Information bounds for nonparametric estimators of L-functionals and survival functionals under censored data
| Autor: | Andreas Knoch, Arnold Janssen |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Statistics and Probability
05 social sciences Nonparametric statistics Estimator 01 natural sciences L-estimator Upper and lower bounds 010104 statistics & probability Nelson–Aalen estimator 0502 economics and business Statistics Applied mathematics Differentiable function 0101 mathematics Statistics Probability and Uncertainty Cramér–Rao bound Kaplan–Meier estimator 050205 econometrics Mathematics |
| Zdroj: | Metrika. 79:195-220 |
| ISSN: | 1435-926X 0026-1335 |
| Popis: | In the present paper we derive lower asymptotic information bounds of Cramer-Rao type for estimators of nonparametric statistical functionals. The results are based on dense differentiability and dense regularity concepts which lead to weak assumptions. As explicit examples L-estimators are treated. In addition a new rapid method for the treatment of survival functionals under randomly right censored data is presented. For instance, for the famous Kaplan-Meier and Nelson-Aalen estimators, our information bound is just the lower bound obtained earlier in the literature. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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