Empirical Estimates in Optimization Problems: Survey with Special Regard to Heavy Tails and Dependent Sample
Economic processes are usually influenced simultaneously by a random factor and a decision parameter. Since the decision parameter has to be mostly determined before realization of the random element, deterministic optimization problems which depend on a probability measure often correspond to the above mentioned situations. A complete knowledge of the “underlying” measure would be a necessary assumption to determine both an exact optimal solution and an exact optimal value. Since this condition is not usually fulfilled, the solution is often determined on an empirical data base. Corresponding estimates can only be obtained using this approach. Many efforts have been made to investigate the above mentioned estimates. The consis- tency, convergence rate and an asymptotic distribution have been examined. This was mostly done under assumptions of linear dependence on the probability measure, distri- butions with “thin” tails and an assumption of independent data. The aim of this paper is to consider the cases in which these assumptions are rather relaxed. To this end we employ stability results based on the Wasserstein metric corresponding to L 1 norm and some results on mixing sequences.
Volume (Year): 19 (2012)
Issue (Month): 30 ()
|Contact details of provider:|| Web page: http://ces.utia.cas.czEmail: |
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:czx:journl:v:19:y:2012:i:30:id:201. 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: (Jozef Barunik)
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.