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A Bayesian multinomial regression model for paleoclimate reconstruction with time uncertainty
Author(s) -
Parnell Andrew C.
Publication year - 2016
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.2401
Subject(s) - citation , multinomial logistic regression , multinomial distribution , bayesian probability , history , library science , sociology , mathematics , statistics , computer science
In this discussion I hope to highlight some of the real contributions of this paper, to point out some of the important non-statistical considerations (which, as applied statisticians in this area we should be cognisant), and to contrast with the rapidly expanding mostly-Bayesian palaeoclimate statistics literature. In particular, accounting for time uncertainty is, I suspect, almost a unique challenge for time series analysis in palaeoclimate science. For this reason it has been ignored for decades. Now with tools as in this paper, they can start to draw proper inferences on climate over time with suitably quantified uncertainties