Bayesian approach to smoothing palaeomagnetic data using ABIC

Abstract

Bayesian spline regression for 1‐D time series is useful for smoothing palaeointensity data. This method, however, is not applicable to directional data composed of inclination and declination. In the present study a new spline regression, based on Bayesian statistics, is developed for smoothing a time series of unit vectors subjected to Fisher distribution. An optimal smoothing factor is determined by minimizing a Bayesian information criterion (ABIC) in this new method. These methods are applied to archaeomagnetic data in Japan, and the X, Y and Z components are estimated in the absolute scale for the time span of 200–2000 yr BP. Copyright © 1992, Wiley Blackwell. All rights reserved