Benchmarked estimates in small areas using linear mixed models with restrictions
No abstract is available for this item.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 18 (2009)
Issue (Month): 2 (August)
|Contact details of provider:|| Web page: http://www.springerlink.com/link.asp?id=120411|
|Order Information:||Web: http://link.springer.de/orders.htm|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Peter Hall & Tapabrata Maiti, 2006. "On parametric bootstrap methods for small area prediction," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(2), pages 221-238.
- Jiming Jiang & P. Lahiri, 2006. "Mixed model prediction and small area estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 15(1), pages 1-96, June.
- A. F. Militino & M. D. Ugarte & T. Goicoa, 2007. "A BLUP Synthetic Versus an EBLUP Estimator: An Empirical Study of a Small Area Estimation Problem," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(2), pages 153-165.
When requesting a correction, please mention this item's handle: RePEc:spr:testjl:v:18:y:2009:i:2:p:342-364. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla)or (Christopher F Baum)
If references are entirely missing, you can add them using this form.