Bayesian Estimation of Time Series Lags and Structure

Abstract

This paper derives practical algorithms, based on Bayesian inference methods, for several data analysis problems common in time series analysis of astronomical and other data. One problem is the determination of the lag between two time series, for which the cross-correlation function is a sufficient statistic. The second problem is the estimation of structure in a time series of measurements which are a weighted integral over a finite range of the independent variable.