Least squares estimators of the mode of a unimodal regression function

Jyh Ming Shoung; Cun Hui Zhang

doi:10.1214/aos/1009210684

Least squares estimators of the mode of a unimodal regression function

Jyh Ming Shoung, Cun Hui Zhang

School of Arts and Sciences, Statistics

Research output: Contribution to journal › Article › peer-review

20 Scopus citations

Abstract

In this paper, we consider nonparametric least squares estimators of the mode of an unknown unimodal regression function. We establish almost sure convergence of these estimators with nearly optimal convergence rates, under the assumption of the exponential tail for the error distributions.

Original language	English (US)
Pages (from-to)	648-665
Number of pages	18
Journal	Annals of Statistics
Volume	29
Issue number	3
DOIs	https://doi.org/10.1214/aos/1009210684
State	Published - Jun 2001

All Science Journal Classification (ASJC) codes

Statistics and Probability
Statistics, Probability and Uncertainty

Keywords

Convergence rate
Least squares estimation
Mode
Nonparametric regression

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10.1214/aos/1009210684

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title = "Least squares estimators of the mode of a unimodal regression function",

abstract = "In this paper, we consider nonparametric least squares estimators of the mode of an unknown unimodal regression function. We establish almost sure convergence of these estimators with nearly optimal convergence rates, under the assumption of the exponential tail for the error distributions.",

keywords = "Convergence rate, Least squares estimation, Mode, Nonparametric regression",

author = "Shoung, {Jyh Ming} and Zhang, {Cun Hui}",

year = "2001",

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KW - Convergence rate

KW - Least squares estimation

KW - Mode

KW - Nonparametric regression

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JO - Annals of Statistics

JF - Annals of Statistics

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Least squares estimators of the mode of a unimodal regression function

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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