Simplex Algorithm
SimplexNumerica provides the following algorithm:
Regression
- Linear Least Squares Fit
- Exponential Least Squares Fit
- Logarithmic Least Squares Fit
- Power Least Squares Fit
- Invers Least Squares Fit
- n-dimensinal Polynomial
- Quadratic Polynomial
- Cubic Polynomia
- Sine Wave
Approximation
- Simplex Algorithm Fit
- Gauß Algorithm Fit
- Bezier
- B-Spline
- Smoothing Spline
- Parametric Smoothing Spline
- Cyclic Smoothing Spline
Interpolation
- Polygonal Curve
- Additive Segmentation
- (n-1) Polynomial
- Lagrange polynomial
- Newton Polynomial
- Rationale Polynomial
- Aitken/Neville Polynomial
- Cubic Spline
- Parametric Spline
- Periodic Spline
- Cyclic Spline
- Smooth Spline
- Akima Subspline
- Renner Subspline
- Hermite Splines
- Catmull-Rom Spline
- Kochanek-Bartel Spline
- Cardinal Spline
Surface Fit
- Bi-Linear
- Nearest Neighbors Linear
- Smoothing Spline
- Thin Plate Surface Spline
- Nearest Neighbors Distance
- Nearest Neighbors Around Distance
- Thin Plate Surface Spline
- Bivariate Cubic Spline
FFT
- Approximation
- Spectrum
- Phase
- Analysis
- Synthesis
- Real Part
- Imaginary Part
Outlier Test
- Dean-Dixon
- Nalimov
- Grubbs
- Significance of extreme values
Polyline Simplification
- Polyline Simplification
- Radial Vertex Reduction
- Perpendicular Vertex Reduction
- Retake Perpendicular Vertex Reduction
- Reumann/Witkam Reduction
- Ramer/Douglas/Peucker Reduction
- Optimized Ramer/Douglas/Peucker Reduction
IMPORTANT: WARRANTY DISCLAIMER
The author makes no warranty of any kind, expressed or implied, including
any warranties of
fitness for a particular purpose. In no event will the author be liable
for any incidental
or consequential damages arising from the use of, or inability to use,
this algorithm
from the programs SimplexNumerica or Simplexety.
In particular you must NOT assume
that the algorithm shown
are always
correct in SimplexNumerica or Simplexety!
