ms()
to represent
the result of fitting a nonlinear model by general minimization.
The object contains the final parameter values, corresponding function
and gradient values, and final values for the flags generated internally
in the minimization algorithm.
If the model was defined in terms of
n
contributions from
n
observations,
as in the case of minimizing the negative log-likelihood, the
function value and derivatives will also be returned on a per-observation
form for use in plots, etc.
ms()
, but with all the arguments explicitly
named, so that the
data
component of the call will always give the
data
argument, and so on.
hessian
, only the lower triangle is returned.
N
giving the contributions of the
N
observations to the value.
N
rows giving the contributions of the
N
observations to
the gradients. The
slopes
component is returned only if derivatives are
computed.
N
rows giving the contributions of the
N
observations to the
hessian of the objective function. The
curves
component is returned only
if second derivatives are computed.
dmnf
in the Port library.
parameters
component
to the named parameters (e.g., as specified by the
start
argument).
Note that the names attribute of
parameters
gives the individual
names; where an element of
assign
is of length > 1, the individual
parameter names will be extended to be unique.
The elements of this list are weakly analagous to the terms in a
linear model, and the
assign
components in this sense serve the
same function in both cases.
data
argument with the final value of the parameters.
This is returned if the
control
in the fit included
data=T
.
The returned data will be a paremetrized data frame if the data in
the fit inherited from
"data.frame"
.