Dependence in Probability and Statistics

• Corporate Author: SpringerLink (Online service)
• Other Authors: Bertail, Patrice (Editor), Soulier, Philippe (Editor), Doukhan, Paul (Editor)
• Format: Electronic eBook
• Language: English
• Published: New York, NY : Springer New York, 2006.
• Series: Lecture Notes in Statistics, 187
• Subjects: Statistics.; Probabilities.; Statistical Theory and Methods.; Probability Theory and Stochastic Processes.

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...

Table of Contents:

• 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.