Class of L2 differentiable parametric families.
Objects can be created by calls of the form new("L2ParamFamily", ...)
.
More frequently they are created via the generating function
L2ParamFamily
.
name
:object of class "character"
:
name of the family.
distribution
:object of class "Distribution"
:
member of the family.
distrSymm
:Object of class "DistributionSymmetry"
:
symmetry of distribution
.
param
:object of class "ParamFamParameter"
:
parameter of the family.
props
:object of class "character"
:
properties of the family.
L2deriv
:object of class "EuclRandVariable"
:
L2 derivative of the family.
L2derivSymm
:object of class "FunSymmList"
:
symmetry of the maps included in L2deriv
.
L2derivDistr
:object of class "UnivarDistrList"
:
list which includes the distribution of L2deriv
.
L2derivDistrSymm
:object of class "DistrSymmList"
:
symmetry of the distributions included in L2derivDistr
.
FisherInfo
:object of class "PosDefSymmMatrix"
:
Fisher information of the family.
Class "ParamFamily"
, directly.
Class "ProbFamily"
, by class "ParamFamily"
.
signature(object = "L2ParamFamily")
:
accessor function for L2deriv
.
signature(object = "L2ParamFamily")
:
accessor function for L2derivSymm
.
signature(object = "L2ParamFamily")
:
accessor function for L2derivDistr
.
signature(object = "L2ParamFamily")
:
accessor function for L2derivDistrSymm
.
signature(object = "L2ParamFamily")
:
accessor function for FisherInfo
.
signature(object = "L2ParamFamily")
:
check centering of L2deriv
and compute precision
of Fisher information.
signature(object = "L2ParamFamily", fun = "EuclRandVariable", cond = "missing")
:
expectation of fun
under the distribution of object
.
signature(object = "L2ParamFamily", fun = "EuclRandMatrix", cond = "missing")
:
expectation of fun
under the distribution of object
.
signature(object = "L2ParamFamily", fun = "EuclRandVarList", cond = "missing")
:
expectation of fun
under the distribution of object
.
signature(x = "L2ParamFamily")
:
plot of distribution
and L2deriv
.
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.
# NOT RUN {
F1 <- new("L2ParamFamily")
plot(F1)
# }
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