Abstract
An overview is given of linear measurement error models. Such models appear in many forms, including errors-in-variables regression and factor analysis, but are mathematically related to each other. Of particular interest to chemists are mass balance receptor models in which source profiles are estimated with error. A general model is given for errors in profiles, and the attention of chemists is directed toward recent advances in statistical model fitting and numerical analysis which may be of use in estimating source contributions.
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