| mpl.object {nlreg} | R Documentation |
Class of objects returned when calculating the maximum adjusted profile likelihood estimates of the variance parameters of a nonlinear heteroscedastic model.
The following components must be included in a mpl object:
varPar |
the maximum adjusted profile likelihood estimates of the variance parameters. |
coefficients |
the constrained MLEs of the regression coefficients given the maximum adjusted profile likelihood estimates of the variance parameters. |
offset |
the values passed through the offset argument in the call
to mpl.nlreg that generated the mpl
object and to which the variance parameters were fixed.
|
varParMLE |
the MLEs of the variance parameters. |
coefMLE |
the MLEs of the regression coefficients. |
varParCov |
the (asymptotic) covariance matrix of the variance parameters, that is, the corresponding block in the inverse of the observed information matrix. |
coefCov |
the (asymptotic) covariance matrix of the regression coefficients, that is, the corresponding block in the inverse of the observed information matrix. |
lmp |
the adjusted profile log likelihood from the fit. |
lp |
the profile log likelihood from the fit. |
stats |
the indicator of which higher order solution was used. |
formula |
the model formula. |
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.
|
nobs |
the number of observations. |
iter |
the number of interations needed for convergence; only if
offset is not NULL.
|
call |
an image of the call to mpl.nlreg, but with all the
arguments explicitly named.
|
ws |
a list containing information that is used in subsequent
calculations, that is:
|
This class of objects is returned by the
mpl.nlreg function. Class mpl inherits
from class nlreg.
Objects of this class have methods for the functions
print, summary,
coef and param.
The coefficients and variance parameters 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 used by users, but rather contain information used by
functions such as summary.