Class of minimum criterion estimates.
Objects can be created by calls of the form new("MCEstimate", ...).
More frequently they are created via the generating functions
MCEstimator, MDEstimator or MLEstimator.
More specifically, MDEstimator, CvMMDEstimator,
and MLEstimator return objects of classes MDEstimate,
CvMMDEstimate, and MLEstimate respectively, which each
are immediate subclasses of MCEstimate (without further slots,
for internal use in method dispatch).
nameObject of class "character":
name of the estimator.
estimateObject of class "ANY":
estimate.
estimate.callObject of class "call":
call by which estimate was produced.
criterionObject of class "numeric":
minimum value of the considered criterion.
criterion.fctObject of class "function":
the considered criterion function; used for compatibility with class
"mle" from package stats4; should be a function
returning the criterion; i.e. a numeric of length 1 and should have
as arguments all named components of argument
untransformed.estimate
methodObject of class "character":
the method by which the estimate was calculated, i.e.;
"optim", "optimize", or "explicit calculation";
used for compatibility with class "mle" from package
stats4, could be any character value.
Infosobject of class "matrix"
with two columns named method and message:
additional informations.
optimwarnobject of class "character"
warnings issued during optimization.
optimReturnobject of class "ANY"
the return value of the optimizer (or NULL if, e.g.,
closed form solutions are used).
startPar--- object of class "ANY"; filled either
with NULL (no starting value used) or with "numeric"
--- the value of the starting parameter.
asvarobject of class "OptionalMatrix"
which may contain the asymptotic (co)variance of the estimator.
samplesizeobject of class "numeric" ---
the samplesize at which the estimate was evaluated.
nuis.idxobject of class "OptionalNumeric":
indices of estimate belonging to the nuisance part
fixedobject of class "OptionalNumeric":
the fixed and known part of the parameter.
trafoobject of class "list":
a list with components fct and mat (see below).
untransformed.estimateObject of class "ANY":
untransformed estimate.
untransformed.asvarobject of class "OptionalNumericOrMatrix"
which may contain the asymptotic (co)variance of the untransformed
estimator.
completecasesobject of class "logical" ---
complete cases at which the estimate was evaluated.
startParobject of class "ANY"; usually filled with
argument startPar of generating function MCEstimator,
MLEstimator, MDEstimator.
Class "Estimate", directly.
signature(object = "MCEstimate"):
accessor function for slot criterion.
signature(object = "MCEstimate"):
replacement function for slot criterion.
signature(object = "MCEstimate"):
accessor function for slot optimwarn.
signature(object = "MCEstimate"):
accessor function for slot optimReturn.
signature(object = "MCEstimate"):
accessor function for slot startPar.
signature(object = "MCEstimate"):
accessor function for slot criterion.fct.
signature(object = "Estimate")
signature(from = "MCEstimate", to = "mle"):
create a "mle" object from a "MCEstimate" object
signature(fitted = "MCEstimate"):
coerces fitted to class "mle" and then calls
the corresponding profile-method
from package stats4; for details we confer to the corresponding
man page.
Matthias Kohl Matthias.Kohl@stamats.de,
Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de
Estimate-class, MCEstimator,
MDEstimator, MLEstimator
## (empirical) Data
x <- rgamma(50, scale = 0.5, shape = 3)
## parametric family of probability measures
G <- GammaFamily(scale = 1, shape = 2)
MDEstimator(x, G)
(m <- MLEstimator(x, G))
m.mle <- as(m,"mle")
par(mfrow=c(1,2))
profileM <- profile(m)
## plot-profile throws an error
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