In this paper we consider the estimation of optimal state-action value function Q⁎ with ReLU
ResNet based on minimax Bellman error minimization. We construct the non-asymptotic …

In this paper, we provide statistical guarantees for over-parameterized deep nonparametric
regression in the presence of dependent data. By decomposing the error, we establish …

In this paper, we construct a nonparametric M-estimator of a regression function for a left
truncated model when the data exhibit some kind of dependence. It is assumed that the …

By applying local polynomial regression, we propose an estimator of a conditional mean
function and its derivatives under a left truncation model. The target function includes the …

On the basis of the idea of the Nadaraya–Watson (NW) kernel smoother and the technique
of the local linear (LL) smoother, we construct the NW and LL estimators of conditional mean …

In this paper, we define a new nonlinear wavelet-based estimator of the regression function
under random left-truncation. We provide an asymptotic expression for the mean integrated …

In this article we establish pointwise asymptotic normality of nonparametric kernel estimator
of regression function for a left truncation model. It is assumed that the lifetime observations …

In this paper, we consider the modified product-limit estimator of an unknown distribution
function proposed by Huang and Qin (2011), where the observations are subject to length …

The local polynomial quasi-likelihood estimation has several good statistical properties such
as high minimax efficiency and adaptation of edge effects. In this paper, we construct a local …

This paper studies the behaviour of the kernel estimator of the regression function for
associated data in the random left truncated model. The uniform strong consistency rate over …