Abstract
Extrapolation refers to the use of a fitted curve beyond the range of the observed data, and 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. 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. If this produces unsatisfactory results, you can try manual guesses. 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. For built-in curve fitting functions, you can let Igor automatically set the initial guesses. For the other built-in data fitting functions and for user-defined functions, the operation must be iterative. For data fitting to user-defined functions, you must supply manual guesses.
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