Article contents
U-Processes in the Analysis of a Generalized Semiparametric Regression Estimator
Published online by Cambridge University Press: 11 February 2009
Abstract
We prove -consistency
and asymptotic normality of a generalized
semiparametric regression estimator that includes as
special cases Ichimura's semiparametric
least-squares estimator for single index models, and
the estimator of Klein and Spady for the binary
choice regression model. Two function expansions
reveal a type of U-process structure in the
criterion function; then new U-process maximal
inequalities are applied to establish the requisite
stochastic equicontinuity condition. This method of
proof avoids much of the technical detail required
by more traditional methods of analysis. The general
framework suggests other
-consistent
and asymptotically normal estimators.
- Type
- Research Article
- Information
- Copyright
- Copyright © Cambridge University Press 1994
References
- 49
- Cited by