Lectures on Gaussian Processes
Gaussian processes can be viewed as a far-reaching infinite-dimensional extension of classical normal random variables. Their theory presents a powerful range of tools for probabilistic modelling in various academic and technical domains such as Statistics, Forecasting, Finance, Information Transmi...
Κύριος συγγραφέας: | |
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Συγγραφή απο Οργανισμό/Αρχή: | |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2012.
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Σειρά: | SpringerBriefs in Mathematics,
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Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Preface
- 1.Gaussian Vectors and Distributions
- 2.Examples of Gaussian Vectors, Processes and Distributions
- 3.Gaussian White Noise and Integral Representations
- 4.Measurable Functionals and the Kernel
- 5.Cameron-Martin Theorem
- 6.Isoperimetric Inequality
- 7.Measure Concavity and Other Inequalities
- 8.Large Deviation Principle
- 9.Functional Law of the Iterated Logarithm
- 10.Metric Entropy and Sample Path Properties
- 11.Small Deviations
- 12.Expansions of Gaussian Vectors
- 13.Quantization of Gaussian Vectors
- 14.Invitation to Further Reading
- References.