Detecting gene–environment interactions with rare variants is critical in dissecting the etiology of common diseases. Interactions with rare haplotype variants (rHTVs) are of particular interest. At ...
The use of complex sampling designs in population-based case-control studies is becoming more common, particularly for sampling the control population. This is prompted by all the usual cost and ...
This is a preview. Log in through your library . Abstract Multiple imputation is popular for handling item nonresponse in survey sampling. Current multiple imputation techniques with complex survey ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Enhanced sampling techniques are a promising approach to obtain reliable binding ...
Researchers at EPFL have made a breakthrough in understanding how neural network-based generative models perform against traditional data sampling techniques in complex systems, unveiling both ...
Monte Carlo Simulations take the spotlight when we discuss the photorealistic rendering of natural images. Photorealistic rendering, or, in layman’s words, creating indistinguishable “clones” of ...
Abstract: In empirical research on large-scale complex networks, sampling is a necessary way to collect data. Current methods commonly-used are Y2H-derived partial sampling strategy and random ...
Abstract: Whether the sampling subnets can accurately represent the topology and dynamics of the original networks is an important research topic. To improve the quality of network sampling, this ...
When that message comes from Uncle Sam, it’s often delivered in the form of a survey. The federal government amasses an astounding amount of data each year from nationally representative surveys on ...
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