Subsample Goal Model for Multihalver on Outliers
Problem statement: In this study, a delete-half jackknife problem reformulated as a subsample multihalver was presented. Approach: In this respect, exploiting outlier nomination and estimation, since considering all possible half-sample is unpractical and unfeasible were considered. Results: We derived subsample algorithm which is unbiased multihalver and the performance of the model in formulating the subsample multihalver was shown. Conclusion: The result of subsample multihalver method of nomination and estimation is better way of resolving large population.
Copyright: © 2010 B. Onoghojobi. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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- Subsample multihalver
- unbiased multihalver
- outlier nomination