Using Nonparametric Conditional M-Quantiles to Estimate a Cumulative Distribution Function in a Domain
Estimating the cumulative distribution function in survey sampling is of interest on the population but also on a sub-population (domain). However, in most practical applications, sample sizes in the domains are not large enough to produce sufficiently precise estimators. Therefore, we propose new nonparametric estimators of the cumulative distribution function in a domain based on M-quantile estimation. The obtained estimators are compared by simulations and applied to real data.
|Date of creation:||Dec 2009|
|Date of revision:|
|Publication status:||Published in Annales d'Économie et de Statistique, vol. 107-108, Institut national de la statistique et des études économiques, Paris, juillet/décembre 2012, p. 287-297.|
|Contact details of provider:|| Phone: (+33) 5 61 12 86 23|
Web page: http://www.tse-fr.eu/
More information through EDIRC
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.:
- Ray Chambers & Nikos Tzavidis, 2006. "M-quantile models for small area estimation," Biometrika, Biometrika Trust, vol. 93(2), pages 255-268, June.
When requesting a correction, please mention this item's handle: RePEc:tse:wpaper:22254. 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: ()
If references are entirely missing, you can add them using this form.