Estimating the slope in measurement error models - A different perspective

Ori Davidov

doi:10.1016/j.spl.2004.11.011

Estimating the slope in measurement error models - A different perspective

Ori Davidov

Department of Statistics

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	215-223
Number of pages	9
Journal	Statistics and Probability Letters
Volume	71
Issue number	3
DOIs	https://doi.org/10.1016/j.spl.2004.11.011
State	Published - 1 Mar 2005

Keywords

Line-segment structural relationship
Measurement error
Method of moments
Regression slope

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1016/j.spl.2004.11.011

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title = "Estimating the slope in measurement error models - A different perspective",

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.",

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AB - 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.

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KW - Method of moments

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Estimating the slope in measurement error models - A different perspective

Abstract

Keywords

ASJC Scopus subject areas

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