A very fast and simple algorithm for estimation of the parameters of large multivariate time series and distributed lag models is presented. An analysis of the distribution of the estimates shows that they are asymptotically normal and unbiased, and that they have a variance that decreases like 1/n, n being the sample size. The algorithm is especially applicable for estimation of large multivariate models where it is generally many times faster than maximalization algorithms.
No takes yet. Share an insight, caveat, or question.
Henrik Spliid (1983) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: