Let M be an isotonic real-valued function on a compact subset of Rd and let M̂n be an unconstrained estimator of M. A feasible monotonizing technique is to take the largest (smallest) monotone function that lies below (above) the estimator M̂n or any convex combination of these two envelope estimators. When the process rn(M̂n−M) is asymptotically equicontinuous for some sequence rn> 0, we show that these projected estimators are rn-equivalent in probability to the original unrestricted estimator. Our first motivating application involves a monotone estimator of the conditional distribu-tion function that has the distributional properties of the local linear regression esti-mator. Applications also include the estimation of econometric (p...
The classes of monotone or convex (and necessarily monotone) densities on inline image can be viewed...
We study nonparametric isotonic confidence intervals for monotone functions. In [Ann. Statist. 29 (2...
The monotone rearrrangement algorithm was introduced by Hardy, Littlewood and Po ́lya as a sorting d...
In many problems, a sensible estimator of a possibly multivariate monotone function may fail to be m...
We consider the nonparametric regression problem with multiple predictors and an additive error, whe...
Thesis (Ph.D.)--University of Washington, 2018In this dissertation, we study general strategies for ...
Abstract. Suppose that a target function f0: Rd → R is monotonic, namely, weakly increasing, and an ...
Recently, Dette et al. [A simple nonparametric estimator of a strictly increasing regression functio...
The paper proposes two Bayesian approaches to non-parametric monotone function estimation. The first...
In a recent paper Dette, Neumeyer and Pilz (2005) proposed a new nonparametric estimate of a monoto...
In this thesis we address the problem of estimating a curve of interest (which might be a probabilit...
Suppose that a target function is monotonic and an available original estimate of this target functi...
Consider the problem of pointwise estimation of f in a multiple isotonic regression model Z = f(X1, ...
Pointwise limit distribution results are given for the isotonic regression estimator at a point of d...
This article introduces a new nonparametric method for estimating a univariate regression function o...
The classes of monotone or convex (and necessarily monotone) densities on inline image can be viewed...
We study nonparametric isotonic confidence intervals for monotone functions. In [Ann. Statist. 29 (2...
The monotone rearrrangement algorithm was introduced by Hardy, Littlewood and Po ́lya as a sorting d...
In many problems, a sensible estimator of a possibly multivariate monotone function may fail to be m...
We consider the nonparametric regression problem with multiple predictors and an additive error, whe...
Thesis (Ph.D.)--University of Washington, 2018In this dissertation, we study general strategies for ...
Abstract. Suppose that a target function f0: Rd → R is monotonic, namely, weakly increasing, and an ...
Recently, Dette et al. [A simple nonparametric estimator of a strictly increasing regression functio...
The paper proposes two Bayesian approaches to non-parametric monotone function estimation. The first...
In a recent paper Dette, Neumeyer and Pilz (2005) proposed a new nonparametric estimate of a monoto...
In this thesis we address the problem of estimating a curve of interest (which might be a probabilit...
Suppose that a target function is monotonic and an available original estimate of this target functi...
Consider the problem of pointwise estimation of f in a multiple isotonic regression model Z = f(X1, ...
Pointwise limit distribution results are given for the isotonic regression estimator at a point of d...
This article introduces a new nonparametric method for estimating a univariate regression function o...
The classes of monotone or convex (and necessarily monotone) densities on inline image can be viewed...
We study nonparametric isotonic confidence intervals for monotone functions. In [Ann. Statist. 29 (2...
The monotone rearrrangement algorithm was introduced by Hardy, Littlewood and Po ́lya as a sorting d...