Abstract
We discuss a new method of estimation of parameters in semiparametric and nonparametric models. The method is based on U-statistics constructed from quadratic influence functions. The latter extend ordinary linear influence functions of the parameter of interest as defined in semiparametric theory, and represent second order derivatives of this parameter. For parameters for which the matching cannot be perfect the method leads to a bias-variance trade-off, and results in estimators that converge at a slower than n
| Original language | English |
|---|---|
| Pages (from-to) | 227-247 |
| Journal | Metrika |
| Volume | 69 |
| DOIs | |
| Publication status | Published - 2009 |
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