Prediction Error of Small Area Predictors Shrinking Both Means and Variances
Tapabrata Maiti,
Hao Ren and
Samiran Sinha
Scandinavian Journal of Statistics, 2014, vol. 41, issue 3, 775-790
Abstract:
type="main" xml:id="sjos12061-abs-0001"> The article considers a new approach for small area estimation based on a joint modelling of mean and variances. Model parameters are estimated via expectation–maximization algorithm. The conditional mean squared error is used to evaluate the prediction error. Analytical expressions are obtained for the conditional mean squared error and its estimator. Our approximations are second-order correct, an unwritten standardization in the small area literature. Simulation studies indicate that the proposed method outperforms the existing methods in terms of prediction errors and their estimated values.
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)
Downloads: (external link)
http://hdl.handle.net/10.1111/sjos.12061 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:scjsta:v:41:y:2014:i:3:p:775-790
Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0303-6898
Access Statistics for this article
Scandinavian Journal of Statistics is currently edited by ÿrnulf Borgan and Bo Lindqvist
More articles in Scandinavian Journal of Statistics from Danish Society for Theoretical Statistics, Finnish Statistical Society, Norwegian Statistical Association, Swedish Statistical Association
Bibliographic data for series maintained by Wiley Content Delivery ().