Nonparametric estimation of a multiple order conditional within-subject covariance function for a continuous times univariate stochastic process

Asymptotic Properties of Longitudinal Weighted Averages for Strongly Mixing Data

“…His results are obtained for independent data with arguments that the data were formed by weighted averages of longitudinal or functional data. Soro & Hili (Soro & Hili, 2012) extended the results of Yao (Yao, 2007) for a continuous univariate stochastic process.…”

“…= k 1 !k 2 !k 3 !. As most kernel-based nonparametric estimators can be written as function of averages, then we consider averages (introduced in Soro & Hili (2012)) of the form:…”

“…Our results can be applied to within-subject covariance function introduced by Soro & Hili (Soro & Hili, 2012) with mixing arguments.…”

“…The main purpose of this article is to extend the results of Soro & Hili (Soro & Hili, 2012) to α-mixing longitudinal data. Our results can be applied to within-subject covariance function introduced by Soro & Hili (Soro & Hili, 2012) with mixing arguments.…”

“…The case of independent and identically distributed observations using kernel-based estimation has received considerable attention in recent years with contribution (Hart & Wehrly, 1986;Lin & Caroll, 2000;Yao, 2007;Hall, et al, 2008;Degras, 2008;Soro & Hili, 2012).…”