Bootstrap Testing in Nonlinear Models
When a model is nonlinear, boostrap testing can be expensive because of the need to perform at least one nonlinear estimation for every bootstrap sample. We show that it may be possible to reduce computational costs by performing only a fixed, small number of Newton steps or artificial regressions for each bootstrap sample.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
|Date of creation:||1997|
|Contact details of provider:|| Postal: G.R.E.Q.A.M., (GROUPE DE RECHERCHE EN ECONOMIE QUANTITATIVE D'AIX MARSEILLE), CENTRE DE VIEILLE CHARITE, 2 RUE DE LA CHARITE, 13002 MARSEILLE.|
Web page: http://www.greqam.fr/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:fth:aixmeq:97a39. 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: (Thomas Krichel)
If references are entirely missing, you can add them using this form.