The Annals of Statistics

Monotone Nonparametric Regression

Hari Mukerjee

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Abstract

In monotone regression procedures one utilizes only the monotonicity of the regression function. In nonparametric regression one utilizes only the assumed smoothness. The analytic and asymptotic properties of the estimator are superior in the latter case; however, monotonicity is not guaranteed. We study a hybrid procedure that produces monotone estimators with properties similar to those of nonparametric regression estimators.

Article information

Source
Ann. Statist., Volume 16, Number 2 (1988), 741-750.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176350832

Digital Object Identifier
doi:10.1214/aos/1176350832

Mathematical Reviews number (MathSciNet)
MR947574

Zentralblatt MATH identifier
0647.62042

JSTOR
links.jstor.org

Subjects
Primary: 62G05: Estimation
Secondary: 60F05: Central limit and other weak theorems 60F15: Strong theorems

Keywords
Isotonic regression nonparametric regression uniform strong consistency asymptotic normality

Citation

Mukerjee, Hari. Monotone Nonparametric Regression. Ann. Statist. 16 (1988), no. 2, 741--750. doi:10.1214/aos/1176350832. https://projecteuclid.org/euclid.aos/1176350832


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