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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Lifshits, Mikhail (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012.
Edición:1st ed. 2012.
Colección:SpringerBriefs in Mathematics,
Temas:
Probabilities.
Probability Theory.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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