# jacobianest.m

Estimate of the Jacobian matrix of a vector valued function of n variables.

## Syntax

    [jac,err] = jacobianest(fun,x0)


## Description

Simple finite difference estimation.

## Arguments

 fun - (vector valued) analytical function to differentiate.
fun must be a function of the vector or array x0.

x0  - vector location at which to differentiate fun
If x0 is an nxm array, then fun is assumed to be
a function of n*m variables.


## Outputs

 jac - array of first partial derivatives of fun.
Assuming that x0 is a vector of length p
and fun returns a vector of length n, then
jac will be an array of size (n,p)

err - vector of error estimates corresponding to
each partial derivative in jac.