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Dependence in Probability and Statistics

Lecture Notes in Statistics Band 187

Patrice Bertail, Paul Doukhan, Philippe Soulier

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Beschreibung

PThis book gives an account of recent developments in the field of probability and statistics for dependent data. It 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 times series and random fields. There is a section on statistical estimation problems and specific applications. The book is written as a succession of papers by field specialists, alternating general surveys, mostly at a level accessible to graduate students in probability and statistics, and more general research papers mainly suitable to researchers in the field./P

Produktdetails

Einband Taschenbuch
Herausgeber Patrice Bertail, Paul Doukhan, Philippe Soulier
Seitenzahl 490
Erscheinungsdatum 24.05.2006
Sprache Englisch
ISBN 978-0-387-31741-0
Verlag Springer US
Maße (L/B/H) 23,5/15,5/2,6 cm
Gewicht 1540 g
Abbildungen 40 schwarzweisse Abbildungen
Auflage 2006

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  • 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.