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

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  • Davidov, Ori

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.

Suggested Citation

  • Davidov, Ori, 2005. "Estimating the slope in measurement error models--a different perspective," Statistics & Probability Letters, Elsevier, vol. 71(3), pages 215-223, March.
    • Handle: RePEc:eee:stapro:v:71:y:2005:i:3:p:215-223
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    Cited by:

    1. Davidov, Ori & Griskin, Vladimir, 2008. "A note on constrained estimation in the simple linear measurement error model," Statistics & Probability Letters, Elsevier, vol. 78(5), pages 508-517, April.

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