marginalOptim {BIGL}  R Documentation 
This function is an alternative to nonlinear least squares and
provides optimization framework with optim
function.
It is however noticeably slower than NLS methods and can be especially
time consuming in large datasets, in particular if bootstrap statistics
are calculated.
marginalOptim(data, transforms = NULL, start, model, ...)
data 
Doseresponse dataframe. Marginal data will be extracted from it automatically. 
transforms 
Transformation functions. If nonnull, 
start 
Starting parameter values. If not specified, they will be
obtained from 
model 
List with model parameters. Typically, this is an output from

... 
Further parameters passed to 
Variancecovariance matrix which is returned by optim
is based on the fact that minimization of sumofsquared residuals leads
essentially to a maximum likelihood estimator and so variancecovariance
matrix can be estimated using inverse Hessian evaluated at the optimal
parameters. In some cases, so obtained variancecovariance matrix might not
be positivedefinite which probably means that estimates are unstable
because of either a poor choice of initial values or poor properties of the
data itself.