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978-3-8439-1807-7, Reihe Statistik
Alexander Pilhöfer Categorical Data Analysis Reordered
284 Seiten, Dissertation Universität Augsburg (2014), Hardcover, D4
The analysis of categorical data can often be challenging, especially when multiple nominal variables are involved. The major problem is the lack of naturally defined distances and orders. In this work the concept of 'joint reordering' is introduced and applied in different areas of categorical data analysis: Various methods are developed and described which can be utilized for discrete clustering, measuring associations or to widen the scope of visualizations and improve their interpretability. The book also offers some new visualizations, concepts for applications of reordering to large scale data and of course many real-data examples. The reader is also invited to try the technqiues out using the implementations in the R package extracat.