**Curve fitting** is the process of constructing a curve, or mathematical function, that has the **best fit** to a series of data points, possibly subject to constraints. Curve fitting can involve either interpolation, where an exact fit to the data is required, or smoothing, in which a "smooth" function is constructed that approximately fits the data. A related topic is regression analysis, which focuses more on questions of statistical inference such as how much uncertainty is present in a curve that is fit to data observed with random errors. Fitted curves can be used as an aid for data visualization, to infer values of a function where no data are available, and to summarize the relationships among two or more variables. Extrapolation refers to the use of a fitted curve beyond the range of the observed data, and is subject to a greater degree of uncertainty since it may reflect the method used to construct the curve as much as it reflects the observed data.

Read more about Curve Fitting: Software

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### Famous quotes containing the words fitting and/or curve:

“We do not quite say that the new is more valuable because it fits in; but its *fitting* in is a test of its value—a test, it is true, which can only be slowly and cautiously applied, for we are none of us infallible judges of conformity.”

—T.S. (Thomas Stearns)

“The years-heired feature that can

In *curve* and voice and eye

Despise the human span

Of durance—that is I;

The eternal thing in man,

That heeds no call to die.”

—Thomas Hardy (1840–1928)