The Annals of Statistics

Monotone Regression Estimates for Grouped Observations

F. T. Wright

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Abstract

The maximum likelihood estimator of a nondecreasing regression function with normally distributed errors has been considered in the literature. Its asymptotic distribution at a point is related to a solution of the heat equation, and its rate of convergence to the underlying regression function is of order $n^{-1/3}$. This estimator can be modified by grouping adjacent observations and then "isotonizing" the corresponding means. It is shown that the resulting estimator has an asymptotic normal distribution for certain group sizes and its rate of convergence is of order $n^{-2/5}$. The results of a simulation study for small sample sizes are presented and grouping procedures are discussed.

Article information

Source
Ann. Statist., Volume 10, Number 1 (1982), 278-286.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176345710

Digital Object Identifier
doi:10.1214/aos/1176345710

Mathematical Reviews number (MathSciNet)
MR642739

Zentralblatt MATH identifier
0494.62031

JSTOR
links.jstor.org

Subjects
Primary: 62F10: Point estimation
Secondary: 62E20: Asymptotic distribution theory

Keywords
Isotone regression grouped observations interpolation asymptotic distribution and rates of convergence

Citation

Wright, F. T. Monotone Regression Estimates for Grouped Observations. Ann. Statist. 10 (1982), no. 1, 278--286. doi:10.1214/aos/1176345710. https://projecteuclid.org/euclid.aos/1176345710


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