On the construction of efficient estimators in semiparametric models
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Jeffrey S. Forrester
, William J. Hooper , Hanxiang Peng und Anton Schick
Summary
This paper deals with the construction of efficient estimators in semiparametric models without the sample splitting technique. Schick (1987) gave sufficient conditions using the leave-one-out technique for a construction without sample splitting. His conditions are stronger and more cumbersome to verify than the necessary and sufficient conditions for the existence of efficient estimators which suffice for the construction based on sample splitting. In this paper we use a conditioning argument to weaken Schick′s conditions. We shall then show that in a large class of semiparametric models and for properly chosen estimators of the score function the resulting weaker conditions reduce to the minimal conditions for the construction with sample splitting. In other words, in these models efficient estimators can be constructed without sample splitting under the same conditions as those used for the construction with sample splitting. We demonstrate our results by constructing an efficient estimator using these ideas in a semiparametric additive regression model.
© 2003 Oldenbourg Wissenschaftsverlag GmbH
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Artikel in diesem Heft
- On arbitrage and replication in the fractional Black–Scholes pricing model
- On the construction of efficient estimators in semiparametric models
- The Bahadur risk in probability density estimation
- On preferences of general two-sided tests with applications to Kolmogorov–Smirnov-type tests
- Estimating the dimension of factors of diffusion processes
- Ranking of populations in parameter′s modulus