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Parametric Regression


Parametric regression is regression in which the relation between predictors and a response is assumed to have a specified functional form depending on a finite-dimensional parameter vector. A model may be written

 y=f(x;theta)+epsilon,

where the data are used to estimate theta. Linear regression and many forms of nonlinear regression are parametric (Bates and Watts 1988). In contrast, symbolic regression searches over the functional form as well as its parameters.


See also

Linear Regression, Parameter, Regression, Symbolic Regression

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References

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

Cite this as:

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

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