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GeneralMiniMaxApproximation[{fx, fy}, {t, {t0, t1}, m, n}, x]
finds the rational polynomial function of x, with numerator order m and denominator order n, that gives a mini-max approximation to the curve with x and y coordinates fx and fy generated as a function of t on the interval t0 to t1.
GeneralMiniMaxApproximation[{fx, fy}, approx, {t, {t0, t1}, m, n}, x]
finds the mini-max approximation, starting the iterative algorithm with approx.
  • GeneralMiniMaxApproximation by default minimizes the maximum value of the relative error between the approximation and expr.
  • GeneralMiniMaxApproximation[{fx, fy, g}, {t, {t0, t1}, m, n}, x] computes the error using a factor of g. In this case the mini-max approximation returned by GeneralMiniMaxApproximation is the rational function h[x] that minimizes the maximum value of the quantity (fy-h[fx])/g.
  • GeneralMiniMaxApproximation returns {abscissa, {approximation, maxerror}}, where abscissa is a list of the abscissas where the relative error is a local maximum, approximation is the rational approximant, and maxerror is the global maximum of the relative error.
  • When an approximation is given as the second argument of GeneralMiniMaxApproximation, it must have the same form as the result returned by GeneralMiniMaxApproximation.
  • The following options can be given:
Bias0bias in the automatic choice of interpolation points
Brake{5,5}braking to apply on iterative algorithm
DerivativesAutomaticfunction to use for derivatives
MaxIterations20maximum number of iterations to use
PlotFlagFalsewhether to plot relative error
PrintFlagFalsewhether to print status information
WorkingPrecisionMachinePrecisionprecision to use in internal computations