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.
