Kuljus, Kristi
- Department of Forest Economics, Swedish University of Agricultural Sciences
Research article2013Peer reviewed
Asymptotic properties of a rank estimate in linear regression with symmetric non-identically distributed errors
Kuljus, Kristi; Zwanzig, Silvelyn
Abstract
In this article, a simple linear regression model with independent and symmetric but non-identically distributed errors is considered. Asymptotic properties of the rank regression estimate defined in Jaeckel [Estimating regression coefficients by minimizing the dispersion of the residuals, Ann. Math. Statist. 43 (1972), pp. 1449-1458] are studied. We show that the studied estimator is consistent and asymptotically normally distributed. The cases of bounded and unbounded score functions are examined separately. The regularity conditions of the article are exemplified for finite mixture distributions.
Keywords
rank regression; symmetric heteroscedastic errors; linear rank statistics; consistency; asymptotic normality; bounded score functions; unbounded score functions
Published in
Statistics
2013, volume: 47, number: 6, pages: 1160-1183
Publisher: TAYLOR & FRANCIS LTD
SLU Authors
UKÄ Subject classification
Probability Theory and Statistics
Publication identifier
- DOI: https://doi.org/10.1080/02331888.2012.688206
Permanent link to this page (URI)
https://res.slu.se/id/publ/56110