Version 2.5 has four functions: 'linear_interp', 'cubic_spline', 'bessel_spline' and 'oneway_spline'. These functions are listed under the 'SRS1Spline.Functions25' function category in the 'Insert Function' dialog box of Excel.

Click the Repair/Refresh button on the ribbon bar to refresh the functions on your workbook and fix those broken links.

Yes. 'Data Curve Fit Creator Add-in' has all the functions included in SRS1 Cubic Spline for Excel along with many more. To avoid confusion, the function names in SRS1 'SRS1 Cubic Spline for Excel' include underscores, but the function names in Data Curve Fit Creator Add-in do not contain underscores.

A cubic spline interpolates a smooth line through a given set of data points. Unlike a polynomial or other curve fits, a spline is forced to directly pass through all points in the data set. There are a few other constraints that are used to generate the smooth curve. Interpolating between two points, if we know the second derivative tat the first and second points, then the second derivative of the interpolated curve will vary linearly from the first to the second point. Also, the first derivative of the curve needs to be continuous across the curve.

As mentioned before, the cubic spline is forced to go through all data points. If there is noise in your data, then the curve can become erratic as it tries to smoothly pass through each point. You can try using the Bessel_spline or OneWay_spline functions for more constrained results.

The other person needs to have the SRS1 Cubic Spline for Excel add-in installed on their machine for functions to work for them.

The Bessel spline is similar to the cubic spline except the Bessel spline uses a parabolic fit internally for its interpolation. The results of the Bessel spline can be more constrained (fewer unwanted oscillations) than the cubic spline, but might be be as smooth.

The 'OneWay' spline is a constrained version of the bessel spline which always produces monotic results as long as the source data is monotonic. It is the most constrained (fewest overshoots and oscillations) spline in this add-in. You can use the OneWay spline with data that isn't monotonic as well. In that case the results won't necessarily be monotonic, but it will still be a very contrained curve (fewest possible overshoots and oscillations). You would use this if you had monotonic data or if the other splines produced oscillations between data points.

It means only flat/increasing or only flat/decreasing. For example {1,2,2,3} is monotonic while {1, 2, 3, 2} is not.

We recommend the book 'Numerical Recipes: The Art of Scientific Computing, Third Edition (2007)', published by Cambridge University Press'. The code in SRS1 Cubic Spline for Excel is based on the cubic spline in that book.