Bayesian Estimation of Time Series Lags and Structure
arXiv:math/0111127 · doi:10.1063/1.1477036
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.
arXiv comment16 pages, 1 figure, MAXENT2001: Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering