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https://hdl.handle.net/20.500.14279/1277| Title: | Minimum distance regression-type estimates with rates under weak dependence |
| Authors: | Roussas, George G. Yatracos, Yannis G. Roussas, George G. |
| Major Field of Science: | Natural Sciences |
| Keywords: | Regression analysis;Entropy;Estimation |
| Issue Date: | 1996 |
| Source: | Annals of the Institute of Statistical Mathematics, 1996, vol. 48, no. 2, pp. 267-281 |
| Volume: | 48 |
| Issue: | 2 |
| Start page: | 267 |
| End page: | 281 |
| Journal: | Annals of the Institute of Statistical Mathematics |
| Abstract: | Under weak dependence, a minimum distance estimate is obtained for a smooth function and its derivatives in a regression-type framework. The upper bound of the risk depends on the Kolmogorov entropy of the underlying space and the mixing coefficient. It is shown that the proposed estimates have the same rate of convergence, in the L 1-norm sense, as in the independent case. |
| URI: | https://hdl.handle.net/20.500.14279/1277 |
| ISSN: | 15729052 |
| DOI: | 10.1007/BF00054790 |
| Rights: | © Springer Nature |
| Type: | Article |
| Affiliation : | University of California Université de Montréal |
| Appears in Collections: | Άρθρα/Articles |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 10.1007_BF00054790.pdf | 660.92 kB | Adobe PDF | View/Open |
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