On sampling the degree-of-freedom of Student's-t disturbances
In a Bayesian analysis of a model with Student's-t disturbances developed by Geweke (J. Appl. Econom. 8 (1993) S19), and Fernández and Steel (J. Amer. Statist. Assoc. 93 (1998) 359), the degree-of-freedom of Student's-t disturbances, if unknown, must be sampled from its conditional distribution. This article presents a new method for this sampling using a Metropolis-Hastings acceptance-rejection algorithm proposed by Tierney (Ann. Statist. 21 (1994) 1701). The acceptance probabilities in both the acceptance-rejection and Metropolis-Hastings parts of this method are shown to exceed 95%.
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): 52 (2001)
Issue (Month): 2 (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:stapro:v:52:y:2001:i:2:p:177-181. 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.