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Robust Estimation through Schoenberg transformations
Correspondence Analysis Euclidean distances Huber func-tion Huygens principles M-estimators Schoenberg transformations Tukey bisquare
2011/3/24
Schoenberg transformations, mapping Euclidean configurations into Euclidean configurations, define in turn a transformed inertia, whose minimization produces robust location estimates. The procedure o...
According to the Loss Distribution Approach, the operational risk of a bank is determined as 99.9% quantile of the respective loss distribution, covering unexpected severe events. The 99.9% quantile i...
Robust estimation and finite population。
The papex deals with the concept of robustness given
by Zielidski (see [17J and [18]). The uniformly most bias-robust
estimates of the scale parameter, based on order statistics and
spacings, for s...
Estimating functions of variance components is
considered. The problem is to find an estimator, the variance of
which changes as little as possible when the kurtosis of the
underlying distribution ...
Robust estimation and forecasting for beta-mixed hierarchical models of grouped binary data
grouped binary data distortions hierarchical models beta-binomial beta-logistic robust estimation forecasting
2009/2/23
The paper focuses on robust estimation and forecasting techniques for grouped binary data with
misclassified responses. It is assumed that the data are described by the beta-mixed hierarchical model ...