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G. Chant, INRIA, Rocquencourt, France Nonlinear Least Squares for Inverse Problems Theoretical Foundations and Step-by-Step Guide for Applications 2010. XIV, 360 p. (Scientific Computation) Hardcover
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What is nonlinear least squares for?
Nonlinear least squares is a method used to estimate the parameters of a nonlinear mathematical model by minimizing the sum of the squared differences between the observed and predicted values.
Who is required to file nonlinear least squares for?
Nonlinear least squares is a statistical technique utilized by researchers, scientists, and analysts in various fields such as economics, physics, and engineering.
How to fill out nonlinear least squares for?
To fill out nonlinear least squares, you need to have a mathematical model describing the relationship between variables, data representing observed values, and an optimization algorithm that minimizes the sum of the squared differences.
What is the purpose of nonlinear least squares for?
The purpose of nonlinear least squares is to estimate the unknown parameters in a nonlinear model, allowing for the best fit between observed data and the predicted values from the model.
What information must be reported on nonlinear least squares for?
In nonlinear least squares, the reported information includes the estimated parameter values, the goodness-of-fit statistics, such as residual sum of squares or R-squared, and any relevant diagnostics or confidence intervals.
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