A screening method for a nonparametric model
type: Item
instance of: scholarly article
title: A screening method for a nonparametric model
zbMATH Open document ID: 0609.62102
DOI: 10.1016/0167-7152(87)90032-0
author: Teresa Kowalczyk
author: Jan Mielniczuk
published in: Statistics \& Probability Letters
publication date: 1987-01-01T00:00:00Z
review text: Let (W,Z) be a two-dimensional r.v. such that W and Z are positively dependent in the sense that the function \(\Theta\) defined by \(\Theta (t,K)=P(W>K| Z=z)\) is a continuous, strictly increasing function of t for any \(K\in {\mathbb{R}}\). We consider estimation of the so-called screening threshold, whose definition is motivated by some discrimination problems, on the basis of a completely observable learning sample. The construction of the estimator utilises the order restrictions imposed on the model. Strong consistency of the proposed estimators is proved and their behaviour for moderate sample sizes is investigated via simulation.
Mathematics Subject Classification ID: 62H30
Mathematics Subject Classification ID: 62G05
zbMATH DE Number: 3986455
zbMATH Keywords: nonparametric positive dependence model
zbMATH Keywords: preference threshold
zbMATH Keywords: univariate gamma distribution
zbMATH Keywords: discrimination rule
zbMATH Keywords: isotonic regression
zbMATH Keywords: screening threshold
zbMATH Keywords: completely observable learning sample
zbMATH Keywords: Strong consistency
zbMATH Keywords: simulation
describes a project that uses: AS 149
MaRDI profile type: Publication
full work available at URL: 0167-7152(87)90032-0
OpenAlex ID: W1982247452
cites work: Q5658961
cites work: Algorithm AS 149: Amalgamation of Means in the Case of Simple Ordering
cites work: Classes of orderings of measures and related correlation inequalities. I. Multivariate totally positive distributions
cites work: Limit theorems for the ratio of the empirical distribution function to the true distribution function
description: scientific article; zbMATH DE number 3986455