On the Studentisation of Random Vectors
We give general matrix Studentisation results for random vectors converging in distribution to a spherically symmetric random vector, which have wide applicability to the asymptotic properties of estimators obtained from estimating equations, for example. Appropriate matrix "square roots," required for normalisation of the random vectors, are shown to be the Cholesky square root and the symmetric positive definite square root.
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): 57 (1996)
Issue (Month): 1 (April)
|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:jmvana:v:57:y:1996:i:1:p:142-155. 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: (Shamier, Wendy)
If references are entirely missing, you can add them using this form.