Experience Accumulation for Decision Making in Multivariate Time Series

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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/634 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/634 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/634 archive 351 disk0/00/00/06/14 2016-01-15 01:43:37 2021-08-27 17:08:25 2016-01-15 01:43:37 monograph show 2 Peterka V. AL0316 Experience Accumulation for Decision Making in Multivariate Time Series pub iis_met prog_sds A dynamic stochastic system with multivariate input and multivariate output, possibly controlled in a closed loop, is considered. It is assumed that the input-output relation is describable by a model of a given structure but with a finite set of unknown parameters. The uncertainty of the parameters is characterized by the subjective probability density function. Functional recursion relations are derived describing the evolution of this subjective p.d.f. when it is successively conditioned by the observed data. A self-reproducing form of the conditional p.d.f. is found for the case, when the process is describable by a multivariate regression model and no parameter -- except the order -- is a priori known. This makes it possible to reduce the functional recursion into an algebraic recursion which is easy to perform. 1976-09 published RM-76-070 RM-76-070 10 2285 public research_memorandum IIASA, Laxenburg, Austria 28 FALSE info:eu-repo/semantics/book