| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1151523 | Statistics & Probability Letters | 2016 | 8 Pages |
Abstract
A class of nonparametric methods is developed to estimate a set of possibly similar densities that offers greater efficiency if they are similar while seemingly not losing any if they are not. Theoretical properties and finite sample performance are promising.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Alan P. Ker,