02126aam 2200229 4500999001900000008004500019020001800064082001600082100003200098245005400130260003300184300001400217440005000231520125900281650002301540650004201563650004501605650003501650650003901685942001201724952016001736 c210120d210120180905b1986 ||||| |||| 00| 0 eng d a9780824776176 a511.6bH8A8 aHubert, Lawrence J.9369410 aAssignment methods in combinatorial data analysis bMarcel Dkkerc1986aNew York ax, 326 p. aStatistics, textbooks and monographs 9369411 aFor the first time in one text, this handy pedagogical reference presents comprehensive inference strategies for organizing disparate nonparametric statistics topics under one scheme, illustrating ways of analyzing data sets based on generic notions of proximity (of "closeness") between objects. Assignment Methods in Combinatorial Data Analysis specifically reviews both linear and quadratic assignment models ... covers extensions to multiple object sets and higher-order assignment indices ... considers methods of applying linear assignment models in common data analysis contexts ... discusses a second motion of assignment (or "matching") based upon pairs of objects ... explores confirmatory methods of augmenting multidimensional sealing, cluster analysis, and related techniques ... labels sections in order of priority for continuity and convenience ... and includes extensive bibliographies of related literature. Assignment Methods in Combinatorial Data Analysis gives authoritative coverage of statistical testing, and measures of association in a single source. It is required reading and an invaluable reference for researchers and graduate students in the behavioral and social sciences using quantitative methods of data representation. aStatistics9369412 aLinear Assignment Model (LAM)9369414 aQuadratic Assignment Model (QAM)9369415 aCombinatorial analysis9369416 aLinear models (Statistics)9369413 2ddccBK 00102ddc406511_600000000000000_H8A8708NFIC9355043aVSLbVSLcGENd2018-09-05e71g6.00l2m1o511.6 H8A8p197617r2019-02-26s2018-10-25v8386.00yBK