getFiRiskRegTS {ROptRegTS} | R Documentation |
Generic function for the computation of finite-sample risks in regression-type models. This function is rarely called directly. It is used by other functions.
getFiRiskRegTS(risk, ErrorDistr, Regressor, neighbor, ...) ## S4 method for signature ## 'fiUnOvShoot,Norm,UnivariateDistribution,ContNeighborhood' getFiRiskRegTS( risk, ErrorDistr, Regressor, neighbor, clip, stand, sampleSize, Algo, cont) ## S4 method for signature ## 'fiUnOvShoot,Norm,UnivariateDistribution,TotalVarNeighborhood' getFiRiskRegTS( risk, ErrorDistr, Regressor, neighbor, clip, stand, sampleSize, Algo, cont) ## S4 method for signature ## 'fiUnOvShoot,Norm,UnivariateDistribution,CondContNeighborhood' getFiRiskRegTS( risk, ErrorDistr, Regressor, neighbor, clip, stand, sampleSize, cont) ## S4 method for signature ## 'fiUnOvShoot,Norm,UnivariateDistribution,CondTotalVarNeighborhood' getFiRiskRegTS( risk, ErrorDistr, Regressor, neighbor, clip, stand, sampleSize, cont)
risk |
object of class |
ErrorDistr |
error distribution |
Regressor |
regressor |
neighbor |
object of class |
... |
additional parameters. |
clip |
optimal clipping bound/function. |
stand |
standardizing matrix. |
sampleSize |
integer: sample size. |
Algo |
"A" or "B". |
cont |
"left" or "right". |
The computation of the finite-sample under-/overshoot risk is based on FFT. For more details we refer to Subsections 12.1.3 and 12.2.3 of Kohl (2005).
The finite-sample risk is computed.
computes finite-sample under-/overshoot risk in methods for function 'getFixRobRegTypeIC'.
computes finite-sample under-/overshoot risk in methods for function 'getFixRobRegTypeIC'.
computes finite-sample under-/overshoot risk in methods for function 'getFixRobRegTypeIC'.
computes finite-sample under-/overshoot risk in methods for function 'getFixRobRegTypeIC'.
Matthias Kohl Matthias.Kohl@stamats.de
Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor. Verw. Geb. 10:269–278.
Rieder, H. (1989) A finite-sample minimax regression estimator. Statistics 20(2): 211–221.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.