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In this paper, we propose a robustness measure for LTI systems with causal, nonlinear diagonal perturbations with finite L_2-gain. We propose an algorithm to reliably compute this quantity. We show ho...
In this chapter, we discuss the robustness and reliability of the estimators of the probability of a rare event (or, more generally, of the expectation of some function of rare events) with respect to...
The asymptotic robustness of estimators as a function of a rarity parameter, in the context of rare-event simulation, is often qualified by properties such as bounded relative error (BRE) and logarith...
We proof that statistically, the maximum likelihood location estimator of exponential power distribution is strict super robust, when p < 1.
We propose an extension of quasi-Newton methods, and investigate the convergence and the robustness properties of the proposed update formulae for the approximate Hessian matrix. Fletcher has studied ...
Student's t statistic is nding applications today that were never envisaged when it was introduced more than a century ago. Many of these applications rely on properties, for example robustness aga...
Bayesian robustness modelling using heavy-tailed distributions pro- vides a exible approach to resolving problems of conicts between the data and prior distributions. See Dawid (1973) and OHaga (197...
The search tools and information retrieval systems on the contemporary Web use keywords, lexical analysis, popularity, and statistical methods to find and prioritize relevant data to a specific query....
This paper presents the conditions for robustness to the nonnormality on\break three test statistics for a general multivariate linear hypothesis, which were proposed under the normal assumption in a ...
An important aspect of multiple hypothesis testing is controlling the significance level, or the level of Type I error. When the test statistics are not independent it can be particularly challengin...
This article studies the robustness of di&reg;erent likelihood ratio tests proposed by Quandt ([1]) and ([2]), (Q-Test), Kim and Siegmund ([3]), (KS-Test), and Kim ([4]), (K-Test), to detect a chang...
Outlier robust diagnostics (graphically) using Robustly Studentized Robust Residuals (RSRR) and Partial Robustly Studentized Robust Residuals (PRSRR) are established. One problem with some robust re...
It is becoming increasingly apparent that probabilistic approaches can overcome conservatism and computational complexity of the classical worstcase deterministic framework and may lead to designs t...

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