Titlebook: Developments in Robust Statistics; International Confer Rudolf Dutter,Peter Filzmoser,Peter J. Rousseeuw Conference proceedings 2003 Spring

戲法

Jeffrey M. Adams,Warren H. Jonesst three moments of the data set, and hence it is strongly affected by the presence of one or more outliers. In this paper we propose several new measures of skewness which are more robust against outlying values. Their properties are compared using both real and simulated data.

PON

Handbook of Islamic Philosophy of Scienceontaining . A high depth point is a point whose depth is at least max. [.(P.)] For dimension . 2 we give a simple, easily implementable .(.(log .).) deterministic algorithm to compute a high depth point and we give an .(. log .) lower bound for this task.

比喻好

Delectable

978-3-642-63241-9Springer-Verlag Berlin Heidelberg 2003

blister

DAFT

BOGUS

https://doi.org/10.1007/978-981-19-0500-1We consider M-estimators for a class of semiparametric mixed-effect models without time-dependent covariates and show that the simple marginal estimation method is generally better than the same M-estimator applied to the de-correlated response based on a known or estimated covariance matrix for each subject.

使增至最大

Factorable

貿(mào)易

Robust Tools in SAS,In this article, I introduce robust routines and a procedure in SAS. The routines are in SAS/IML, acting as function calls. They are LTS, LMS, MCD, MVE, LAV, and MAD. These routines have been released in SAS/IML V8.2 or in previous versions. The SAS/STAT procedure, ROBUSTREG, is experimental.