Improved power of one-sided tests
For the classical least-squares model it is often the case that shape or order restrictions are appropriate for the regression function, in the form of a set of linear inequality constraints imposed on the parameters. It is generally understood that the hypothesis test using the constrained alternative will provide higher power than the corresponding test using the unconstrained alternative. We present a formal proof that this is the case. Code for constrained estimation and testing is posted at www.stat.colostate.edu/~meyer/constrparam.htm.
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): 82 (2012)
Issue (Month): 8 ()
|Contact details of provider:|| Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description|
|Order Information:|| Postal: http://www.elsevier.com/wps/find/supportfaq.cws_home/regional|
When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:82:y:2012:i:8:p:1619-1622. 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: (Zhang, Lei)
If references are entirely missing, you can add them using this form.