Description Usage Arguments Details Value Methods Author(s) References See Also Examples
Generic function for the computation of the optimal (i.e., minimal) risk for a probability model.
1 2 3 4 5 6 7 8 9  optRisk(model, risk, ...)
## S4 method for signature 'InfRobModel,asRisk'
optRisk(model, risk, z.start = NULL, A.start = NULL, upper = 1e4,
maxiter = 50, tol = .Machine$double.eps^0.4, warn = TRUE)
## S4 method for signature 'FixRobModel,fiUnOvShoot'
optRisk(model, risk, sampleSize, upper = 1e4, maxiter = 50,
tol = .Machine$double.eps^0.4, warn = TRUE, Algo = "A", cont = "left")

model 
probability model 
risk 
object of class 
... 
additional parameters 
z.start 
initial value for the centering constant. 
A.start 
initial value for the standardizing matrix. 
upper 
upper bound for the optimal clipping bound. 
maxiter 
the maximum number of iterations 
tol 
the desired accuracy (convergence tolerance). 
warn 
logical: print warnings. 
sampleSize 
integer: sample size. 
Algo 
"A" or "B". 
cont 
"left" or "right". 
In case of the finitesample risk "fiUnOvShoot"
one can choose
between two algorithms for the computation of this risk where the least favorable
contamination is assumed to be left or right of some bound. For more details
we refer to Section 11.3 of Kohl (2005).
The minimal risk is computed.
asymptotic covariance of L2 differentiable parameteric family.
asymptotic risk of a infinitesimal robust model.
finitesample under/overshoot risk of a robust model with fixed neighborhood.
Matthias Kohl Matthias.Kohl@stamats.de
Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor. Verw. Geb. 10:269–278.
Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. 8: 106–115.
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.
1  optRisk(model = NormLocationScaleFamily(), risk = asCov())

Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.