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) ================================ dfxpdp is more general and is meant to be used instead of dfdp in optimization.
Package: optim