Generic Function for making ICs consistent at a possibly different model
Generic function for providing centering and Fisher consistency of ICs.
makeIC(IC, L2Fam, ...)
## S4 method for signature 'IC,L2ParamFamily'
makeIC(IC, L2Fam, ..., diagnostic = FALSE)
## S4 method for signature 'list,L2ParamFamily'
makeIC(IC, L2Fam, forceIC = TRUE, name, Risks,
Infos, modifyIC = NULL, ..., diagnostic = FALSE)
## S4 method for signature 'function,L2ParamFamily'
makeIC(IC, L2Fam, forceIC = TRUE, name,
Risks, Infos, modifyIC = NULL, ..., diagnostic = FALSE)IC |
object of class |
L2Fam |
L2-differentiable family of probability measures; may be missing,
in which case it is replaced by the family in slot |
forceIC |
logical; shall centeredness and Fisher consistency be enforced applying an affine linear transformation? |
name |
Object of class |
Risks |
object of class |
Infos |
matrix of characters with two columns
named |
modifyIC |
object of class |
... |
additional parameters to be passed to expectation |
diagnostic |
logical; if |
Argument IC is transformed affinely such that the transformed IC
satisfies the defining side conditions of an IC, i.e., centeredness and
Fisher consistency:
E[IC]=0
E[IC Lambda'] = D
where Lambda is the L2 derivative of the model and D is
the Jacobian of transformation trafo.
Diagnostics on the involved integrations are available if argument
diagnostic is TRUE. Then there is attribute diagnostic
attached to the return value, which may be inspected
and accessed through showDiagnostic and
getDiagnostic.
An IC of class "IC" at the model.
signature(IC = "IC", L2Fam = "missing": creates
an object of class "IC" at the parametric model of its own
slot CallL2Fam; enforces IC conditions
centeredness and Fisher consistency, applying an affine linear
transformation.
signature(IC = "IC", L2Fam = "L2ParamFamily": creates
an object of class "IC" at the parametric model L2Fam;
enforces IC conditions centeredness and Fisher consistency,
applying an affine linear transformation.
signature(IC = "list", L2Fam = "L2ParamFamily": creates
an object of class "IC" out of a list of functions given by argument
IC at the parametric model L2Fam;
enforces IC conditions centeredness and Fisher consistency,
applying an affine linear transformation.
signature(IC = "function", L2Fam = "L2ParamFamily": creates
an object of class "IC" out of a function given by argument
IC at the parametric model L2Fam;
enforces IC conditions centeredness and Fisher consistency,
applying an affine linear transformation.
Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.
## default IC
IC1 <- new("IC")
## L2-differentiable parametric family
B <- BinomFamily(13, 0.3)
## check IC properties
checkIC(IC1, B)
## make IC
IC2 <- makeIC(IC1, B)
## check IC properties
checkIC(IC2)
## slot modifyIC is filled in case of IC2
IC3 <- modifyIC(IC2)(BinomFamily(13, 0.2), IC2)
checkIC(IC3)
## identical to
checkIC(IC3, BinomFamily(13, 0.2))
IC4 <- makeIC(sin, B)
checkIC(IC4)
(IC5 <- makeIC(list(function(x)x^3), B, name="a try"))
plot(IC5)
checkIC(IC5)
## don't run to reduce check time on CRAN
N0 <- NormLocationScaleFamily()
IC6 <- makeIC(list(sin,cos),N0)
plot(IC6)
checkIC(IC6)
getRiskIC(IC6,risk=trAsCov())$trAsCov$value
getRiskIC(IC6,risk=asBias(),neighbor=ContNeighborhood())$asBias$valuePlease choose more modern alternatives, such as Google Chrome or Mozilla Firefox.