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Wiley Series in Probability and Statistics Ser.: Multivariate Analysis : Methods and Applications by William R. Dillon and Matthew Goldstein (1984, Hardcover)
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About this product
Product Identifiers
PublisherWiley & Sons, Incorporated, John
ISBN-100471083178
ISBN-139780471083177
eBay Product ID (ePID)243551
Product Key Features
Number of Pages608 Pages
Publication NameMultivariate Analysis : Methods and Applications
LanguageEnglish
Publication Year1984
SubjectProbability & Statistics / Multivariate Analysis
TypeTextbook
Subject AreaMathematics
AuthorWilliam R. Dillon, Matthew Goldstein
SeriesWiley Series in Probability and Statistics Ser.
FormatHardcover
Dimensions
Item Height1.3 in
Item Weight33.7 Oz
Item Length9.6 in
Item Width6.4 in
Additional Product Features
Intended AudienceScholarly & Professional
LCCN84-003584
Dewey Edition19
Series Volume Number118
IllustratedYes
Dewey Decimal519.5/35
Table Of ContentSelected Aspects of Multivariate Analysis. Principal Components Analysis. Factor Analysis. Multidimensional Scaling. Cluster Analysis. Multiple Regression. Some Practical Considerations: Data Analysis Problems. Cross-Classified Frequency Data. Canonical Correlation Analysis. Discriminant Analysis: The Two-Group Problem. Multiple Discriminant Analysis and Related Topics. Linear Structural Relations (LISREL). Latent Structure Analysis. Appendixes. References. Index.
SynopsisStructural Sensitivity in Econometric Models Edwin Kuh, John W. Neese and Peter Hollinger Provides a pathbreaking assessment of the worth of linear dynamic systems methods for probing the behavior of complex macroeconomic models., Structural Sensitivity in Econometric Models Edwin Kuh, John W. Neese and Peter Hollinger Provides a pathbreaking assessment of the worth of linear dynamic systems methods for probing the behavior of complex macroeconomic models. Representing a major improvement upon the standard "black box" approach to analyzing economic model structure, it introduces the powerful concept of parameter sensitivity analysis within a linear systems root/vector framework. The approach is illustrated with a good mediumsize econometric model (Michigan Quarterly Econometric Model of the United States). EISPACK, the Fortran code for computing characteristic roots and vectors has been upgraded and augmented by a model linearization code and a broader algorithmic framework. Also features an interface between the algorithmic code and the interactive modeling system (TROLL), making an unusually wide range of linear systems methods accessible to economists, operations researchers, engineers and physical scientists. 1985 (0-471-81930-1) 324 pp. Linear Statistical Models and Related Methods With Applications to Social Research John Fox A comprehensive, modern treatment of linear models and their variants and extensions, combining statistical theory with applied data analysis. Considers important methodological principles underlying statistical methods. Designed for researchers and students who wish to apply these models to their own work in a flexible manner. 1984 (0 471-09913-9) 496 pp. Statistical Methods for Forecasting Bovas Abraham and Johannes Ledolter This practical, user-oriented book treats the statistical methods and models used to produce short-term forecasts. Provides an intermediate level discussion of a variety of statistical forecasting methods and models and explains their interconnections, linking theory and practice. Includes numerous time-series, autocorrelations, and partial autocorrelation plots. 1983 (0 471-86764-0) 445 pp.
LC Classification NumberQA278.D55 1984
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