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June, 1987 Monte Carlo Evidence on Adaptive Maximum Likelihood Estimation of a Regression
David A. Hsieh, Charles F. Manski
Ann. Statist. 15(2): 541-551 (June, 1987). DOI: 10.1214/aos/1176350359

Abstract

This paper reports Monte Carlo evidence on the fixed sample size properties of adaptive maximum likelihood estimates of a linear regression. The focus is on the problem of selecting the smoothing and trimming parameters used in estimating the score function. We examine the performance of adaptive maximum likelihood estimators when these parameters are preselected or, alternatively, are determined by a data-based bootstrap method.

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David A. Hsieh. Charles F. Manski. "Monte Carlo Evidence on Adaptive Maximum Likelihood Estimation of a Regression." Ann. Statist. 15 (2) 541 - 551, June, 1987. https://doi.org/10.1214/aos/1176350359

Information

Published: June, 1987
First available in Project Euclid: 12 April 2007

zbMATH: 0621.62034
MathSciNet: MR888424
Digital Object Identifier: 10.1214/aos/1176350359

Subjects:
Primary: 62E25
Secondary: 62F11, 62F35, 62J05

Rights: Copyright © 1987 Institute of Mathematical Statistics

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Vol.15 • No. 2 • June, 1987
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