Compound decision in the presence of proxies with an application to spatio-temporal data
Statistics Theory
2010-12-08 v1 Methodology
Statistics Theory
Abstract
We study the problem of incorporating covariates in a compound decision setup. It is desired to estimate the means of response variables, which are independent and normally distributed, and each is accompanied by a vector of covariates. We suggest a method that involves non-parametric empirical Bayes techniques and may be viewed as a generalization of the celebrated Fay-Herriot (1979) method. Some optimality properties of our method are proved. We also compare it numerically with Fay-Herriot and other methods, using a `semi-real' data set that involves spatio-temporal covariates, where the goal is to estimate certain proportions in many small areas (Statistical-Areas)
Keywords
Cite
@article{arxiv.1012.1563,
title = {Compound decision in the presence of proxies with an application to spatio-temporal data},
author = {N. Cohen and E. Greenshtein and Y. Ritov},
journal= {arXiv preprint arXiv:1012.1563},
year = {2010}
}