The Annals of Statistics

Conditional Empirical Processes

Winfried Stute

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Abstract

We prove a Donsker-type invariance principle for a nearest-neighbor-type conditional empirical process. As an application we show asymptotic normality of conditional quantiles and derive large-sample distribution-free tests and confidence bands for a conditional distribution function.

Article information

Source
Ann. Statist., Volume 14, Number 2 (1986), 638-647.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176349943

Digital Object Identifier
doi:10.1214/aos/1176349943

Mathematical Reviews number (MathSciNet)
MR840519

Zentralblatt MATH identifier
0594.62038

JSTOR
links.jstor.org

Subjects
Primary: 60F17: Functional limit theorems; invariance principles
Secondary: 62J02: General nonlinear regression 62G05: Estimation 62G10: Hypothesis testing 62G15: Tolerance and confidence regions

Keywords
Conditional empirical distribution function invariance principle conditional quantiles

Citation

Stute, Winfried. Conditional Empirical Processes. Ann. Statist. 14 (1986), no. 2, 638--647. doi:10.1214/aos/1176349943. https://projecteuclid.org/euclid.aos/1176349943


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