Thus the order of fit can be changed by changing the value in a single cell, so the suitability of fit can be seen instantly.įind interpolated or extrapolated intersection of two curves defined by two sets of (x, y) points. Order of fit is a function argument which can also be a cell reference. Polynomial curve fit using the least squares method (up to about order 49) without building elaborate matrices. The interpolation and extrapolation method can therefore be easily changed and results can be viewed instantly. If the default method of interpolation and extrapolation is unsuitable, it can be controlled using function arguments which can be cell references. Three dimensional interpolation and extrapolation using either a set of (x, y, z) points, or matrix of evenly spaced z values. There is a great satisfaction in building good tools for other people to use.įrom a user in Minano, Italy: Your functions have become very popular in the last two or three years, and it would be tough to abandon them.įast, reliable interpolated and extrapolated values in two and three dimensions. If you work with real-life data and want to interpolate, extrapolate, or curve fit, then you will find these functions very useful. ![]() XlXtrFun has been used for years by engineering and research and development personnel on every continent who need to interpolate, extrapolate, and curve fit data rapidly, reliably, and with a virtually non-existent learning curve.
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