Curve fitting is the idea to construct a mathematical function which best fits a set of data points. possibly subject to constraints. Curve fitting can involve either interpolation or smoothing. Using interpolation requires an exact fit to the data. With smoothing, a "smooth" function is constructed, that fit the data approximately. 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 to help data visualization, to guess values of a function where no data is 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. This is subject to a degree of uncertainty since it may reflect the method used to construct the curve as much as it reflects the observed data.
References[change | change source]
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- See also: Mollifier
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