| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1150192 | Journal of Statistical Planning and Inference | 2007 | 10 Pages |
Abstract
An alternative to full nested evaluation is to perform a random sample of evaluations and use statistical methods to perform inference about the entire tree. We show that the most natural estimate is biased and consider two alternatives: the parametric bootstrap and hierarchical Bayes inference. We explore the properties of these inferences through a simulation study.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Erwann Rogard, Andrew Gelman, Hao Lu,