Standard
On the computation of R-estimators. /
Mukherjee, Kanchan; Wang, Yuankun.
Contemporary developments in statistical theory : a festschrift for Hira Lal Koul. ed. / Soumendra Lahiri; Anton Schick; Ashis SenGupta; T. N. Sriram. Switzerland: Springer, 2014. p. 279-288 (Springer Proceedings in Mathematics & Statistics ; Vol. 68).
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter (peer-reviewed) › peer-review
Harvard
Mukherjee, K & Wang, Y 2014,
On the computation of R-estimators. in S Lahiri, A Schick, A SenGupta & TN Sriram (eds),
Contemporary developments in statistical theory : a festschrift for Hira Lal Koul. Springer Proceedings in Mathematics & Statistics , vol. 68, Springer, Switzerland, pp. 279-288.
https://doi.org/10.1007/978-3-319-02651-0_17
APA
Vancouver
Mukherjee K, Wang Y.
On the computation of R-estimators. In Lahiri S, Schick A, SenGupta A, Sriram TN, editors, Contemporary developments in statistical theory : a festschrift for Hira Lal Koul. Switzerland: Springer. 2014. p. 279-288. (Springer Proceedings in Mathematics & Statistics ). doi: 10.1007/978-3-319-02651-0_17
Author
Mukherjee, Kanchan ; Wang, Yuankun. /
On the computation of R-estimators. Contemporary developments in statistical theory : a festschrift for Hira Lal Koul. editor / Soumendra Lahiri ; Anton Schick ; Ashis SenGupta ; T. N. Sriram. Switzerland : Springer, 2014. pp. 279-288 (Springer Proceedings in Mathematics & Statistics ).
Bibtex
@inbook{70f5248400354ff3b4a0cc19999edc11,
title = "On the computation of R-estimators",
abstract = "In this paper, we propose a simple iterative algorithm for computing R-estimates of the parameters of the linear regression models. The algorithm can be applied routinely to compute R-estimates based on any score function. We apply this to some well-known datasets and can identify outliers which would not have been detected using least squares.",
keywords = "Rank estimators, linear model",
author = "Kanchan Mukherjee and Yuankun Wang",
year = "2014",
doi = "10.1007/978-3-319-02651-0_17",
language = "English",
isbn = "9783319026503",
series = "Springer Proceedings in Mathematics & Statistics ",
publisher = "Springer",
pages = "279--288",
editor = "Soumendra Lahiri and Anton Schick and Ashis SenGupta and Sriram, {T. N. }",
booktitle = "Contemporary developments in statistical theory",
}
RIS
TY - CHAP
T1 - On the computation of R-estimators
AU - Mukherjee, Kanchan
AU - Wang, Yuankun
PY - 2014
Y1 - 2014
N2 - In this paper, we propose a simple iterative algorithm for computing R-estimates of the parameters of the linear regression models. The algorithm can be applied routinely to compute R-estimates based on any score function. We apply this to some well-known datasets and can identify outliers which would not have been detected using least squares.
AB - In this paper, we propose a simple iterative algorithm for computing R-estimates of the parameters of the linear regression models. The algorithm can be applied routinely to compute R-estimates based on any score function. We apply this to some well-known datasets and can identify outliers which would not have been detected using least squares.
KW - Rank estimators
KW - linear model
U2 - 10.1007/978-3-319-02651-0_17
DO - 10.1007/978-3-319-02651-0_17
M3 - Chapter (peer-reviewed)
SN - 9783319026503
T3 - Springer Proceedings in Mathematics & Statistics
SP - 279
EP - 288
BT - Contemporary developments in statistical theory
A2 - Lahiri, Soumendra
A2 - Schick, Anton
A2 - SenGupta, Ashis
A2 - Sriram, T. N.
PB - Springer
CY - Switzerland
ER -
