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arXiv · 1112.1745

Measurement Error Models in Astronomy

Brandon C. Kelly
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Abstract

I discuss the effects of measurement error on regression and density estimation. I review the statistical methods that have been developed to correct for measurement error that are most popular in astronomical data analysis, discussing their advantages and disadvantages. I describe functional models for accounting for measurement error in regression, with emphasis on the methods of moments approach and the modified loss function approach. I then describe structural models for accounting for measurement error in regression and density estimation, with emphasis on maximum-likelihood and Bayesian methods. As an example of a Bayesian application, I analyze an astronomical data set subject to large measurement errors and a non-linear dependence between the response and covariate. I conclude with some directions for future research.

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Brandon C. Kelly. 2011-12-08. Measurement Error Models in Astronomy. https://arxiv.org/abs/1112.1745

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