The smooth colonel meets the reverend
Kernel smoothing techniques have attracted much attention and some notoriety in recent years. The attention is well deserved as kernel methods free researchers from having to impose rigid parametric structure on their data. The notoriety arises from the fact that the amount of smoothing (i.e., local averaging) that is appropriate for the problem at hand is under the control of the researcher. In this paper we provide a deeper understanding of kernel smoothing methods for discrete data by leveraging the unexplored links between hierarchical Bayesmodels and kernelmethods for discrete processes. A number of potentially useful results are thereby obtained, including bounds on when kernel smoothing can be expected to dominate non-smooth (e.g., parametric) approaches in mean squared error and suggestions for thinking about the appropriate amount of smoothing.
Year of publication: |
2008
|
---|---|
Authors: | Kiefer, Nicholas M. ; Racine, Jeffrey S. |
Publisher: |
Ithaca, NY : Cornell University, Center for Analytical Economics (CAE) |
Saved in:
freely available
Series: | CAE Working Paper ; 08-01 |
---|---|
Type of publication: | Book / Working Paper |
Type of publication (narrower categories): | Working Paper |
Language: | English |
Other identifiers: | 571823785 [GVK] hdl:10419/70459 [Handle] |
Source: |
Persistent link: https://www.econbiz.de/10010292076
Saved in favorites
Similar items by person
-
The smooth colonel meets the reverend
Kiefer, Nicholas Maximilian, (2008)
-
The smooth colonel and the reverend find common ground
Kiefer, Nicholas M., (2013)
-
The smooth colonel and the reverend find common ground
Kiefer, Nicholas Maximilian, (2017)
- More ...