✦ LIBER ✦

Empirical Likelihood Confidence Intervals for Linear Regression Coefficients

✍ Scribed by S.X. Chen

Publisher: Elsevier Science
Year: 1994
Tongue: English
Weight: 527 KB
Volume: 49
Category: Article
ISSN: 0047-259X
DOI: 10.1006/jmva.1994.1011

No coin nor oath required. For personal study only.

✦ Synopsis

Nonparametric versions of Wilks' theorem are proved for empirical likelihood estimators of slope and mean parameters for a simple linear regression model. They enable us to construct empirical likelihood confidence intervals for these parameters. The coverage errors of these confidence intervals are of order (n^{-1}) and can be reduced to order (n^{-2}) by Bartlett correction. 1 1994 Academic Press. Inc.

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