Natural Cubic Splines

 

Here is the MATLAB code that one could use to fitting curve through a set of data points by Natural Cubic Spline. It is my first matlab code.
The fitting of smooth curve through a set of data points
and extention to this is the fitting of 'best fit' spline
to a large set of data points which show the cerrent
trend but which do not all lie above the curve.
The method involves cluster analysis, that is, grouping
the crude data into clusters and seed points are the
limites of each cluster. The central for each clustrer
become nodes through which a natural spline is fitted.

There are five stages nessesary in the cluster analysis
and calculation of node positions, summerised as follow:
1. starting with choosing seed points
2. determine two data point which are closest to each
seed point (the nearest neighbour pair)
3. calculate the coordinate of weighted average of each
nearest neighbour pair.
4. allocate the remaining data points to their
appropriate cluster.
5. calculate the cordinate of the central point of each
cluster, using weight average.

This method can be used for approximation yield curve
(with gross yields or zero yields), which is shown in
those matlab code.

If you want to download Matlab code please click here

example

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