01843aam a2200193 4500008004500000020001800045082001600063100002400079245005400103260003300157300001400190440004200204520125900246650001501505650003401520650003701554650002701591650003101618180905b1986 ||||| |||| 00| 0 eng d a9780824776176 a511.6bH8A8 aHubert, Lawrence J. aAssignment methods in combinatorial data analysis bMarcel Dkkerc1986aNew York ax, 326 p. aStatistics, textbooks and monographs 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. aStatistics aLinear Assignment Model (LAM) aQuadratic Assignment Model (QAM) aCombinatorial analysis aLinear models (Statistics)