getMaxIneff | R Documentation |
computes the maximal inefficiency of an IC for the radius range [0,Inf).
getMaxIneff(IC, neighbor, biastype = symmetricBias(), normtype = NormType(), z.start = NULL, A.start = NULL, maxiter = 50, tol = .Machine$double.eps^0.4, warn = TRUE, verbose = NULL, ...)
IC |
some IC of class |
neighbor |
object of class |
biastype |
a bias type of class |
normtype |
a norm type of class |
z.start |
initial value for the centering constant. |
A.start |
initial value for the standardizing matrix. |
maxiter |
the maximum number of iterations. |
tol |
the desired accuracy (convergence tolerance). |
warn |
logical: print warnings. |
verbose |
logical: if |
... |
additional arguments to be passed to |
The maximal inefficiency, i.e.; a number in [1,Inf).
Peter Ruckdeschel peter.ruckdeschel@fraunhofer.itwm.de
Hampel et al. (1986) Robust Statistics. The Approach Based on Influence Functions. New York: Wiley.
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not Knowing the Radius. Statistical Methods and Applications 17(1) 13-40.
Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing the Radius. Submitted. Appeared as discussion paper Nr. 81. SFB 373 (Quantification and Simulation of Economic Processes), Humboldt University, Berlin; also available under doi: 10.18452/3638
N0 <- NormLocationFamily(mean=2, sd=3) ## L_2 family + infinitesimal neighborhood neighbor <- ContNeighborhood(radius = 0.5) N0.Rob1 <- InfRobModel(center = N0, neighbor = neighbor) ## OBRE solution (ARE 95%) N0.ICA <- optIC(model = N0.Rob1, risk = asAnscombe(.95)) ## OMSE solution radius 0.5 N0.ICM <- optIC(model=N0.Rob1, risk=asMSE()) ## RMX solution N0.ICR <- radiusMinimaxIC(L2Fam=N0, neighbor=neighbor,risk=asMSE()) getMaxIneff(N0.ICA,neighbor) getMaxIneff(N0.ICM,neighbor) getMaxIneff(N0.ICR,neighbor) ## Don't run to reduce check time on CRAN N0ls <- NormLocationScaleFamily() ICsc <- makeIC(list(sin,cos),N0ls) getMaxIneff(ICsc,neighbor)
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