679-0 gnd Gauß-Prozess (DE-588)4156111-9 gnd |
| subject_GND | (DE-588)4191092-8 (DE-588)4191096-5 (DE-588)4074626-4 (DE-588)4075494-7 (DE-588)4139679-0 (DE-588)4156111-9 (DE-588)4113937-9 |
| title | Gaussian Random Functions |
| title_auth | Gaussian Random Functions |
| title_exact_search | Gaussian Random Functions |
| title_full | Gaussian Random Functions by M. A. Lifshits |
| title_fullStr | Gaussian Random Functions by M. A. Lifshits |
| title_full_unstemmed | Gaussian Random Functions by M. A. Lifshits |
| title_short | Gaussian Random Functions |
| title_sort | gaussian random functions |
| topic | Mathematics Functional analysis Distribution (Probability theory) Statistics Probability Theory and Stochastic Processes Statistics, general Measure and Integration Functional Analysis Mathematik Statistik Zufällige Folge (DE-588)4191092-8 gnd Zufallsfunktion (DE-588)4191096-5 gnd Maßtheorie (DE-588)4074626-4 gnd Normalverteilung (DE-588)4075494-7 gnd Konvexe Funktion (DE-588)4139679-0 gnd Gauß-Prozess (DE-588)4156111-9 gnd |
| topic_facet | Mathematics Functional analysis Distribution (Probability theory) Statistics Probability Theory and Stochastic Processes Statistics, general Measure and Integration Functional Analysis Mathematik Statistik Zufällige Folge Zufallsfunktion Maßtheorie Normalverteilung Konvexe Funktion Gauß-Prozess Hochschulschrift |
| url | https://doi.org/10.1007/978-94-015-8474-6 |
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