29 research outputs found
Conditional Acceptability for Random Variables
Acceptable random variables introduced by Giuliano Antonini et al. (J. Math. Anal. Appl. 338:1188-1203, 2008) form a class of dependent random variables that contains negatively dependent random variables as a particular case. The concept of
acceptability has been studied by authors under various versions of the definition, such as extended acceptability or wide acceptability. In this paper, we combine the concept of acceptability with the concept of conditioning, which has been the
subject of current research activity. For conditionally acceptable random variables, we provide a number of probability inequalities that can be used to obtain asymptotic results
Asymptotic properties of wavelet-based estimator in nonparametric regression model with weakly dependent processes
Strong consistency of estimators in partially linear models for longitudinal data with mixing-dependent structure
Asymptotics of a wavelet estimator in the nonparametric regression model with repeated measurements under a NA error process
Berry–Esseen bounds for density estimates under NA assumption
Negatively associated random variable, Berry–Esseen bound, Density estimate,