The bivariate normal distribution function is approximated with emphasis on situations where the correlation coefficient is large. The high accuracy of the approximation is illustrated by numerical examples. Moreover, exact upper and lower bounds are presented as well as asymptotic results on the er
On testing the correlation coefficient of a bivariate normal distribution
β Scribed by M. N. Goria
- Publisher
- Springer
- Year
- 1980
- Tongue
- English
- Weight
- 247 KB
- Volume
- 27
- Category
- Article
- ISSN
- 0026-1335
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## Abstract In lifeβtesting situations under bivariate normality of (__X, U__), a few smallest or a few largest __Y__βobservations may not be available. Tests for ΞΌ = 0 (mean vector) and __o__ = 0 (correlation coefficient) are developed from the available __Y__βobservations and their concomitant __
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