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On the minimization of a certain convex function arising in applied decision theory
dc.contributor.authorEricson, W. A.en_US
dc.date.accessioned2013-11-01T19:01:07Z
dc.date.available2013-11-01T19:01:07Z
dc.date.issued1968-03en_US
dc.identifier.citationEricson, W. A. (1968). "On the minimization of a certain convex function arising in applied decision theory." Naval Research Logistics Quarterly 15(1): 33-48. <http://hdl.handle.net/2027.42/100328>en_US
dc.identifier.issn0028-1441en_US
dc.identifier.issn1931-9193en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/100328
dc.description.abstractThe author, in an expository paper [4], has presented an algorithm for choosing a non‐negative vector to minimize the function subject to the constraint , where are given vectors and {rm vec M} is positive definite symmetric. In this paper a derivation of this algorithm is presented, including an exact solution in a degenerate case, only alluded to in [4], Several applications, in addition to that of [4], are briefly indicated.en_US
dc.publisherWiley Subscription Services, Inc., A Wiley Companyen_US
dc.titleOn the minimization of a certain convex function arising in applied decision theoryen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelNaval Architecture and Marine Engineeringen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumThe University of Michiganen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/100328/1/3800150104_ftp.pdf
dc.identifier.doi10.1002/nav.3800150104en_US
dc.identifier.sourceNaval Research Logistics Quarterlyen_US
dc.identifier.citedreferenceBellman, R., Introduction to Matrix Analysis ( McGraw‐Hill Book Co., Inc., New York, 1960 ).en_US
dc.identifier.citedreferenceVajda, S., Mathematical Programming ( Addison‐Wesley Publishing Co., Inc., Reading, Mass., 1961 ).en_US
dc.identifier.citedreferenceAnderson, T. W., Introduction to Multivariate Statistical Analysis ( John Wiley and Sons, Inc., New York, 1958 ).en_US
dc.identifier.citedreferenceRaiffa, H. and R. O. Schlaifer, Applied Statistical Decision Theory ( Division of Research, Harvard Business School, Boston, 1961 ).en_US
dc.identifier.citedreferenceKuhn, H. W. and A. W. Tucker, “Non‐Linear Programming,” Proceedings of the Second Berkeley Symposium on Mathematical Statistics and Probability(Ed. J. Neyman )( University of California Press, Berkeley, 1950 ).en_US
dc.identifier.citedreferenceEricson, W. A., “Optimum Allocation in Stratified and Multistage Samples Using Prior Information,” to appear in the J. Am. Statistical Assn.en_US
dc.identifier.citedreferenceEricson, W. A., “On the Economic Choice of Experiment Sizes for Decision Regarding Certain Linear Combinations,” J. Roy. Statistical Soc. (B), Part III( 1967 ).en_US
dc.identifier.citedreferenceEricson, W. A., “Optimum Stratified Sampling Using Prior Information,” J. Am. Statistical Assn. 60, 750 – 771 (Sept. 1965 ).en_US
dc.identifier.citedreferenceDwyer, P. S., “Some Applications of Matrix Derivatives in Multivariate Analysis,” J. Am. Statistical Assn. 62, 607 – 625 (June 1967 ).en_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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