Robust and Asymptotically Efficient Estimation of Location in a Stationary Strong Mixing Gaussian Parametric Model
AbstractThis paper considers the problem of robust estimation of location in a model with stationary strong mixing Gaussian parametric distributions. An estimator is found that is within epsilon of being asymptotically efficient at the Gaussian parametric distribution and is within epsilon of being optimally robust! For the robustness results a Huber-type minimax criterion is used, where minimaxing takes place over neighborhoods of the parametric Gaussian distributions. The neighborhood system considered includes distributions of strong mixing processes and allows for deviations from the normal univariate parametric distributions within a Hellinger metric neighborhood, as well as deviations from stationarity and from the Gaussian structure of independence.
Download InfoIf 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.
Bibliographic InfoPaper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 659.
Length: 66 pages
Date of creation: Nov 1982
Date of revision:
Publication status: Published in Advances in Econometrics, Vol. 7, JAI Press, 1988, pp. 3-44
Note: CFP 725.
Contact details of provider:
Postal: Yale University, Box 208281, New Haven, CT 06520-8281 USA
Phone: (203) 432-3702
Fax: (203) 432-6167
Web page: http://cowles.econ.yale.edu/
More information through EDIRC
Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Andrews, Donald W K, 1986. "Stability Comparisons of Estimators," Econometrica, Econometric Society, vol. 54(5), pages 1207-35, September.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Glena Ames).
If references are entirely missing, you can add them using this form.