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Adaptive Robust Confidence Intervals [PDF]
This paper studies the construction of adaptive confidence intervals under Huber's contamination model when the contamination proportion is unknown. For the robust confidence interval of a Gaussian mean, we show that the optimal length of an adaptive interval must be exponentially wider than that of a non-adaptive one.
Yuetian Luo, Chao Gao
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Adaptively robust small area estimation: Balancing robustness and efficiency of empirical bayes confidence intervals [PDF]
Scandinavian Journal of StatisticsABSTRACTEmpirical Bayes (EB) small area estimation based on the well‐known Fay‐Herriot model may produce unreliable estimates when outlying areas exist. Existing robust methods against outliers or model misspecification are generally inefficient when the assumed distribution is plausible.
Daisuke Kurisu +2 more
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Journal of Biostatistics and EpidemiologyBachground :While the main advantage of the confidence interval is that it enables more precise evaluations when the risk for the outcome of interest is related to the cluster size, the predicted confidence interval width demonstrates the degree of ...
Tareef Fadhil Raham +2 more
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ROBUSTNESS OF WILKS' CONSERVATIVE ESTIMATE OF CONFIDENCE INTERVALS [PDF]
International Journal for Uncertainty Quantification, 2015 The striking generality and simplicity of Wilks’ method has made it popular for quantifying modeling uncertainty. A conservative estimate of the confidence interval is obtained from a very limited set of randomly drawn model sample values, with probability set by the assigned so-called stability. In contrast, the reproducibility of the estimated limits,
Jan Peter Hessling, Jeffrey Uhlmann
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Model validation for a noninvasive arterial stenosis detection problem [PDF]
Mathematical Biosciences and Engineering, 2013 A current thrust in medical research is the development of a non-invasive method for detection, localization, and characterization of an arterial stenosis (a blockage or partial blockage in an artery).
H. Thomas Banks +8 more
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Robust Confidence Intervals in High-Dimensional Left-Censored Regression [PDF]
, 2016 62 pages, 4 ...
Jelena Bradić, Jiaqi Guo
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Robust confidence intervals for meta-regression with interaction effects [PDF]
Computational StatisticsAbstractMeta-analysis is an important statistical technique for synthesizing the results of multiple studies regarding the same or closely related research question. So-called meta-regression extends meta-analysis models by accounting for study-level covariates.
Maria Thurow +4 more
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Robust Confidence Intervals for Meta-Regression with Interaction Effects [PDF]
, 2022 main paper: 23 pages, 6 figures; supplement: 148 pages, 131 ...
Eric S. Knop +3 more
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Sequential confidence intervals based on robust estimators [PDF]
Banach Center Publications, 1985 Jana Jurečková
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Methodology, 2022 Researchers often examine whether two continuous variables (X and Y) are linearly related. Pearson’s correlation (r) is a widely-employed statistic for assessing bivariate linearity.
Johnson Ching-Hong Li
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