PV-WAVE Advantage > IMSL Mathematics Reference Guide > Interpolation and Approximation
Interpolation and Approximation
 
This section contains the following topics:
*Cubic Spline Interpolation
*CSINTERP Function—Derivative end conditions.
*CSSHAPE Function—Shape preserving.
*B-spline Interpolation
*BSINTERP Function—One-dimensional and two-dimensional interpolation.
*BSKNOTS Function—Knot sequence given interpolation data.
*B-spline and Cubic Spline Evaluation and Integration
*SPVALUE Function—Evaluation and differentiation.
*SPINTEG Function—Integration.
*Least-squares Approximation and Smoothing
*FCNLSQ Function—General functions.
*BSLSQ Function—Splines with fixed knots.
*CONLSQ Function—Constrained spline fit.
*CSSMOOTH Function—Cubic-smoothing spline.
*WgSplineTool Procedure—Widget-based interface.
*SMOOTHDATA1D Function—Smooth one-dimensional data by error detection.
*POLYEVAL Function—Evaluates a polynomial.
*WENDCOEF Function—Computes the coefficients for the Wendland polynomial of type (d,k).
*POLYFITN Function—Fits a polynomial.
*Scattered Data Interpolation
*SCAT2DINTERP Function—Akima’s surface-fitting method.
*RADBF Function—Computes a fit using radial-basis functions.
*RADBE Function—Evaluates a radial-basis fit.
*RBFIMSCL Procedure—Multiscale radial basis interpolation for n-dimensional data.