Description Arguments Generation Methods Note See Also
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 
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

call 
an image of the call to 
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
.
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