OBJECTIVE To determine how specific methodological choices affect "data-driven" simplifications of event-related potentials (ERPs) using principal components analysis (PCA). The usefulness of the extracted component measures can be evaluated by knowledge about the variance distribution of ERPs, which are characterized by the removal of baseline activity. The variance should be small before and ...

We introduce a covariance cleaning method which works well in the very high-dimensional regime, i.e. when there are many more assets than data points per asset. This opens way to unconditional reactive portfolio optimization not enough calibrate dynamical conditional models, happens, for example, new appear market. The is k-fold boosted version of Bootstrapped Average Hierarchical Clustering pr...

A rigorous test of our understanding of evolutionary quantitative genetics would be to predict accurately the equilibrium distribution of a character from empirical estimates of the relevant parameters in a mutation-selection-drift balance model. An aspect of this problem that is amenable to experimental analysis is the distribution of the effects of new mutations. This study quantifies the div...

A novel web-based tool PedWiz that pipelines the informatics process for pedigree data is introduced. PedWiz is designed to assist researchers in the analysis of pedigree data. It provides a convenient tool for pedigree informatics: descriptive statistics, relative pairs, genetic similarity coefficients, the variance-covariance matrix for three estimated coefficients of allele identical-by-desc...

Data processing in geodetic applications often relies on the least-squares method, for which one needs a proper stochastic model of the observables. Such a realistic covariance matrix allows one first to obtain the best (minimum variance) linear unbiased estimator of the unknown parameters; second, to determine a realistic precision description of the unknowns; and, third, along with the distri...