Dependence in Probability and Statistics

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This book gives a detailed account of some recent developments in the field of probability and statistics for dependent data. The book covers a wide range of topics from Markov chain theory and weak dependence with an emphasis on some recent developments on dynamical systems, to strong dependence in...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Bertail, Patrice (Editor ), Doukhan, Paul (Editor ), Soulier, Philippe (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York, NY : Springer New York : Imprint: Springer, 2006.
Edición:1st ed. 2006.
Colección:Lecture Notes in Statistics, 187
Temas:
Statistics .
Probabilities.
Statistical Theory and Methods.
Probability Theory.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Weak dependence and related concepts
  • Regeneration-based statistics for Harris recurrent Markov chains
  • Subgeometric ergodicity of Markov chains
  • Limit Theorems for Dependent U-statistics
  • Recent results on weak dependence for causal sequences. Statistical applications to dynamical systems.
  • Parametrized Kantorovich-Rubinštein theorem and application to the coupling of random variables
  • Exponential inequalities and estimation of conditional probabilities
  • Martingale approximation of non adapted stochastic processes with nonlinear growth of variance
  • Strong dependence
  • Almost periodically correlated processes with long memory
  • Long memory random fields
  • Long Memory in Nonlinear Processes
  • A LARCH(?) Vector Valued Process
  • On a Szegö type limit theorem and the asymptotic theory of random sums, integrals and quadratic forms
  • Aggregation of Doubly Stochastic Interactive Gaussian Processes and Toeplitz forms of U-Statistics
  • Statistical Estimation and Applications
  • On Efficient Inference in GARCH Processes
  • Almost sure rate of convergence of maximum likelihood estimators for multidimensional diffusions
  • Convergence rates for density estimators of weakly dependent time series
  • Variograms for spatial max-stable random fields
  • A non-stationary paradigm for the dynamics of multivariate financial returns
  • Multivariate Non-Linear Regression with Applications
  • Nonparametric estimator of a quantile function for the probability of event with repeated data.

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