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Multivariate Confidence Intervals [PDF]
, 2017 Confidence intervals are a popular way to visualize and analyze data distributions. Unlike p-values, they can convey information both about statistical significance as well as effect size. However, very little work exists on applying confidence intervals to multivariate data.
Korpela, Jussi +4 more
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Computation of confidence intervals for Poisson processes [PDF]
, 1999 We present an algorithm which allows a fast numerical computation of Feldman-Cousins confidence intervals for Poisson processes, even when the number of background events is relatively large.
Aguilar-Saavedra, J. A.
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Randomization-Based Confidence Intervals for Cluster Randomized Trials [PDF]
, 2020 In a cluster randomized trial (CRT), groups of people are randomly assigned to different interventions. Existing parametric and semiparametric methods for CRTs rely on distributional assumptions or a large number of clusters to maintain nominal ...
Rabideau, Dustin J, Wang, Rui
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An adaptation theory for nonparametric confidence intervals [PDF]
, 2004 A nonparametric adaptation theory is developed for the construction of confidence intervals for linear functionals. A between class modulus of continuity captures the expected length of adaptive confidence intervals.
Cai, T. Tony, Low, Mark G.
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L'établissement d'une norme de qualification sûre dans un contexte non paramétrique [PDF]
Tutorials in Quantitative Methods for Psychology, 2008 La sélection de personnel pour un emploi se base souvent sur une norme psychométrique quun candidat doit atteindre afin dêtre recruté. Or, cette norme est statistique, cest-à-dire calculée sur les mesures dun simple échantillon de la population ...
Louis Laurencelle
doaj
Interval-Valued Intuitionistic Fuzzy Confidence Intervals
Journal of Intelligent Systems, 2019 Confidence intervals are useful tools for statistical decision-making purposes. In case of incomplete and vague data, fuzzy confidence intervals can be used for decision making under uncertainty.
Kahraman Cengiz +2 more
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Confidence Intervals for Stereological Estimators with Infinite Variance [PDF]
, 1981 A statistical estimator is discussed for using two-dimensional electron-microscope data to estimate NV, the number of organelles per unit volume. Under general assumptions, the estimator is shown to be the unique unbiased estimator of NV.
Franklin, Joel N.
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Confidence Intervals from Normalized Data: A correction to Cousineau (2005) [PDF]
Tutorials in Quantitative Methods for Psychology, 2008 Presenting confidence intervals around means is a common method of expressing uncertainty in data. Loftus and Masson (1994) describe confidence intervals for means in within-subjects designs. These confidence intervals are based on the ANOVA mean squared
Richard D. Morey
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A note on confidence intervals for deblurred images [PDF]
Opuscula Mathematica, 2020 We consider pointwise asymptotic confidence intervals for images that are blurred and observed in additive white noise. This amounts to solving a stochastic inverse problem with a convolution operator.
Michał Biel, Zbigniew Szkutnik
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Enhancing the physical significance of Frequentist confidence intervals [PDF]
, 2000 It is shown that all the Frequentist methods are equivalent from a statistical point of view, but the physical significance of the confidence intervals depends on the method.
Giunti, C.
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