Regression Diagnostics

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. "e;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."e; Journal of the Royal Statistical Society "e;The book assumes a working knowledge of all of the principal results and techniques used in least squares multiple regression, as expressed in vector and matrix notation. Given this background, the book is clear and easy to use. . . . The techniques are illustrated in great detail with practical data sets from econometrics."e; Short Book Reviews, International Statistical Institute 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

The Wiley-Interscience Paperback Series consists of selected booksthat have been made more accessible to consumers in an effort toincrease global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese works by making them available to future generations ofstatisticians, mathematicians, and scientists."The title of the book more or less sums up the contents. Itappears to me to represent a real breakthrough in the art ofdealing in 'unconventional' data. . . . I found thewhole book both readable and enjoyable. It is suitable for dataanalysts, academic statisticians, and professional softwarewriters."Journal of the Royal Statistical Society"The book assumes a working knowledge of all of the principalresults and techniques used in least squares multiple regressionas expressed in vector and matrix notation. Given this backgroundthe book is clear and easy to use. . . . The techniques areillustrated in great detail with practical data sets fromeconometrics."Short Book Reviews, International Statistical InstituteRegression Diagnostics: Identifying Influential Data and Sourcesof Collinearity provides practicing statisticians andeconometricians with new tools for assessing quality andreliability of regression estimates. Diagnostic techniques aredeveloped that aid in the systematic location of data points thatare unusual or inordinately influential; measure the presence andintensity of collinear relations among the regression data; andhelp to identify variables involved in each and pinpoint estimatedcoefficients potentially most adversely affected. The bookemphasizes diagnostics and includes suggestions for remedialaction

1. Introduction and Overview.2. Detecting Influential Observations and Outliers.3. Detecting and Assessing Collinearity.4. Applications and Remedies.5. Research Issues and Directions for Extensions.Bibliography.Author Index.Subject Index.