Results 11 to 20 of about 8,657 (149)
Environmental and Resource Economics, 2022 The reduction of greenhouse gas emissions is the key action to limit global warming. An important source of greenhouse gas emissions and pollution is the inefficiency of production processes.
J. Krüger, Moritz Tarach
semanticscholar +1 more source
Resampling-based confidence intervals and bands for the average treatment effect in observational studies with competing risks [PDF]
Statistics and computing, 2023 The g-formula can be used to estimate the treatment effect while accounting for confounding bias in observational studies. With regard to time-to-event endpoints, possibly subject to competing risks, the construction of valid pointwise confidence ...
Jasmin Rühl, Sarah Friedrich
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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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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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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
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Nonparametric asymptotic confidence intervals for extreme quantiles
Scandinavian Journal of Statistics, 2022 In this paper, we propose new asymptotic confidence intervals for extreme quantiles, that is, for quantiles located outside the range of the available data. We restrict ourselves to the situation where the underlying distribution is heavy‐tailed.
L. Gardes, Samuel Maistre
semanticscholar +1 more source
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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Confidence Intervals for Randomized Quasi-Monte Carlo Estimators
Online World Conference on Soft Computing in Industrial Applications, 2023 Randomized Quasi-Monte Carlo (RQMC) methods provide unbiased estimators whose variance often converges at a faster rate than standard Monte Carlo as a function of the sample size.
P. L’Ecuyer +3 more
semanticscholar +1 more source
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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