Nonlinear regression
Nonlinear regression in statistics is the problem of fitting a model
to multidimensional x,y data, where f is a nonlinear function of x with parameters θ.
In general, there is no algebraic expression for the best-fitting parameters, as there is in linear regression. Usually numerical optimization algorithms are applied to determine the best-fitting parameters. There may be many local maxima of the goodness of fit, again in contrast to linear regression, in which there is usually a unique global maximum of the goodness of fit.
References
G.A.F Seber and C.J. Wild. Nonlinear Regression. New York: John Wiley and Sons, 1989.
Categories: Statistics