EconPapers    
Economics at your fingertips  
 

Estimating the slope in measurement error models--a different perspective

Ori Davidov

Statistics & Probability Letters, 2005, vol. 71, issue 3, 215-223

Abstract: Motivated by a statistical model for the structural line segment relationship developed for computer vision applications we derive an estimator for the slope of a regression line in univariate measurement error models. We show that under the typical side conditions, this estimator coincides, in most cases, with the maximum likelihood estimator for the normal structural model. Its large sample properties are derived.

Keywords: Line-segment; structural; relationship; Measurement; error; Method; of; moments; Regression; slope (search for similar items in EconPapers)
Date: 2005
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(04)00303-7
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:71:y:2005:i:3:p:215-223

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:stapro:v:71:y:2005:i:3:p:215-223