nlreg.object {nlreg} | R Documentation |
Class of objects returned when fitting a nonlinear heteroscedastic model.
The following components must be included in a nlreg
object:
coef |
the MLEs of the regression coefficients, that is, of
the parameters appearing in the right-hand side of the
formula argument in the call that generated the
nlreg object.
|
varPar |
the MLEs of the variance parameters appearing in the
weights argument of the call that generated the
nlreg object. If this argument was missing, the
MLE of log(s^2) , the
logarithm of the constant variance, is returned.
|
offset |
a numerical vector with a single named element indicating the parameter of interest and the value to which it was fixed while fitting the nonlinear model. |
logLik |
the log likelihood from the fit. |
meanFun |
the formula expression of the mean function. |
varFun |
the formula expression of the variance function. |
data |
a list representing a summary of the original data with the
following components:
|
fitted |
the fitted values, that is, the mean function evaluated at each data point. |
weights |
the variance function evaluated at each data point. |
residuals |
the response/standardized residuals from the fit. |
start |
the starting values used to initialize the fitting routine. |
call |
an image of the call to nlreg , but with all the arguments
explicitly named.
|
ws |
a list containing information that is used in subsequent
calculations with the following components:
|
This class of objects is returned by the nlreg
function to
represent a fitted nonlinear heteroscedastic model. Class
nlreg
inherits from class nls
, which represents a
homoscedastic nonlinear model fit.
Objects of this class have methods for the functions
print
, summary
,
fitted
among others.
The residuals, fitted values and coefficients should be extracted by
the generic functions of the same name, rather than by the $
operator.
The data
and ws
components are not intended to be
directly accessed by users, but rather contain information invoked
by functions such as profile
and
nlreg.diag
.