Email this article Two-Step Estimation in a Heteroscedastic Linear Regression Model
- Authors: Linke Y.Y.1,2
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Affiliations:
- Sobolev Institute of Mathematics SB RAS
- Novosibirsk State University
- Issue: Vol 231, No 2 (2018)
- Pages: 206-217
- Section: Article
- URL: https://journal-vniispk.ru/1072-3374/article/view/241119
- DOI: https://doi.org/10.1007/s10958-018-3816-y
- ID: 241119
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Abstract
We study the problem of estimating a parameter in some heteroscedastic linear regression model in the case where the regressors consist of all order statistics based on the sample of identically distributed not necessarily independent observations with finite second moment. It is assumed that the random errors depend on the parameter and distributions of the corresponding regressors. We propose a two-step procedure for finding explicit asymptotically normal estimators.
About the authors
Yu. Yu. Linke
Sobolev Institute of Mathematics SB RAS; Novosibirsk State University
Author for correspondence.
Email: linke@math.nsc.ru
Russian Federation, 4, Akad. Koptyuga pr., Novosibirsk, 630090; 1, Pirogova St., Novosibirsk, 630090
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