numDeriv (version 2016.8-1.1)

numDeriv-package: Accurate Numerical Derivatives

Description

Calculate (accurate) numerical approximations to derivatives.

Details

The main functions are

grad	  to calculate the gradient (first derivative) of a scalar 
  	  real valued function (possibly applied to all elements 
  	  of a vector argument).
jacobian  to calculate the gradient of a real m-vector valued
  	  function with real n-vector argument.
hessian   to calculate the Hessian (second derivative) of a scalar 
  	  real valued function with real n-vector argument.
genD	  to calculate the gradient and second derivative of a
  	  real m-vector valued function with real n-vector 
	  argument.

References

Linfield, G. R. and Penny, J. E. T. (1989) Microcomputers in Numerical Analysis. New York: Halsted Press.

Fornberg, B. and Sloan, D, M. (1994) ``A review of pseudospectral methods for solving partial differential equations.'' Acta Numerica, 3, 203-267.

Lyness, J. N. and Moler, C. B. (1967) ``Numerical Differentiation of Analytic Functions.'' SIAM Journal for Numerical Analysis, 4(2), 202-210.