M-Estimation for Discrete Data. Asymptotic Distribution Theory and Implications.
NORTH CAROLINA UNIV AT CHAPEL HILL DEPT OF STATISTICS
Pagination or Media Count:
The asymptotic distribution of an M-estimator is studies when the underlying distribution is discrete. Asymptotic normality is shown to hold quite generally within the assumed parametric family. When the specification of the model is inexact, however, it is demonstrated that an M-estimator with a non-smooth score function, e.g. a Huber estimator, has a non-normal limiting distribution at certain distributions, resulting in unstable inference in the neighborhood of such distributions. Consequently, smooth score functions are proposed for discrete data. Keywords Robust estimation and Discrete parametric models. Author
- Numerical Mathematics