function prt = dfdp (x, f, p, dp, func[, bounds])
 numerical partial derivatives (Jacobian) df/dp for use with leasqr
 --------INPUT VARIABLES---------
 x=vec or matrix of indep var(used as arg to func) x=[x0 x1 ....]
 f=func(x,p) vector initialsed by user before each call to dfdp
 p= vec of current parameter values
 dp= fractional increment of p for numerical derivatives
      dp(j)>0 central differences calculated
      dp(j)<0 one sided differences calculated
      dp(j)=0 sets corresponding partials to zero; i.e. holds p(j) fixed
 func=function (string or handle) to calculate the Jacobian for,
      e.g. to calc Jacobian for function expsum prt=dfdp(x,f,p,dp,'expsum')
 bounds=two-column-matrix of lower and upper bounds for parameters
      If no 'bounds' options is specified to leasqr, it will call
      dfdp without the 'bounds' argument.
----------OUTPUT VARIABLES-------
 prt= Jacobian Matrix prt(i,j)=df(i)/dp(j)
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 dfxpdp is more general and is meant to be used instead of dfdp in
 optimization.

Package: optim