Results 1 to 10 of about 6,880 (105)
Quantifying dependencies for sensitivity analysis with multivariate input sample data [PDF]
, 2018 We present a novel method for quantifying dependencies in multivariate datasets, based on estimating the R\'{e}nyi entropy by minimum spanning trees (MSTs). The length of the MSTs can be used to order pairs of variables from strongly to weakly dependent,
Crommelin, D. T., Eggels, A. W.
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Estimation of reference intervals from small samples: an example using canine plasma creatinine [PDF]
, 2009 Background: According to international recommendations, reference intervals should be determined from at least 120 reference individuals, which often are impossible to achieve in veterinary clinical pathology, especially for wild animals.
Braun, Jean-Pierre +3 more
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Quantifying statistical uncertainty in the attribution of human influence on severe weather [PDF]
, 2018 Event attribution in the context of climate change seeks to understand the role of anthropogenic greenhouse gas emissions on extreme weather events, either specific events or classes of events.
Paciorek, Christopher J. +2 more
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Bayesian Nonparametric Calibration and Combination of Predictive Distributions [PDF]
, 2015 We introduce a Bayesian approach to predictive density calibration and combination that accounts for parameter uncertainty and model set incompleteness through the use of random calibration functionals and random combination weights. Building on the work
Bassetti, Federico +2 more
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Semiparametric Estimation of Structural Functions in Nonseparable Triangular Models [PDF]
, 2019 Triangular systems with nonadditively separable unobserved heterogeneity provide a theoretically appealing framework for the modelling of complex structural relationships.
Chernozhukov, Victor +4 more
core +3 more sources
, 2009 By representing the range of fair betting odds according to a pair of confidence set estimators, dual probability measures on parameter space called frequentist posteriors secure the coherence of subjective inference without any prior distribution.
Datta G. S. +16 more
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Robust estimation of risks from small samples [PDF]
, 2017 Data-driven risk analysis involves the inference of probability distributions from measured or simulated data. In the case of a highly reliable system, such as the electricity grid, the amount of relevant data is often exceedingly limited, but the impact
Strbac, Goran, Tindemans, Simon H.
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Likelihood Ratio as Weight of Forensic Evidence: A Closer Look
, 2017 The forensic science community has increasingly sought quantitative methods for conveying the weight of evidence. Experts from many forensic laboratories summarize their findings in terms of a likelihood ratio.
Iyer, Hari K., Lund, Steven P.
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Empirical likelihood-based tests for stochastic ordering
, 2013 This paper develops an empirical likelihood approach to testing for the presence of stochastic ordering among univariate distributions based on independent random samples from each distribution.
Barmi, Hammou El, McKeague, Ian W.
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Distribution Regression with Sample Selection, with an Application to Wage Decompositions in the UK
, 2019 We develop a distribution regression model under endogenous sample selection. This model is a semiparametric generalization of the Heckman selection model that accommodates much richer patterns of heterogeneity in the selection process and effect of the ...
Chernozhukov, Victor +2 more
core +1 more source