Robust Methods in Biostatistics

Abstract

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Large Scale Statistical Analysis of GEO Datasets

“…to use robust statistics. This implies replacing the data of each sample by their empirical distribution function, or some other distribution-free score [7,8]. Even after data have been homogenized, important discrepancies remain.…”

“…As in [9][10][11], we have made the choice to use robust statistics [7,8]. This implies changing the columns of a data matrix into distribution free values.…”

“…A solution is provided by robust (or distribution-free) statistics [7,8]. Robust methods amount to replacing actual values by ranks, or equivalently by empirical distribution functions or van der Waerden's normal scores [7, p. 309].…”

Defensive Signal Processing: The Case for the Use of Nonparametric and Robust Statistical Methods to Reduce Product Liability Exposure

“…A commonly used value is c Hub = 1.345. It is in fact the boundedness of ψ which makes the M-estimator robust [20,24,[26][27][28].…”

“…a linear function in x (see [27], p. 17). The limit of S C n (x) for n → ∞ then represents the asymptotic influence of the additional arbitrary data point x on the sample mean.…”