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On Maximizing a Robustness Measure for Structured Nonlinear Perturbations
Maximizing Robustness Measure Structured Nonlinear Perturbations
2015/7/13
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...
Robustness Properties and Confidence Interval Reliability
Robustness Properties Confidence Interval Reliability
2015/7/6
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...
Asymptotic Robustness of Estimators in Rare-Event Simulation
Asymptotic Robustness Estimators Rare-Event Simulation
2015/7/6
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...
The Super Robustness of Maximum Likelihood Location Estimator of Exponential Power Distribution, when p < 1
The Super Robustness Maximum Likelihood Location Estimator Exponential Power Distribution p < 1
2012/9/18
We proof that statistically, the maximum likelihood location estimator of exponential power distribution is strict super robust, when p < 1.
A Bregman Extension of quasi-Newton updates II: Convergence and Robustness Properties
A Bregman Extension quasi-Newton updates II Convergence Robustness Properties
2010/10/19
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 ...
Robustness and accuracy of methods for high dimensional data analysis based on Student's t statistic
Bootstrap central limit theorem classication dimension reduction higher criticism large deviation probability
2010/3/9
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 regularly varying distributions
Bayesian robustness heavy-tailed distributions conicting information regular variation credence
2009/9/21
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...
Robustness of the Sequential Testing Procedures for the Feneralized Life Distributions
Robustness the Sequential Testing Procedures the Feneralized Life Distributions
2009/9/17
Robustness of the Sequential Testing Procedures for the Feneralized Life Distributions。
Relation Robustness Evaluation for the Semantic Associations
Semantic web emantic association’s search elation robustness anking semantic relations elationship search iscovery que
2009/7/16
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....
Conditions for Robustness to Nonnormality on Test Statistics in a GMANOVA Model
actual test size asymptotic expansion Bartlett correction chi-square approximation general multivariate linear hypothesis modified Bartlett correction
2009/3/5
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 ...
Robustness of multiple testing procedures against dependence
False-discovery rate family-wise error rate linear process moving average multiplicity significance level
2010/3/18
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...
ROBUSTNESS OF TWO-PHASE REGRESSION TESTS
segmented regression models likelihood ratio tests robustness
2009/2/26
This article studies the robustness of di®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...
Graphical display in outlier diagnostics：adequacy and robustness
Masking outlier robust diagnostics robust residuals swamping
2009/2/23
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...
Probabilistic Robustness Analysis——Risks，Complexity and Algorithms
Robustness analysis risk analysis randomized algorithms uncertain system computational complexity
2010/4/30
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...