Beschreibung
This 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.
Inhaltsverzeichnis
Regeneration-based statistics for Harris recurrent Markov chains (Patrice Bertail, Stephan Clemencon).- Subgeometric ergodicity of Markov chains (Randal Douc, Eric Moulines, Philippe Soulier).- Limit theorems for dependent U-statistics (Herold Dehling).- Recent results on weak dependence for causal sequences. statistical applications to dynamic systems (Clementine Prieur).- Parametrized Kantorovic-RubinÅ¡tein theorem and application to the coupling of random variables (Jerome Dedecker, Clementine Prieur, Paul Raynaud De Fitte).- Exponential inequalities and estimation of conditional probabilities (V. Maume-Deschamps).- Martingale approximation of non adapted stochastic processes with nonlinear growth of variance (Dalibor Volny).- Almost periodically correlated processes with long memory (Anne Philippe, Donatas Surgailis, Marie-Claude Viano).- Long memory random fields (Frederic Lavancier).- Long memory in nonlinear processes (Rohit Deo, Mengchen Hsich, Clifford M. Hurvich, Philippe Soulier).- A LARCH (8) vector valued process (Paul Doukhan, Gilles Teyssiere, Pablo Winant).- On a Szegö type limit theorem and the asymptotic theory of random sums, integrals and quadratic forms (Florin Avram, Murad S. Taqqu).- Aggregation of doubly stochastic interactive Gaussian processes and Toeplitz forms of U-statistics (Didier Dacunha-Castelle, Lisandro FermÃn).- On efficient inference in GARCH processes (Christian Francq, Jean-Michel Zakoïan).- Almost sure rate of convergence of maximum likelihood estimators for multidimensional diffusions (Dasha Loukianova, Oleg Loukianova).- Convergence rates for density estimators of weakly dependent time series (Nicolas Ragache, Olivier Wintenberger).- Variograms for spatial max-stable random fields (Dan Cooley, Philippe Naveau, Paul Poncet).- A non-stationary paradigm for the dynamics of multivariate financial returns (Stefano Herzel, Catalin Starica, Reha Tütüncü).- Multivariate non-linear regression with applications (Tata Subba Rao, Gyorgy Terdik).- Nonparametric estimator of a quantile function for the probability of event with repeated data (Claire Pincon, Odile Pons).
Autorenporträt
InhaltsangabeWeak 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-Rubinstein 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.
