We review and compare block, sieve and local bootstraps for time series and thereby
illuminate theoretical aspects of the procedures as well as their performance on finite …

In this paper we discuss weak dependence and mixing properties of some popular models.
We also develop some of their econometric applications. Autoregressive models …

This volume is devoted to the study of asymptotic properties of wide classes of stochastic
systems arising in mathematical statistics, percolation theory, statistical physics and …

This book offers a predominantly theoretical coverage of statistical prediction, with some
potential applications discussed, when data and/or parameters belong to a large or infinite …

We compare three dependence coefficients expressed in terms of conditional expectations,
and we study their behaviour in various situations. Next, we give a new covariance …

Many authors have used one of the two following type of dependence: on the one hand
mixing properties, introduced by Rosenblatt (1956)[166], on the other hand martingales …

Controlling the false discovery rate (FDR) is a powerful approach to multiple testing, with
procedures developed with applications in many areas. Dependence among the test …

The mixing condition is often considered to modeling the functional time series data.
Alternatively, in this work we consider the problem of nonparametric estimation of the …

Local linear fitting of nonlinear processes under strong (ie, α-) mixing conditions has been
investigated extensively. However, it is often a difficult step to establish the strong mixing of a …

We consider kernel density and regression estimation for a wide class of nonlinear time
series models. Asymptotic normality and uniform rates of convergence of kernel estimators …