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Davis, Donald W. (1982) Optimum linear regression and error estimation applied to U–Pb data. Canadian Journal of Earth Sciences, 19 (11) 2141-2149 doi:10.1139/e82-188

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Reference TypeJournal (article/letter/editorial)
TitleOptimum linear regression and error estimation applied to U–Pb data
JournalCanadian Journal of Earth Sciences
AuthorsDavis, Donald W.Author
Year1982 (November 1)Volume19
Issue11
PublisherCanadian Science Publishing
DOIdoi:10.1139/e82-188Search in ResearchGate
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Mindat Ref. ID477308Long-form Identifiermindat:1:5:477308:9
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Full ReferenceDavis, Donald W. (1982) Optimum linear regression and error estimation applied to U–Pb data. Canadian Journal of Earth Sciences, 19 (11) 2141-2149 doi:10.1139/e82-188
Plain TextDavis, Donald W. (1982) Optimum linear regression and error estimation applied to U–Pb data. Canadian Journal of Earth Sciences, 19 (11) 2141-2149 doi:10.1139/e82-188
In(1982, November) Canadian Journal of Earth Sciences Vol. 19 (11) Canadian Science Publishing
Abstract/Notes A method is presented for the estimation of age errors for U–Pb zircon data based on Bayesian confidence intervals. The optimum regression problem is first solved using the formalism of maximum probability. The correlation between errors is removed by applying a separate rotation and translation operator for each point. A probability density function is then defined in terms of two straight-line parameters, slope and y intercept, and the optimum line is found by maximizing this function. The intercept parameter is then transformed into an age t, determined by the upper concordia intercept of the given line, and the function is redefined in terms of the slope and t. By integrating this function over the slope parameter, a function of probability versus t is obtained. The age errors then have a natural expression in terms of the width of this function. The results are compared with an approximative method based on confidence-interval theory. A model is then presented to estimate ages and errors for U–Pb data that do not fit a line within error. The error ellipses of the data points are expanded by an amount proportional to discordance until a good fit is obtained. A Student's t factor is applied only to the residuals in the resulting age errors.


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