As one of the classical statistical regression techniques, and
often the first to be taught to new students, least squares fitting
can be a very effective tool in data analysis. Given measured data,
we establish a relationship between independent and dependent
variables so that we can use the data predictively. The main
concern of "Least Squares Data Fitting with Applications" is how to
do this on a computer with efficient and robust computational
methods for linear and nonlinear relationships. The presentation
also establishes a link between the statistical setting and the
In a number of applications, the accuracy and efficiency of the
least squares fit is central, and Per Christian Hansen, Victor
Pereyra, and Godela Scherer survey modern computational methods and
illustrate them in fields ranging from engineering and
environmental sciences to geophysics. Anyone working with problems
of linear and nonlinear least squares fitting will find this book
invaluable as a hands-on guide, with accessible text and carefully
Included are- an overview of computational methods together with
their properties and advantages- topics from statistical regression
analysis that help readers to understand and evaluate the computed
solutions- many examples that illustrate the techniques and
"Least Squares Data Fitting with Applications" can be used as a
textbook for advanced undergraduate or graduate courses and
professionals in the sciences and in engineering.
Johns Hopkins University Press
|Country of origin:
Per Christian Hansen
• Victor Pereyra
• Godela Scherer
||Electronic book text
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