**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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... TableCurve 2D is a linear and non-linear

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... as projecting data onto a solution – which is well known as

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**Curve Fitting**- Software

... such as the GNU Scientific Library, SciPy and OpenOpt include commands for doing

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**curve fitting**they can be found in the lists of statistical and numerical analysis programs as well as in CategoryRegression and

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**Curve Fitting**

... Using a

**curve fitting**technique like Gaussian reduction an N-1th degree polynomial interpolation of the function is found ...

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

“Children’s view of the world and their capacity to understand keep expanding as they mature, and they need to ask the same questions over and over, *fitting* the information into their new level of understanding.”

—Joanna Cole (20th century)

“And out again I *curve* and flow

To join the brimming river,

For men may come and men may go,

But I go on forever.”

—Alfred Tennyson (1809–1892)