Given a set of discrete data points representing the known values
at certain positions
in an n-D space, we may want to estimate the value
at
any other point , using the method of *interpolation*
if is inside the range of the known data points, or
*extrapolation* if is outside the range. For exammple,
the known values of data points may be a set of measuremnts (samples)
of certain variable (e.g.,temperature) over space (3-D) and time (1-D),
and the goal is to estimate its value at any other point in space and
time. Typically this can be achieved by fitting the dataset by a
continuous function
, such as a polynomial, that either
passes through the data points
, or
approximates the data ponts
. The
function
should be continuous ( continuous) and
preferably smooth ( continuous with ).

- Polynomial Interpolation
- The Lagrange Interpolation
- The Newton Polynomial Interpolation
- Hermite Interpolation
- Cubic Spline Interpolation
- 2-D Interpolation