We characterize the robustness of subsampling procedures by deriving a formula for the breakdown point of subsampling quantiles. This breakdown point can be very low for moderate subsampling block sizes, which implies the fragility of subsampling procedures, even when they are applied to robust statistics. This instability arises also for data driven block size selection procedures minimizing t...

Two complementary schools have come to the fore in the field of Structural Equation Modelling (SEM): covariance-based SEM and component-based SEM. The first approach has been developed around Karl Jöreskog and the second one around Herman Wold under the name "PLS" (Partial Least Squares). Hwang and Takane have proposed a new component-based SEM method named Generalized Structured Component Anal...

In this study we address the problem of interpreting a bootstrap tree. The main issue is choosing the threshold of clade selection in order to separate reliable clades from unreliable ones, depending on their bootstrap proportion. This threshold depends on the chosen error measure. We investigate error measures that stem from a generalization of Robinson and Foulds’ (1981) distance, used to qua...

In this paper, we propose a procedure to obtain and test multifactor models based on statistical financial factors. A major issue in the factor literature is select factors included model, as well construction of portfolios. We deal with matter using dimensionality reduction technique designed work several groups data called Common Principal Components. block-bootstrap methodology developed ass...

Statistical methods for functional data are of interest for many applications. In this paper, we prove a central limit theorem for random variables taking their values in a Hilbert space. The random variables are assumed to be weakly dependent in the sense of near epoch dependence, where the underlying process fulfills some mixing conditions. As parametric inference in an infinite dimensional s...

An analytic wavelet transform, based on Hilbert wavelet pairs, is applied to bivariate time-varying spectral estimation for neurophysiological time series. Under the assumption of an underlying block stationary process, both single-trial and ensemble studies are amenable to this method. A bootstrap procedure, which samples with replacement blocks centered around the events of interest, is propo...

We consider consistent tests for stochastic dominance efficiency at any order of a given portfolio with respect to all possible portfolios constructed from a set of assets. We propose and justify approaches based on simulation and the block bootstrap to achieve valid inference in a time series setting. The test statistics and the estimators are computed using linear and mixed integer programmin...

In this paper we propose panel cointegration tests allowing for breaks and cross-section dependence based on the Continuos-Path Block bootstrap. Simulation evidence shows that the proposed panel tests have satisfactory size and power properties, hence improving considerably on asymptotic tests applied to individual series. As an empirical illustration we examined investment and saving for a pan...