Some information inequalities for statistical inference
| Autor: | K. V. Harsha, Alladi Subramanyam |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Statistics and Probability
Discrete mathematics Inequality Information inequality media_common.quotation_subject 05 social sciences Probability density function 01 natural sciences Upper and lower bounds 010104 statistics & probability 0502 economics and business Statistical inference Bhattacharyya distance Point (geometry) 0101 mathematics 050205 econometrics media_common Mathematics |
| Zdroj: | Annals of the Institute of Statistical Mathematics. 72:1237-1256 |
| ISSN: | 1572-9052 0020-3157 |
| DOI: | 10.1007/s10463-019-00725-3 |
| Popis: | In this paper, we first describe the generalized notion of Cramer–Rao lower bound obtained by Naudts (J Inequal Pure Appl Math 5(4), Article 102, 2004) using two families of probability density functions: the original model and an escort model. We reinterpret the results in Naudts (2004) from a statistical point of view and obtain some interesting examples in which this bound is attained. Further, we obtain information inequalities which generalize the classical Bhattacharyya bounds in both regular and non-regular cases. |
| Databáze: | OpenAIRE |
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