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Bayesian Robustness in Change Point Analysis
This paper focuses on robustness analysis of non-exchangeable product partition models (PPM), which are widely used to detect multiple change points....
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Quantitative robustness of instance ranking problems
Instance ranking problems intend to recover the ordering of the instances in a data set with applications in scientific, social and financial...
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Robustness of Principal Component Analysis with Spearman’s Rank Matrix
This paper is concerned with robust principal component analysis (PCA) based on spatial sign and spatial rank vectors. The most common PC approach is...
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A New Look at the Dirichlet Distribution: Robustness, Clustering, and Both Together
Compositional data have peculiar characteristics that pose significant challenges to traditional statistical methods and models. Within this...
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Robustness of the Sequential Efficient Design for Identifying a Target Subpopulation
Precision medicine is an innovative approach for tailoring treatments based on individual characteristics or biomarkers. Enrichment is a main...
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Robustness Aspects of Optimal Transport
Optimal transportation is a flourishing area of research and applications in many different fields. We provide an overview of the stability issues...
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The Diverging Definition of Robustness in Statistics and Computer Vision
Statistics and computer vision have a different role for robustness. Statisticians are primarily concerned with the theoretical properties of...
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On robustness of the relative belief ratio and the strength of its evidence with respect to the geometric contamination prior
The relative belief ratio becomes a widespread tool in many hypothesis testing problems. It measures the statistical evidence that a given statement...
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On the Robustness of Kernel-Based Pairwise Learning
It is shown that many results on the statistical robustness of kernel-based pairwise learning can be derived under basically no assumptions on the...
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Robustness of factor solutions in exploratory factor analysis
Replicability has become a highly discussed topic in psychological research. The debates focus mainly on significance testing and confirmatory...
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Robustness of a truncated estimator for the smaller of two ordered means
In this note, we consider the problem of estimating the smaller of two ordered means. Such problems frequently arise in applications where, for...
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Prediction Approach: Robustness, Bayesian Methods, Empirical Bayes
The classical design-based approach and its modification by the super-population modelling only narrates the properties of estimators for parameters...
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Robustness of lognormal confidence regions for means of symmetric positive definite matrices when applied to mixtures of lognormal distributions
Symmetric positive definite (SPD) matrices arise in a wide range of applications including diffusion tensor imaging (DTI), cosmic background...
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Goodness-of-fit test with a robustness feature
We develop a method originally proposed by R. A. Fisher into a general procedure, called tailoring, for deriving goodness-of-fit tests that are...
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Application of Multiple Imputation, Inverse Probability Weighting, and Double Robustness in Determining Blood Donor Deferral Characteristics in Malawi
Missing data occur in most epidemiological studies and may reduce internal validity of study findings. Biased and inefficient estimates may result if...
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Tolerance intervals in statistical software and robustness under model misspecification
A tolerance interval is a statistical interval that covers at least 100 ρ % of the population of interest with a 100(1− α ) % confidence, where ρ and α ...
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Fast rates of exponential cost function
In this paper, we introduce a new algorithm of learning with exponential cost function within the framework of statistical learning theory. We...
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Outlier-robust parameter estimation for unnormalized statistical models
Unnormalized statistical models are ubiquitous in modern statistical data analysis. Recent methods take a classification approach to estimate...
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Asymptotic expected sensitivity function and its applications to measures of monotone association
We introduce a new type of influence function, the asymptotic expected sensitivity function, which is often equivalent to but mathematically more...
