Numeric Delta Method approximation for the variance-covariance matrix
Source:R/DeltaMethod.R
      DeltaMethod.RdComputes delta method variance-covariance matrix of results of any generic
function fct that computes a vector of estimates as a function of a
set of estimated parameters par.
Arguments
- par
- vector of parameter values at which estimates should be constructed 
- fct
- function that constructs estimates from parameters - par
- vcov
- variance-covariance matrix of the parameters 
- delta
- proportional change in parameters used to numerically estimate first derivative with central-difference formula (ignored) 
- ...
- any additional arguments needed by - fct
Value
a list with values
- variance
- estimated variance-covariance matrix of estimates derived by - fct
- partial
- matrix (or vector) of partial derivatives of - fctwith respect to the parameters- par
Details
The delta method (aka propagation of errors is based on Taylor series
approximation - see Seber's book on Estimation of Animal Abundance). It uses
the first derivative of fct with respect to par.
It also uses the variance-covariance matrix of the estimated parameters
which is derived in estimating the parameters and is an input argument.
The first argument of fct should be par which is a vector of
parameter estimates. It should return a single value (or vector) of
estimate(s).  The remaining arguments of fct if any can be passed to
fct by including them at the end of the call to DeltaMethod as
name=value pairs.