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• W3178784100 abstract "A quantitative analysis of any environment older than the instrumental record relies on proxies. Uncertainties associated with proxy reconstructions are often underestimated, which can lead to artificial conflict between different proxies, and between data and models. In this paper, using ordinary least squares linear regression as a common example, we describe a simple, robust and generalizable method for quantifying uncertainty in proxy reconstructions. We highlight the primary controls on the magnitude of uncertainty, and compare this simple estimate to equivalent estimates from Bayesian, nonparametric and fiducial statistical frameworks. We discuss when it may be possible to reduce uncertainties, and conclude that the unexplained variance in the calibration must always feature in the uncertainty in the reconstruction. This directs future research toward explaining as much of the variance in the calibration data as possible. We also advocate for a data-forward approach, that clearly decouples the presentation of proxy data from plausible environmental inferences." @default.
• W3178784100 created "2021-07-19" @default.
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• W3178784100 date "2021-08-01" @default.
• W3178784100 modified "2023-10-14" @default.
• W3178784100 title "Statistical Uncertainty in Paleoclimate Proxy Reconstructions" @default.
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• W3178784100 doi "https://doi.org/10.1029/2021gl092773" @default.
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