Data Fitting and Uncertainty (Paperback)
Tilo Strutz
Sold by Grand Eagle Retail, Bensenville, IL, U.S.A.
AbeBooks Seller since October 12, 2005
New - Soft cover
Condition: New
Ships within U.S.A.
Quantity: 1 available
Add to basketSold by Grand Eagle Retail, Bensenville, IL, U.S.A.
AbeBooks Seller since October 12, 2005
Condition: New
Quantity: 1 available
Add to basketPaperback. The primary goal of this book is to provide a recipe explaining the functioning of data fitting via least squares and the emphasis here is on practical matters, not on theoretical problems. In addition, the book enables the reader to design own software implementation with application-specific model functions based on the comprehensive discussion of several examples. It includes a self-contained introduction and presents the method in a logical and accessible fashion. The subject of data fitting bridges many disciplines, especially those dealing traditionally with statistics as, for instance, physics, mathematics, engineering, biology, economy, or psychology, but also more recent fields as computer vision. This book is addressed to engineers and computer scientists or corresponding undergraduates, which are interested in data fitting by the method of least-squares approximation, but have no or only limited pre-knowledge in this field. Experienced readers will find new details and interpretations or might appreciate the book as useful reference. The text is accompanied with working source code in ANSI-C for the fitting with weighted least squares including outlier detection. The primary goal of this book is to provide a recipe explaining the functioning of data fitting via least squares and the emphasis here is on practical matters, not on theoretical problems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Seller Inventory # 9783658114558
The primary goal of this book is to provide a recipe explaining the functioning of data fitting via least squares and the emphasis here is on practical matters, not on theoretical problems. In addition, the book enables the reader to design own software implementation with application-specific model functions based on the comprehensive discussion of several examples. It includes a self-contained introduction and presents the method in a logical and accessible fashion. The subject of data fitting bridges many disciplines, especially those dealing traditionally with statistics as, for instance, physics, mathematics, engineering, biology, economy, or psychology, but also more recent fields as computer vision. This book is addressed to engineers and computer scientists or corresponding undergraduates, which are interested in data fitting by the method of least-squares approximation, but have no or only limited pre-knowledge in this field. Experienced readers will find new details and interpretations or might appreciate the book as useful reference. The text is accompanied with working source code in ANSI-C for the fitting with weighted least squares including outlier detection.
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