Multidimensional Nonlinear Descriptive Analysis

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A01=Shizuhiko Nishisato
advanced categorical data modeling
Author_Shizuhiko Nishisato
categorical data analysis
Category=JMA
Category=JMB
Category=PBT
Category=PS
choice
contingency
Contingency Table
contingency tables
Correlation Ratio
correspondence
Correspondence Analysis
data
Data Set
Dominance Data
Dominance Matrix
Dominance Numbers
Dominance Table
dual
Dual Scaling
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
eq_society-politics
Hellinger Distance
Joint Plots
Multidimensional Nonlinear Descriptive Analysis
multiple
Multiple Choice Data
Multiple Correspondence Analysis
multivariate methods
Nonlinear Relations
nonlinear statistics
order
Order Constraint
Paired Comparison Data
Partial Canonical Correspondence Analysis
Proper Component
psychological measurement
rank
Rank Order Data
Reciprocal Averaging
scaling
social science research
Successive Categories Data
Symmetric Scaling
table
Unidimensional Scaling
Vice Versa

Product details

  • ISBN 9781584886129
  • Weight: 598g
  • Dimensions: 156 x 234mm
  • Publication Date: 26 Jun 2006
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Quantification of categorical, or non-numerical, data is a problem that scientists face across a wide range of disciplines. Exploring data analysis in various areas of research, such as the social sciences and biology, Multidimensional Nonlinear Descriptive Analysis presents methods for analyzing categorical data that are not necessarily sampled randomly from a normal population and often involve nonlinear relations.

This reference not only provides an overview of multidimensional nonlinear descriptive analysis (MUNDA) of discrete data, it also offers new results in a variety of fields. The first part of the book covers conceptual and technical preliminaries needed to understand the data analysis in subsequent chapters. The next two parts contain applications of MUNDA to diverse data types, with each chapter devoted to one type of categorical data, a brief historical comment, and basic skills peculiar to the data types. The final part examines several problems and then concludes with suggestions for future progress.

Covering both the early and later years of MUNDA research in the social sciences, psychology, ecology, biology, and statistics, this book provides a framework for potential developments in even more areas of study.

Nishisato, Shizuhiko

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