Robust Diagnostic Regression Analysis
Atkinson, Anthony; Riani, Marco
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Description for Robust Diagnostic Regression Analysis
Paperback. Series: Springer Series in Statistics. Num Pages: 344 pages, biography. BIC Classification: PBT. Category: (G) General (US: Trade). Dimension: 235 x 155 x 18. Weight in Grams: 534.
This book is about using graphs to understand the relationship between a regression model and the data to which it is fitted. Because of the way in which models are fitted, for example, by least squares, we can lose infor mation about the effect of individual observations on inferences about the form and parameters of the model. The methods developed in this book reveal how the fitted regression model depends on individual observations and on groups of observations. Robust procedures can sometimes reveal this structure, but downweight or discard some observations. The novelty in our book is to combine robustness ... Read more
This book is about using graphs to understand the relationship between a regression model and the data to which it is fitted. Because of the way in which models are fitted, for example, by least squares, we can lose infor mation about the effect of individual observations on inferences about the form and parameters of the model. The methods developed in this book reveal how the fitted regression model depends on individual observations and on groups of observations. Robust procedures can sometimes reveal this structure, but downweight or discard some observations. The novelty in our book is to combine robustness ... Read more
Product Details
Format
Paperback
Publication date
2012
Publisher
Springer-Verlag New York Inc. United States
Number of pages
344
Condition
New
Series
Springer Series in Statistics
Number of Pages
328
Place of Publication
New York, NY, United States
ISBN
9781461270270
SKU
V9781461270270
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Robust Diagnostic Regression Analysis
From the reviews: MATHEMATICAL REVIEWS "The text is lucidly written and theoretical discussions are amply complemented with examples and exercises. The book is accessible to students and users of statistical methods. It could, without doubt, serve as a textbook for courses on applied regression and generalized linear models. It will be a welcome addition to the ... Read more