1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
|
\name{numDeriv-package}
\alias{numDeriv-package}
\alias{numDeriv.Intro}
\docType{package}
\title{Accurate Numerical Derivatives}
\description{Calculate (accurate) numerical approximations to derivatives.}
\details{
The main functions are
\preformatted{
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.
}
}
\author{Paul Gilbert, based on work by Xingqiao Liu, and Ravi Varadhan (who wrote complex-step derivative codes)}
\references{
Linfield, G. R. and Penny, J. E. T. (1989) \emph{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.'' \emph{Acta Numerica}, 3, 203-267.
Lyness, J. N. and Moler, C. B. (1967) ``Numerical Differentiation of Analytic
Functions.'' \emph{SIAM Journal for Numerical Analysis},
4(2), 202-210.
}
\keyword{package}
|
