| Principal component analysis (PCA) is a well-established technique in paleomagnetism and provides a means to estimate magnetic remanence directions from univectorial segments of stepwise demagnetization data. Derived directions constrain past geomagnetic field behavior and form the foundation of chronological and tectonic reconstructions. PCA of isolated remanence segments relies on estimates of the segment mean and covariance matrix, which can carry large uncertainties given the relatively small number of demagnetization data points used to characterize individual specimens. Traditional PCA does not, however, lend itself to quantification of these uncertainties, and inferences drawn from paleomagnetic reconstructions suffer from an inability to propagate... |
