Estimating Extreme Wave Surges in the Presence of Missing Data
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DOI: 10.1002/env.70036
Abstract: The block maxima approach, which consists of dividing a series of observations into equal‐sized blocks to extract the block maxima, is commonly used for identifying and modeling extreme events using the generalized extreme value (GEV)… read more here.
Keywords: presence missing; block; extreme wave; block maxima ... See more keywords
Low-regret shape optimization in the presence of missing Dirichlet data
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DOI: 10.1088/1361-6420/adfc91
Abstract: A shape optimization problem subject to an elliptic equation in the presence of missing data on the Dirichlet boundary condition is considered. It is formulated by optimizing the deformation field that varies the spatial domain… read more here.
Keywords: presence missing; shape optimization; low regret;
Changepoint inference in the presence of missing covariates for principal surrogate evaluation in vaccine trials
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DOI: 10.1093/biomet/asaa100
Abstract: We consider the use of threshold-based regression models to evaluate immune response biomarkers as principal surrogate markers of a vaccine’s protective effect. Threshold-based regression models, which allow the relationship between a clinical outcome and a… read more here.
Keywords: vaccine efficacy; missing covariates; principal surrogate; vaccine ... See more keywords
Assessing Intervention Effects in the Presence of Missing Scores
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DOI: 10.3390/educsci11020076
Abstract: Due to repeated observations of an outcome behavior in N-of-1 or single-case design (SCD) intervention studies, the occurrence of missing scores is inevitable in such studies. Approximately 21% of SCD articles published in five reputable… read more here.
Keywords: assessing intervention; intervention; intervention effects; effects presence ... See more keywords