Conditional empirical processes defined by nonstationary absolutely regular sequences

DOI10.1006/jmva.1999.1822zbMath0952.62035OpenAlexW2036131387MaRDI QIDQ1303861

Michel Harel, Madan Lal Puri

Publication date: 25 October 1999

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1006/jmva.1999.1822

zbMATH Keywords

empirical distribution functionabsolute regularityconditional empirical process

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Order statistics; empirical distribution functions (62G30) Functional limit theorems; invariance principles (60F17)

Related Items (4)

The marked empirical process to test nonlinear time series against a large class of alternatives when the random vectors are nonstationary and absolutely regular ⋮ Une méthode semi-paramétrique pour tester un modèle de régression. (A semi-parametric method to test a regression model) ⋮ ROBUST FORECAST COMPARISON ⋮ Central limit theorem of the smoothed empirical distribution functions for asymptotically stationary absolutely regular stochastic processes

This page was built for publication: Conditional empirical processes defined by nonstationary absolutely regular sequences