Patrice Bertail & Paul Doukhan 
Dependence in Probability and Statistics [PDF ebook] 

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.