Bayesian Estimation of the Binomial Parameter in Adaptive Designs With Treatment Selection
Statistics in Medicine, Volume 45, Issue 18-19, August 2026.ABSTRACT It is well‐known that results from adaptive multi‐arm experiments with treatment selection are subject to the bias of the selection process. In this article, we consider designs with a binary outcome that begin with randomized parallel arms.
Pierre Bunouf, Jean‐Marie Boher
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Statistics in Medicine, Volume 45, Issue 18-19, August 2026.ABSTRACT Health risk behaviors, including smoking, poor nutrition, alcohol misuse, and physical inactivity (SNAP), are leading contributors to chronic disease burden and healthcare costs worldwide. Their prevalence is shaped not only by individual demographic characteristics but also by contextual factors such as socioeconomic and occupational ...
Lorenzo Schiavon +3 more
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ESTIMATION OF THE KULLBACK-LEIBLER DIVERGENCE
, 2003 The Kullback-Leibler (KL) divergence K(fl, P) between a set O of probability measures (PMs) on ]R d and some PM P cannot be estimated by K(O, Pn) when O contains PM whose support is not included in the support of the empirical measure Pn. We propose an estimation procedure which avoids any smoothing of Pn.
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Journal of Geophysical Research: Solid Earth, Volume 131, Issue 8, August 2026.Abstract Fault slip occurs in both seismic and aseismic styles with spatial variability across scales, yet non‐unique source inference limits our ability to resolve slip complexity and dynamics. Here we evaluate the effect of spatial smoothing regularization in Bayesian frameworks by comparing an unregularized (BUR) approach that samples distributed ...
Xiong Zhao, Junle Jiang
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Toward Generative Machine Learning for Boosting Ensembles of Climate Simulations
Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.Abstract Accurately quantifying uncertainty in predictions and projections arising from irreducible internal climate variability is critical for decision‐making. Such uncertainty is typically assessed using ensembles produced with climate models. However, computational constraints impose a trade‐off between generating large ensembles required for ...
Parsa Gooya +2 more
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Estimating the spectrum in computed tomography via Kullback-Leibler divergence constrained optimization. [PDF]
Med Phys, 2019 Ha W +4 more
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Directional Dynamics of Fog: Irreversibility and Causal Coupling With Turbulence
Geophysical Research Letters, Volume 53, Issue 13, 16 July 2026.Abstract Fog prediction remains challenging because the physical processes governing its life cycle evolve across time scales and do not follow reversible or stationary dynamics. Using high‐frequency visibility observations from Sable Island, Canada, this study analyzes fog intensity and turbulent kinetic energy (TKE) for their time irreversibility and
Filippo Pesenti +4 more
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Kullback-Leibler Divergence Based Probabilistic Approach for Device-Free Localization Using Channel State Information. [PDF]
Sensors (Basel), 2019 Gao R, Zhang J, Xiao W, Li Y.
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Minimising the Kullback-Leibler Divergence for Model Selection in Distributed Nonlinear Systems. [PDF]
Entropy (Basel), 2018 Cliff OM, Prokopenko M, Fitch R.
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Kullback-Leibler Divergence Based Distributed Cubature Kalman Filter and Its Application in Cooperative Space Object Tracking. [PDF]
Entropy (Basel), 2018 Hu C, Lin H, Li Z, He B, Liu G.
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