The cubic spline interpolation is a method to
interpolate a function y = f(x) within a given interval. The resulting function
runs through the known data points, and has a smooth first derivative and a
continuous second derivative. In order to fully determine the system the
following conditions have to be known:
 n data points (given by pairs of x and y coordinates), sorted by increasing x values
 the value of the first derivative at the first data point, and
 the value of the first derivative at the last data point.
As an alternative condition the second derivative at either endpoint of the interval may be required to be zero. In this case the first derivative is set by the algorithm (natural spline).
The function CubicSpline calculates the value of the spline function (the blue line in the figure above) at the argument x using the data points as specified by EnterStatValue.
