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Details for article 21 of 26 found articles
| Title: |
Robust predictive distributions based on the penalized blended weight hellinger distance |
| Author: |
Park, Chanseok Harris, Ian R. Basu, Ayanendranath |
| Appeared in: |
Communications in statistics |
| Paging: | Volume 26 (1997) nr. 1 pages 21-33 |
| Year: |
1997 |
| Contents: |
Harris (Biometrika, 1989) suggests a predictive distribution based on bootstrapping using the maximum likelihood estimator of an unknown parameter. Basu and Harris (Biometrika, 1994) introduce robust estimative and bootstrap predictive distributions for discrete models by using the minimum Hellinger distance estimator of the unknown parameter instead of the maximum likelihood estimator. Generalizing the results of Basu and Harris, the present paper considers parametric predictive distributions using the minimum penalized blended weight Hellinger distance estimator for discrete models. Monte Carlo siniulations suggest that the proposed predictive distributions are attractive robust substitutes for the usual predictive distributions based on the maximum likelihood estimator under data contamination, and perform favorably compared to the predictive distributions suggested by Basu and Harris |
| Publisher: |
Taylor & Francis |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 21 of 26 found articles
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