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Asymptotic Properties for Methods Combining the Minimum Hellinger Distance Estimate and the Bayesian Nonparametric Density Estimate
In frequentist inference, minimizing the Hellinger distance between a kernel density estimate and a parametric family produces estimators that are both robust to outliers and statistically efficient when the parametric family contains the data-generating distribution. This paper seeks to extend thes...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2018
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512539/ https://www.ncbi.nlm.nih.gov/pubmed/33266679 http://dx.doi.org/10.3390/e20120955 |