getIneffDiff | R Documentation |
Generic function for the computation of inefficiency differencies. This function is rarely called directly. It is used to compute the radius minimax IC and the least favorable radius.
getIneffDiff(radius, L2Fam, neighbor, risk, ...) ## S4 method for signature 'numeric,L2ParamFamily,UncondNeighborhood,asMSE' getIneffDiff( radius, L2Fam, neighbor, risk, loRad, upRad, loRisk, upRisk, z.start = NULL, A.start = NULL, upper.b = NULL, lower.b = NULL, OptOrIter = "iterate", MaxIter, eps, warn, loNorm = NULL, upNorm = NULL, verbose = NULL, ..., withRetIneff = FALSE)
radius |
neighborhood radius. |
L2Fam |
L2-differentiable family of probability measures. |
neighbor |
object of class |
risk |
object of class |
loRad |
the lower end point of the interval to be searched. |
upRad |
the upper end point of the interval to be searched. |
loRisk |
the risk at the lower end point of the interval. |
upRisk |
the risk at the upper end point of the interval. |
z.start |
initial value for the centering constant. |
A.start |
initial value for the standardizing matrix. |
upper.b |
upper bound for the optimal clipping bound. |
lower.b |
lower bound for the optimal clipping bound. |
OptOrIter |
character; which method to be used for determining Lagrange
multipliers |
MaxIter |
the maximum number of iterations |
eps |
the desired accuracy (convergence tolerance). |
warn |
logical: print warnings. |
loNorm |
object of class |
upNorm |
object of class |
verbose |
logical: if |
... |
further arguments to be passed on to |
withRetIneff |
logical: if |
The inefficieny difference between the left and the right margin of a given radius interval is computed.
computes difference of asymptotic MSEâ€“inefficiency for the boundaries of a given radius interval.
Matthias Kohl Matthias.Kohl@stamats.de
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
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.
radiusMinimaxIC
, leastFavorableRadius
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