Two Classes of Covariance Matrices Giving Simple Linear Forecasts

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/523 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/523 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/523 archive 351 disk0/00/00/04/99 2016-01-15 01:43:03 2021-08-27 17:08:13 2016-01-15 01:43:03 monograph show 2 Jewell W.S. Two Classes of Covariance Matrices Giving Simple Linear Forecasts pub iis_mod iis_met iis_frc prog_sds Two special classes of covariance matrices are considered which give simplified computations for linear forecasts without continued reinversion of the matrix. In the first class, the optimal coefficients in the forecast can be computed in advance for every time period by simple closed formulas. In the second class, which is a generalization of the first, the optimal coefficients are obtained through a simple first-order linear recursive relation between forecasts of successive time periods. Collective risk forecasting models which give rise to these classes of covariances are presented. 1975-05 published RM-75-017 RM-75-017 10 public research_memorandum IIASA, Laxenburg, Austria 28 FALSE info:eu-repo/semantics/book