View source: R/L2ParamFamily.R
| L2ParamFamily | R Documentation |
Generates an object of class "L2ParamFamily".
L2ParamFamily(name, distribution = Norm(), distrSymm,
main = 0, nuisance, trafo, param, props = character(0),
L2deriv = EuclRandVarList(RealRandVariable(list(function(x) {x}),
Domain = Reals())),
L2derivSymm, L2derivDistr, L2derivDistrSymm, FisherInfo)
name |
character string: name of the family |
distribution |
object of class |
distrSymm |
object of class |
main |
numeric vector: main parameter |
nuisance |
numeric vector: nuisance parameter |
trafo |
matrix: transformation of the parameter |
param |
object of class |
props |
character vector: properties of the family |
L2deriv |
object of class |
L2derivSymm |
object of class |
L2derivDistr |
object of class |
L2derivDistrSymm |
object of class |
FisherInfo |
object of class |
If name is missing, the default
“L2 differentiable parametric family of probability measures”
is used. In case distrSymm is missing it is set to
NoSymmetry().
If param is missing, the parameter is created via
main, nuisance and trafo as described
in ParamFamParameter. In case L2derivSymm is
missing, it is filled with an object of class FunSymmList
with entries NonSymmetric(). In case L2derivDistr is missing,
it is computed via imageDistr. If L2derivDistrSymm is missing,
it is set to an object of class DistrSymmList with entries
NoSymmetry(). In case FisherInfo is missing, it is computed
from L2deriv using E.
Object of class "L2ParamFamily"
Matthias Kohl Matthias.Kohl@stamats.de
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.
L2ParamFamily-class
F1 <- L2ParamFamily()
plot(F1)
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