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Nonlinear Regression


Nonlinear regression is a regression model in which the response is expressed as a function f(x,theta) that is nonlinear in the unknown parameter vector theta. For observations y_i, nonlinear least squares fitting estimates theta by minimizing

 sum_(i)(y_i-f(x_i,theta))^2.

Unlike linear regression, minimization generally requires an iterative method, and the shape of the objective function can produce multiple local minima.


See also

Least Squares Fitting, Linear Regression, Regression

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References

Bates, D. M. and Watts, D. G. Nonlinear Regression Analysis and Its Applications. New York: Wiley, 1988.

Cite this as:

Weisstein, Eric W. "Nonlinear Regression." From MathWorld--A Wolfram Resource. https://mathworld.wolfram.com/NonlinearRegression.html

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