Furrer, R (2002). M-estimation for dependent random variables. Statistics and Probability Letters, 57(4):337-341.
This paper discusses the consistency in the strong sense and essential uniqueness of M-estimation for dependent random variables. The hypotheses are based on the function defining implicitly the M-estimation as well as on its first derivative and its Hessian matrix. No explicit hypotheses on the random variables are necessary for consistency and uniqueness, thus the framework holds for any stochastic process.
This paper discusses the consistency in the strong sense and essential uniqueness of M-estimation for dependent random variables. The hypotheses are based on the function defining implicitly the M-estimation as well as on its first derivative and its Hessian matrix. No explicit hypotheses on the random variables are necessary for consistency and uniqueness, thus the framework holds for any stochastic process.
| Item Type: | Journal Article, refereed, original work |
|---|---|
| Communities & Collections: | 07 Faculty of Science > Institute of Mathematics |
| Dewey Decimal Classification: | 510 Mathematics |
| Scopus Subject Areas: | Physical Sciences > Statistics and Probability
Social Sciences & Humanities > Statistics, Probability and Uncertainty |
| Language: | English |
| Date: | May 2002 |
| Deposited On: | 27 Aug 2010 12:07 |
| Last Modified: | 23 Jan 2022 14:39 |
| Publisher: | Elsevier |
| ISSN: | 0167-7152 |
| OA Status: | Closed |
| Publisher DOI: | https://doi.org/10.1016/S0167-7152(02)00084-6 |
Furrer, R