Number of the records: 1

Nonparametric Estimation of Regression Parameters in Measurement Error Models

SYSNO ASEP	0348875
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Článek ve SCOPUS
Title	Nonparametric Estimation of Regression Parameters in Measurement Error Models
Author(s)	Ehsanes Saleh, A.K.M.D. (CA) Picek, J. (CZ) Kalina, Jan (UIVT-O)_{RID, SAI, ORCID}
Source Title	Metron. - : Springer - ISSN 0026-1424 Roč. 67, č. 2 (2009), s. 177-200
Number of pages	24 s.
Language	eng - English
Country	IT - Italy
Keywords	asymptotic relative efficiency(ARE) ; asymptotic theory ; emaculate mode ; Me model ; R-estimation ; Reliabilty ratio(RR)
Subject RIV	BB - Applied Statistics, Operational Research
CEZ	AV0Z10300504 - UIVT-O (2005-2011)
EID SCOPUS	77951170971
Annotation	This paper develops the theory of rank estimation for the regression parameters in measurement error models. Using the standard linear rank statistics, R-estimators are defined and their asymptotic properties are studied as robust alternatives to least squares estimators. This paper fills the gap of rank theory in the estimation of parameters of measurement error models. Some simulation results are presented to show the effectiveness of the R-estimators.
Workplace	Institute of Computer Science
Contact	Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
Year of Publishing	2011

Number of the records: 1