Curve fitting using (r, f(r), f'(r), f''(r))

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The discussion focuses on improving the fitting quality and speed of a function f using its value and its first and second derivatives at various points. The original poster seeks an algorithm that incorporates all data points (r, f(r), f'(r), f''(r)) for fitting, particularly suggesting a sum of Gaussian-type functions. A recommendation is made for the book "Numerical Methods for Scientists and Engineers" by Hamming, which includes a chapter on fitting techniques that utilize derivatives to enhance the fitting process. This resource is noted for being affordable and accessible.
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Hi!

I know the value of a function f and its first and second derivatives at different point r (1D).

I know how to fit it using only f(r) and r, but I'm sure its is possible to improve the quality/speed of the fitting by using also f'(r) and f''(r).

Is anybody have in mind a fitting algorithm using all (r, f(r), f'(r), f''(r))?

Any suggestion (book, web site, paper...) on this topic will be really appreciated.
TPEDIT: The fitting probably needs a sum of gaussian type function.
 
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You are right that knowledge of derivatives will improve the quality of the fit between your known points. The book Numerical Methods for Scientists and Engineers by Hamming devotes a chapter to doing exactly this. It is published by Dover and available cheaply.
 
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