asAnscombe-class | R Documentation |
Class of asymptotic Anscombe risk which is the ARE (asymptotic relative efficiency) in the ideal model obtained by an optimal bias robust IC .
Objects can be created by calls of the form new("asAnscombe", ...)
.
More frequently they are created via the generating function
asAnscombe
.
type
Object of class "character"
:
“optimal bias robust IC (OBRI) for given ARE (asymptotic relative efficiency)”.
eff
Object of class "numeric"
:
given ARE (asymptotic relative efficiency) to be attained in the ideal model.
biastype
Object of class "BiasType"
:
symmetric, one-sided or asymmetric
Class "asRiskwithBias"
, directly.
Class "asRisk"
, by class "asRiskwithBias"
.
Class "RiskType"
, by class "asRisk"
.
signature(object = "asAnscombe")
:
accessor function for slot eff
.
signature(object = "asAnscombe")
Peter Ruckdeschel peter.ruckdeschel@fraunhofer.itwm.de
F.J. Anscombe (1960). Rejection of Outliers. Technometrics 2(2): 123-146. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/00401706.1960.10489888")}.
F. Hampel et al. (1986). Robust Statistics. The Approach Based on Influence Functions. New York: Wiley. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/9781118186435")}.
M. Kohl (2005). Numerical Contributions to the Asymptotic Theory of Robustness. Dissertation. University of Bayreuth. https://epub.uni-bayreuth.de/id/eprint/839/2/DissMKohl.pdf.
H. Rieder (1994). Robust Asymptotic Statistics. Springer. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/978-1-4684-0624-5")}.
asRisk-class
, asAnscombe
new("asAnscombe")
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.