Fitting a line segment to noisy data

O. Davidov; A. Goldenshluger

doi:10.1016/S0378-3758(02)00409-3

Fitting a line segment to noisy data

O. Davidov, A. Goldenshluger

Department of Statistics

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

Abstract

In this paper, we consider fitting a line segment to noisy data. We describe the structural segment model and establish conditions for its identifiability. The method of moments estimator (MME) is introduced and explored. The MME is easily computed and is invariant under translation rotation and reflection. We show that the MME follows, asymptotically, a normal distribution. The asymptotic efficiency of the MME relative to the maximum likelihood is investigated numerically and found to be high in most cases.

Original language	English
Pages (from-to)	191-206
Number of pages	16
Journal	Journal of Statistical Planning and Inference
Volume	119
Issue number	1
DOIs	https://doi.org/10.1016/S0378-3758(02)00409-3
State	Published - 15 Jan 2004

Keywords

Identifiability
Line-segment structural relationship
Measurement error
Method of moments

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty
Applied Mathematics

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10.1016/S0378-3758(02)00409-3

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AB - In this paper, we consider fitting a line segment to noisy data. We describe the structural segment model and establish conditions for its identifiability. The method of moments estimator (MME) is introduced and explored. The MME is easily computed and is invariant under translation rotation and reflection. We show that the MME follows, asymptotically, a normal distribution. The asymptotic efficiency of the MME relative to the maximum likelihood is investigated numerically and found to be high in most cases.

KW - Identifiability

KW - Line-segment structural relationship

KW - Measurement error

KW - Method of moments

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Fitting a line segment to noisy data

Abstract

Keywords

ASJC Scopus subject areas

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