Conditioning Diagnostics
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Conditioning Diagnostics: Collinearity and Weak Data in Regression(Probability & Mathematical Statistics S.)

Conditioning Diagnostics: Collinearity and Weak Data in Regression(Probability & Mathematical Statistics S.)


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About the Book

This study integrates old and new procedures for analyzing the problems of ill-conditioning (which include collinearity) that attend statistical data. It aids in understanding how these problems affect statistical estimation and provides suggestions and examples of corrective action. The approach emphasizes diagnostics, drawing on elements of statistics, econometrics, data and numerical analysis. Any of the analytical and geometric tools that are needed are developed and explained. Numerous illustrations and data sets are included as a source for user experiments. The diagnostics featured in the text deal with situations where two explanatory variables vary in much the same way, so it is not possible to separate their effects.

Table of Contents:
Collinearity; A Collinearity Diagnostic; The Experimental Experience; Summarizing and Interpreting the Collinearity Diagnostics; Data and Model Considerations; Harmful Collinearity and Short Data; Collinearity-Influential Observations; Collinearity Diagnostics in Models with Logarithms and First Differences; Corrective Action and Case Studies; General Conditioning and Extensions to Nonlinearities and Simultaneity; Bibliography; Author Index; Subject Index.

Review :
"The book is invaluable for everyone who applies linear regression." (Kwantitatieve Methoden, October 2000)


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Product Details
  • ISBN-13: 9780471528890
  • Publisher: John Wiley and Sons Ltd
  • Publisher Imprint: John Wiley & Sons Inc
  • Height: 241 mm
  • Returnable: N
  • Sub Title: Collinearity and Weak Data in Regression
  • Width: 165 mm
  • ISBN-10: 0471528897
  • Publisher Date: 05 Feb 1991
  • Binding: Hardback
  • Language: English
  • Series Title: Probability & Mathematical Statistics S.
  • Weight: 765 gr


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Conditioning Diagnostics: Collinearity and Weak Data in Regression(Probability & Mathematical Statistics S.)
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