FINDING A CONSENSUS ON CREDIBLE FEATURES AMONG SEVERAL PALEOCLIMATE RECONSTRUCTIONS
2013
We propose a method to merge several paleoclimate time series into
one that exhibits a consensus on the features of the individual
times series. The paleoclimate time series can be noisy,
nonuniformly sampled and the dates at which the paleoclimate is
reconstructed can have errors. Bayesian inference is used to
model the various sources of uncertainty and smoothing of the
posterior distribution of the consensus is used to capture its
credible features in different time scales. The technique is
demonstrated by analyzing a collection of six Holocene
temperature reconstructions from Finnish Lapland based on
various biological proxies. Although the paper focuses on
paleoclimate time series, the proposed method can be applied in
other contexts where one seeks to infer features that are
jointly supported by an ensemble of irregularly sampled noisy
time series.
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