Statistics – Computation
Scientific paper
Jun 1994
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1994mnras.268..690k&link_type=abstract
Monthly Notices of the Royal Astronomical Society, Vol. 268, NO. 3/JUN1, P. 690, 1994
Statistics
Computation
8
Scientific paper
Lag estimation methods that have been used in the astronomical literature are reviewed. Some problems are pointed out, particularly the influence of autocorrelation and non-stationarity of the series. If the two series can be modelled as random walks, both these problems can be dealt with efficiently. Maximum likelihood estimation of the random walk and measurement error variances, as well as the lag between the two series, is discussed. Large-sample properties of the estimators are derived. An efficient computational procedure for the likelihood, which exploits the sparseness of the covariance matrix, is briefly described. Results are derived for two sample data sets: observations of the two components of a gravitational lens and photometry of an AGN.
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