Assignment methods in combinatorial data analysis
Hubert, Lawrence J.
creator
text
New York
Marcel Dkker
1986
monographic
| 0
x, 326 p.
For 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.
Statistics
Linear Assignment Model (LAM)
Quadratic Assignment Model (QAM)
Combinatorial analysis
Linear models (Statistics)
511.6 H8A8
Statistics, textbooks and monographs
9780824776176
180905