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Belsley D.A., Kuh E., Welsch R.E. Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

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Belsley D.A., Kuh E., Welsch R.E. Regression Diagnostics: Identifying Influential Data and Sources of Collinearity
Wiley – 2004, 314 pages
ISBN: 0471691178
The title of the book more or less sums up the contents. It appears to me to represent a real breakthrough in the art of dealing in ‘unconventional’ data I found the whole book both readable and enjoyable. It is suitable for data analysts, academic statisticians, and professional software writers.
Provides practicing statisticians and econometricians with new tools for assessing quality and reliability of regression estimates. Diagnostic techniques are developed that aid in the systematic location of data points that are unusual or inordinately influential, and measure the presence and intensity of collinear relations among the regression data and help to identify variables involved in each and pinpoint estimated coefficients potentially most adversely affected
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.
Regression Diagnostics: Identifying Influential Data and Sources of Collinearity provides practicing statisticians and econometricians with new tools for assessing quality and reliability of regression estimates. Diagnostic techniques are developed that aid in the systematic location of data points that are unusual or inordinately influential; measure the presence and intensity of collinear relations among the regression data; and help to identify variables involved in each and pinpoint estimated coefficients potentially most adversely affected. The book emphasizes diagnostics and includes suggestions for remedial action
Introduction and Overview.
Detecting Influential Observations and Outliers.
Detecting and Assessing Collinearity.
Applications and Remedies.
Research Issues and Directions for Extensions.
Author Index.
Subject Index.
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