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Minimax variance estimation of a correlation coefficient for ε-contaminated bivariate normal distributions

✍ Scribed by Georgy L. Shevlyakov; Nikita O. Vilchevski

Publisher
Elsevier Science
Year
2002
Tongue
English
Weight
115 KB
Volume
57
Category
Article
ISSN
0167-7152

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✦ Synopsis

A minimax variance (in the Huber sense) estimator of a correlation coe cient for -contaminated bivariate normal distributions is given by the trimmed correlation coe cient. Consistency and asymptotic normality of this estimator are established, and the explicit expression for its asymptotic variance is obtained. The limiting cases of this estimator are the sample correlation coe cient with =0 and the median correlation coe cient as → 1. In -contaminated normal models, the proposed trimmed correlation coe cient is superior in e ciency than the sample correlation coe cient.

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Maximum likelihood estimation of the correlation coefficient in a bivariate normal model with missing data
✍ Steven T. Garren 📂 Article 📅 1998 🏛 Elsevier Science 🌐 English ⚖ 396 KB

The maximum likelihood estimator (MLE) of the correlation coefficient and its asymptotic properties are well-known for bivariate normal data when no observations are missing. The situation in which one of the two variates is not observed in some of the data is examined herein. The MLE of the correla