In most GWAS, the participants are assumed to be unrelated and to come from a single population. However, even in carefully designed studies, some degrees of relatedness and population stratification ...

In this sense, the proposed method is an extension of the variance of the regression estimator for two-stage sampling. The method is applied to quarterly data from the Labor Force Survey where ...

Spatial variation is often encountered when large scale field trials are conducted which can result in biased estimation or prediction of treatment (i.e. genotype) values. An effective removal of ...

Abstract: We study variance reduction schemes for stochastic generalized Nash equilibrium problems. Specifically, we consider two instances of the extragradient algorithm to find a Nash equilibrium ...

Subsampling and block resampling methods have been suggested in the literature to nonparametrically estimate the variance of statistics computed from spatial data. Usually stationary data are required ...

Abstract: Learning-based methods have been widely applied to solve electromagnetic (EM) inverse scattering problems (ISPs). In learning-based induced current inversions, the deterministic part of the ...