A computational examination of orthogonal distance regression

• Published in: Journal of econometrics Vol. 38; no. 1; pp. 169 - 201
• Main Authors: Boggs, Paul T., Spiegelman, Clifford H., Donaldson, Janet R., Schnabel, Robert B.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.05.1988; Elsevier; North-Holland Pub. Co; Elsevier Sequoia S.A
• Series: Journal of Econometrics
• Subjects: Algorithms; Discriminant analysis; Econometrics; Exact sciences and technology; Mathematics; Monte Carlo simulation; Multivariate analysis; Probability and statistics; Sciences and techniques of general use; Statistics; Regression; Statistical estimation; Fitting; Least squares method

Ordinary least squares (OLS) is one of the most commonly used criteria for fitting data to models and for estimating parameters. Orthogonal distance regression (ODR) extends least squares data fitting to problems with independent variables that are not known exactly. In this paper, we present the re...