MCEstimate-class {distrMod} | R Documentation |
MCEstimate-class.
Description
Class of minimum criterion estimates.
Objects from the Class
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).
Slots
name
Object of class
"character"
: name of the estimator.estimate
Object of class
"ANY"
: estimate.estimate.call
Object of class
"call"
: call by which estimate was produced.criterion
Object of class
"numeric"
: minimum value of the considered criterion.criterion.fct
Object 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 argumentuntransformed.estimate
method
Object 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.Infos
object of class
"matrix"
with two columns namedmethod
andmessage
: additional informations.optimwarn
object of class
"character"
warnings issued during optimization.optimReturn
object of class
"ANY"
the return value of the optimizer (orNULL
if, e.g., closed form solutions are used).startPar
— object of class
"ANY"
; filled either withNULL
(no starting value used) or with"numeric"
— the value of the starting parameter.asvar
object of class
"OptionalMatrix"
which may contain the asymptotic (co)variance of the estimator.samplesize
object of class
"numeric"
— the samplesize at which the estimate was evaluated.nuis.idx
object of class
"OptionalNumeric"
: indices ofestimate
belonging to the nuisance partfixed
object of class
"OptionalNumeric"
: the fixed and known part of the parameter.trafo
object of class
"list"
: a list with componentsfct
andmat
(see below).untransformed.estimate
Object of class
"ANY"
: untransformed estimate.untransformed.asvar
object of class
"OptionalNumericOrMatrix"
which may contain the asymptotic (co)variance of the untransformed estimator.completecases
object of class
"logical"
— complete cases at which the estimate was evaluated.startPar
object of class
"ANY"
; usually filled with argumentstartPar
of generating functionMCEstimator
,MLEstimator
,MDEstimator
.
Extends
Class "Estimate"
, directly.
Methods
- criterion
signature(object = "MCEstimate")
: accessor function for slotcriterion
.- criterion<-
signature(object = "MCEstimate")
: replacement function for slotcriterion
.- optimwarn
signature(object = "MCEstimate")
: accessor function for slotoptimwarn
.- optimReturn
signature(object = "MCEstimate")
: accessor function for slotoptimReturn
.- startPar
signature(object = "MCEstimate")
: accessor function for slotstartPar
.- criterion.fct
signature(object = "MCEstimate")
: accessor function for slotcriterion.fct
.- show
signature(object = "Estimate")
- coerce
signature(from = "MCEstimate", to = "mle")
: create a"mle"
object from a"MCEstimate"
object- profile
signature(fitted = "MCEstimate")
: coercesfitted
to class"mle"
and then calls the correspondingprofile
-method from package stats4; for details we confer to the corresponding man page.
Author(s)
Matthias Kohl Matthias.Kohl@stamats.de,
Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de
See Also
Estimate-class
, MCEstimator
,
MDEstimator
, MLEstimator
Examples
## (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