%
\def\updated{07mar04}%14nov97 \magnification=1200\input carlformat\def\cite#1{[#1]}\parskip10pt % % %It is clear that the resulting interpolant is in $C^{(1)}$. In (complete) cubic spline interpolation, $s_i = f(x_i)$ for $i=1,n$, while all other $s_i$ are chosen to make the interpolant be even in $C^{(2)}$. All other variants of piecewise cubic interpolation choose the $s_i$ by some local considerations. %
In piecewise cubic Hermite interpolation, $s_i = f(x_i)$, all $i$, with $f$ the function being interpolated. %
In Bessel interpolation, $s_i$ is chosen as the slope at $x_i$ of the parabola which matches the data at $x_{i-1}, x_i, x_{i+1}$, except for $i=1,n$ where the slope of the parabola through the nearest three data points is used. %
In Akima interpolation (see Akima70, Akima72), $s_i$ is chosen by certain
geometric considerations as the following average:
$$%
s_i = (w_{i+1} dy_{i-1} + w_{i-1} dy_i) / (w_{i+1} + w_{i-1}),
$$%
with $dy_j := \dvd{x_j,x_{j+1}}y := (y_{j+1}-y_j)/(x_{j+1}-x_j)$ the divided
difference, and
$$%
w_i := |dy_i - dy_{i-1}|.
$$%
The additional data $(x_i,y_i)$ for $i=-1,0$ and $i=n+1,n+2$ are obtained by
evaluating the parabolic interpolant to the nearest three points at the
additional data sites, with $x_i := x_{i+2} + (x_1 - x_3)$ for $i=-1,0$ and a
corresponding formula for the additional two sites at the other end.
Note that only the sequence $dy$ needs extension and that the choice of the
additional data sites is handpicked to give, e.g., $dy_0 = dy_1 + (dy_1-dy_2)$,
$dy_{-1} = dy_1 + 2(dy_1-dy_2)$ (consider the construction of
the additional $dy_i$ as the job of extending the divided difference table at
the points $x_1,x_2,x_3$).
%
14nov97 \bigskip\rightline{last updated \updated} % % \bye