Minimum distance estimation of the distribution functions of stochastically ordered random variables
Stochastic ordering of distributions can be a natural and minimal restriction in an estimation problem. Such restrictions occur naturally in several settings in medical research. The standard estimator in such settings is the nonparametric maximum likelihood estimator (NPMLE). The NPMLE is known to be biased, and, even when the empirical cumulative distribution functions nearly satisfy the stochastic orderings, the NPMLE and the empirical cumulative distribution functions may differ substantially. In many settings, this can make the NPMLE seem to be an unappealing estimator. As an alternative to the NPMLE, we propose a minimum distance estimator of distribution functions subject to stochastic ordering constraints. Consistency of the minimum distance estimator is proved, and superior performance is demonstrated through a simulation study. We demonstrate the use of the methodology to assess the reproducibility of gradings of nuclear sclerosis from fundus photographs. Copyright 2002 Royal Statistical Society.
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): 51 (2002)
Issue (Month): 4 ()
|Contact details of provider:|| Postal: |
Web page: http://wileyonlinelibrary.com/journal/rsscEmail:
More information through EDIRC
|Order Information:||Web: http://ordering.onlinelibrary.wiley.com/subs.asp?ref=1467-9876&doi=10.1111/(ISSN)1467-9876|
When requesting a correction, please mention this item's handle: RePEc:bla:jorssc:v:51:y:2002:i:4:p:485-492. 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: (Wiley-Blackwell Digital Licensing)or (Christopher F. Baum)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.