## Abstract The estimation of any biserial correlation coefficient is biased if noiseβlike processes are overlaid. We've carried out a computer simulation to study this effect. The effect can be described in a universal way. Additionally, we've varied the type of distribution within the simulation
On the Performance of the SPRT for Correlation Coefficient: Normal and Mixtures of Normal Populations
β Scribed by K. Kocherlakota; N. Balakrishnan; Prof. S. Kocherlakota
- Publisher
- John Wiley and Sons
- Year
- 1986
- Tongue
- English
- Weight
- 559 KB
- Volume
- 28
- Category
- Article
- ISSN
- 0323-3847
No coin nor oath required. For personal study only.
β¦ Synopsis
The sequential probability ratio test (SPRT) for the correlation coefficient is exaniined in the normal and non-normal situations. I n the latter case, we evaluate the robustness of the normal procedure when sampling from the mixtures of normal distributions. Two models are introduced for this type of nonnormality.It is shown that in the case of moderate nonnormality, the normal procedure is robust while for extreme nonnormality, the normal procedure is not recommended.
π SIMILAR VOLUMES
For a scale mixture of normal vector, X=A 1Γ2 G, where X, G # R n and A is a positive variable, independent of the normal vector G, we obtain that the conditional variance covariance, Cov(X 2 | X 1 ), is always finite a.s. for m 2, where X 1 # R n and m<n, and remains a.s. finite even for m=1, if an