# Package smile.interpolation

package smile.interpolation
Interpolation is the process of constructing a function that takes on specified values at specified points. In engineering and science, one often has a number of data points, obtained by sampling or experimentation, which represent the values of a function for a limited number of values of the independent variable. It is often required to interpolate (i.e. estimate) the value of that function for an intermediate value of the independent variable. A different problem which is closely related to interpolation is the approximation of a complicated function by a simple function.
• Class
Description
Abstract base class of one-dimensional interpolation methods.
Bicubic interpolation in a two-dimensional regular grid.
Bilinear interpolation in a two-dimensional regular grid.
Cubic spline interpolation.
Cubic spline interpolation in a two-dimensional regular grid.
In numerical analysis, interpolation is a method of constructing new data points within the range of a discrete set of known data points.
Interpolation of 2-dimensional data.
Kriging interpolation for the data points irregularly distributed in space.
Kriging interpolation for the data points irregularly distributed in space.
Kriging interpolation for the data points irregularly distributed in space.
Laplace's interpolation to restore missing or unmeasured values on a 2-dimensional evenly spaced regular grid.
Piecewise linear interpolation.
Radial basis function interpolation is a popular method for the data points are irregularly distributed in space.
Radial basis function interpolation is a popular method for the data points are irregularly distributed in space.
Radial basis function interpolation is a popular method for the data points are irregularly distributed in space.
Shepard interpolation is a special case of normalized radial basis function interpolation if the function φ(r) goes to infinity as r → 0, and is finite for `r > 0`.
Shepard interpolation is a special case of normalized radial basis function interpolation if the function φ(r) goes to infinity as r → 0, and is finite for `r > 0`.
Shepard interpolation is a special case of normalized radial basis function interpolation if the function φ(r) goes to infinity as r → 0, and is finite for `r > 0`.