Nonparametric density estimation in presence of bias and censoring
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): 1 (May)
|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.:
- Asgharian M. & MLan C.E. & Wolfson D. B., 2002. "Length-Biased Sampling With Right Censoring: An Unconditional Approach," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 201-209, March.
- Colin Wu & Andrew Mao, 1996. "Minimax kernels for density estimation with biased data," Annals of the Institute of Statistical Mathematics, Springer, vol. 48(3), pages 451-467, September.
- A. Antoniadis & G. Grégoire & G. Nason, 1999. "Density and hazard rate estimation for right-censored data by using wavelet methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(1), pages 63-84.
When requesting a correction, please mention this item's handle: RePEc:spr:testjl:v:18:y:2009:i:1:p:166-194. 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: (Guenther Eichhorn)or (Christopher F Baum)
If references are entirely missing, you can add them using this form.